Migrate release files 241-270

ext/marker_embeddings/fasta/P01732.fasta

@@ -0,0 +1,5 @@
+>sp|P01732|CD8A_HUMAN T-cell surface glycoprotein CD8 alpha chain OS=Homo sapiens OX=9606 GN=CD8A PE=1 SV=1
+MALPVTALLLPLALLLHAARPSQFRVSPLDRTWNLGETVELKCQVLLSNPTSGCSWLFQP
+RGAAASPTFLLYLSQNKPKAAEGLDTQRFSGKRLGDTFVLTLSDFRRENEGYYFCSALSN
+SIMYFSHFVPVFLPAKPTTTPAPRPPTPAPTIASQPLSLRPEACRPAAGGAVHTRGLDFA
+CDIYIWAPLAGTCGVLLLSLVITLYCNHRNRRRVCKCPRPVVKSGDKPSLSARYV

ext/marker_embeddings/fasta/P02533.fasta

@@ -0,0 +1,9 @@
+>sp|P02533|K1C14_HUMAN Keratin, type I cytoskeletal 14 OS=Homo sapiens OX=9606 GN=KRT14 PE=1 SV=4
+MTTCSRQFTSSSSMKGSCGIGGGIGGGSSRISSVLAGGSCRAPSTYGGGLSVSSSRFSSG
+GACGLGGGYGGGFSSSSSSFGSGFGGGYGGGLGAGLGGGFGGGFAGGDGLLVGSEKVTMQ
+NLNDRLASYLDKVRALEEANADLEVKIRDWYQRQRPAEIKDYSPYFKTIEDLRNKILTAT
+VDNANVLLQIDNARLAADDFRTKYETELNLRMSVEADINGLRRVLDELTLARADLEMQIE
+SLKEELAYLKKNHEEEMNALRGQVGGDVNVEMDAAPGVDLSRILNEMRDQYEKMAEKNRK
+DAEEWFFTKTEELNREVATNSELVQSGKSEISELRRTMQNLEIELQSQLSMKASLENSLE
+ETKGRYCMQLAQIQEMIGSVEEQLAQLRCEMEQQNQEYKILLDVKTRLEQEIATYRRLLE
+GEDAHLSSSQFSSGSQSSRDVTSSSRQIRTKVMDVHDGKVVSTHEQVLRTKN

ext/marker_embeddings/fasta/P07766.fasta

@@ -0,0 +1,5 @@
+>sp|P07766|CD3E_HUMAN T-cell surface glycoprotein CD3 epsilon chain OS=Homo sapiens OX=9606 GN=CD3E PE=1 SV=2
+MQSGTHWRVLGLCLLSVGVWGQDGNEEMGGITQTPYKVSISGTTVILTCPQYPGSEILWQ
+HNDKNIGGDEDDKNIGSDEDHLSLKEFSELEQSGYYVCYPRGSKPEDANFYLYLRARVCE
+NCMEMDVMSVATIVIVDICITGGLLLLVYYWSKNRKAKAKPVTRGAGAGGRQRGQNKERP
+PPVPNPDYEPIRKGQRDLYSGLNQRRI

ext/marker_embeddings/fasta/P08575-4.fasta

@@ -0,0 +1,21 @@
+>sp|P08575-4|PTPRC_HUMAN Isoform 2 of Receptor-type tyrosine-protein phosphatase C OS=Homo sapiens OX=9606 GN=PTPRC
+MTMYLWLKLLAFGFAFLDTEVFVTGQSPTPSPTDAYLNASETTTLSPSGSAVISTTTIAT
+TPSKPTCDEKYANITVDYLYNKETKLFTAKLNVNENVECGNNTCTNNEVHNLTECKNASV
+SISHNSCTAPDKTLILDVPPGVEKFQLHDCTQVEKADTTICLKWKNIETFTCDTQNITYR
+FQCGNMIFDNKEIKLENLEPEHEYKCDSEILYNNHKFTNASKIIKTDFGSPGEPQIIFCR
+SEAAHQGVITWNPPQRSFHNFTLCYIKETEKDCLNLDKNLIKYDLQNLKPYTKYVLSLHA
+YIIAKVQRNGSAAMCHFTTKSAPPSQVWNMTVSMTSDNSMHVKCRPPRDRNGPHERYHLE
+VEAGNTLVRNESHKNCDFRVKDLQYSTDYTFKAYFHNGDYPGEPFILHHSTSYNSKALIA
+FLAFLIIVTSIALLVVLYKIYDLHKKRSCNLDEQQELVERDDEKQLMNVEPIHADILLET
+YKRKIADEGRLFLAEFQSIPRVFSKFPIKEARKPFNQNKNRYVDILPYDYNRVELSEING
+DAGSNYINASYIDGFKEPRKYIAAQGPRDETVDDFWRMIWEQKATVIVMVTRCEEGNRNK
+CAEYWPSMEEGTRAFGDVVVKINQHKRCPDYIIQKLNIVNKKEKATGREVTHIQFTSWPD
+HGVPEDPHLLLKLRRRVNAFSNFFSGPIVVHCSAGVGRTGTYIGIDAMLEGLEAENKVDV
+YGYVVKLRRQRCLMVQVEAQYILIHQALVEYNQFGETEVNLSELHPYLHNMKKRDPPSEP
+SPLEAEFQRLPSYRSWRTQHIGNQEENKSKNRNSNVIPYDYNRVPLKHELEMSKESEHDS
+DESSDDDSDSEEPSKYINASFIMSYWKPEVMIAAQGPLKETIGDFWQMIFQRKVKVIVML
+TELKHGDQEICAQYWGEGKQTYGDIEVDLKDTDKSSTYTLRVFELRHSKRKDSRTVYQYQ
+YTNWSVEQLPAEPKELISMIQVVKQKLPQKNSSEGNKHHKSTPLLIHCRDGSQQTGIFCA
+LLNLLESAETEEVVDIFQVVKALRKARPGMVSTFEQYQFLYDVIASTYPAQNGQVKKNNH
+QEDKIEFDNEVDKVKQDANCVNPLGAPEKLPEAKEQAEGSEPTSGTEGPEHSVNGPASPA
+LNQGS

ext/marker_embeddings/fasta/P08575.fasta

@@ -0,0 +1,23 @@
+>sp|P08575|PTPRC_HUMAN Receptor-type tyrosine-protein phosphatase C OS=Homo sapiens OX=9606 GN=PTPRC PE=1 SV=3
+MTMYLWLKLLAFGFAFLDTEVFVTGQSPTPSPTGLTTAKMPSVPLSSDPLPTHTTAFSPA
+STFERENDFSETTTSLSPDNTSTQVSPDSLDNASAFNTTGVSSVQTPHLPTHADSQTPSA
+GTDTQTFSGSAANAKLNPTPGSNAISDVPGERSTASTFPTDPVSPLTTTLSLAHHSSAAL
+PARTSNTTITANTSDAYLNASETTTLSPSGSAVISTTTIATTPSKPTCDEKYANITVDYL
+YNKETKLFTAKLNVNENVECGNNTCTNNEVHNLTECKNASVSISHNSCTAPDKTLILDVP
+PGVEKFQLHDCTQVEKADTTICLKWKNIETFTCDTQNITYRFQCGNMIFDNKEIKLENLE
+PEHEYKCDSEILYNNHKFTNASKIIKTDFGSPGEPQIIFCRSEAAHQGVITWNPPQRSFH
+NFTLCYIKETEKDCLNLDKNLIKYDLQNLKPYTKYVLSLHAYIIAKVQRNGSAAMCHFTT
+KSAPPSQVWNMTVSMTSDNSMHVKCRPPRDRNGPHERYHLEVEAGNTLVRNESHKNCDFR
+VKDLQYSTDYTFKAYFHNGDYPGEPFILHHSTSYNSKALIAFLAFLIIVTSIALLVVLYK
+IYDLHKKRSCNLDEQQELVERDDEKQLMNVEPIHADILLETYKRKIADEGRLFLAEFQSI
+PRVFSKFPIKEARKPFNQNKNRYVDILPYDYNRVELSEINGDAGSNYINASYIDGFKEPR
+KYIAAQGPRDETVDDFWRMIWEQKATVIVMVTRCEEGNRNKCAEYWPSMEEGTRAFGDVV
+VKINQHKRCPDYIIQKLNIVNKKEKATGREVTHIQFTSWPDHGVPEDPHLLLKLRRRVNA
+FSNFFSGPIVVHCSAGVGRTGTYIGIDAMLEGLEAENKVDVYGYVVKLRRQRCLMVQVEA
+QYILIHQALVEYNQFGETEVNLSELHPYLHNMKKRDPPSEPSPLEAEFQRLPSYRSWRTQ
+HIGNQEENKSKNRNSNVIPYDYNRVPLKHELEMSKESEHDSDESSDDDSDSEEPSKYINA
+SFIMSYWKPEVMIAAQGPLKETIGDFWQMIFQRKVKVIVMLTELKHGDQEICAQYWGEGK
+QTYGDIEVDLKDTDKSSTYTLRVFELRHSKRKDSRTVYQYQYTNWSVEQLPAEPKELISM
+IQVVKQKLPQKNSSEGNKHHKSTPLLIHCRDGSQQTGIFCALLNLLESAETEEVVDIFQV
+VKALRKARPGMVSTFEQYQFLYDVIASTYPAQNGQVKKNNHQEDKIEFDNEVDKVKQDAN
+CVNPLGAPEKLPEAKEQAEGSEPTSGTEGPEHSVNGPASPALNQGS

ext/marker_embeddings/fasta/P11836.fasta

@@ -0,0 +1,6 @@
+>sp|P11836|CD20_HUMAN B-lymphocyte antigen CD20 OS=Homo sapiens OX=9606 GN=MS4A1 PE=1 SV=1
+MTTPRNSVNGTFPAEPMKGPIAMQSGPKPLFRRMSSLVGPTQSFFMRESKTLGAVQIMNG
+LFHIALGGLLMIPAGIYAPICVTVWYPLWGGIMYIISGSLLAATEKNSRKCLVKGKMIMN
+SLSLFAAISGMILSIMDILNIKISHFLKMESLNFIRAHTPYINIYNCEPANPSEKNSPST
+QYCYSIQSLFLGILSVMLIFAFFQELVIAGIVENEWKRTCSRPKSNIVLLSAEEKKEQTI
+EIKEEVVGLTETSSQPKNEEDIEIIPIQEEEEEETETNFPEPPQDQESSPIENDSSP

ext/marker_embeddings/fasta/P12830.fasta

@@ -0,0 +1,16 @@
+>sp|P12830|CADH1_HUMAN Cadherin-1 OS=Homo sapiens OX=9606 GN=CDH1 PE=1 SV=3
+MGPWSRSLSALLLLLQVSSWLCQEPEPCHPGFDAESYTFTVPRRHLERGRVLGRVNFEDC
+TGRQRTAYFSLDTRFKVGTDGVITVKRPLRFHNPQIHFLVYAWDSTYRKFSTKVTLNTVG
+HHHRPPPHQASVSGIQAELLTFPNSSPGLRRQKRDWVIPPISCPENEKGPFPKNLVQIKS
+NKDKEGKVFYSITGQGADTPPVGVFIIERETGWLKVTEPLDRERIATYTLFSHAVSSNGN
+AVEDPMEILITVTDQNDNKPEFTQEVFKGSVMEGALPGTSVMEVTATDADDDVNTYNAAI
+AYTILSQDPELPDKNMFTINRNTGVISVVTTGLDRESFPTYTLVVQAADLQGEGLSTTAT
+AVITVTDTNDNPPIFNPTTYKGQVPENEANVVITTLKVTDADAPNTPAWEAVYTILNDDG
+GQFVVTTNPVNNDGILKTAKGLDFEAKQQYILHVAVTNVVPFEVSLTTSTATVTVDVLDV
+NEAPIFVPPEKRVEVSEDFGVGQEITSYTAQEPDTFMEQKITYRIWRDTANWLEINPDTG
+AISTRAELDREDFEHVKNSTYTALIIATDNGSPVATGTGTLLLILSDVNDNAPIPEPRTI
+FFCERNPKPQVINIIDADLPPNTSPFTAELTHGASANWTIQYNDPTQESIILKPKMALEV
+GDYKINLKLMDNQNKDQVTTLEVSVCDCEGAAGVCRKAQPVEAGLQIPAILGILGGILAL
+LILILLLLLFLRRRAVVKEPLLPPEDDTRDNVYYYDEEGGGEEDQDFDLSQLHRGLDARP
+EVTRNDVAPTLMSVPRYLPRPANPDEIGNFIDENLKAADTDPTAPPYDSLLVFDYEGSGS
+EAASLSSLNSSESDKDQDYDYLNEWGNRFKKLADMYGGGEDD

ext/marker_embeddings/fasta/P16284.fasta

@@ -0,0 +1,14 @@
+>sp|P16284|PECA1_HUMAN Platelet endothelial cell adhesion molecule OS=Homo sapiens OX=9606 GN=PECAM1 PE=1 SV=2
+MQPRWAQGATMWLGVLLTLLLCSSLEGQENSFTINSVDMKSLPDWTVQNGKNLTLQCFAD
+VSTTSHVKPQHQMLFYKDDVLFYNISSMKSTESYFIPEVRIYDSGTYKCTVIVNNKEKTT
+AEYQVLVEGVPSPRVTLDKKEAIQGGIVRVNCSVPEEKAPIHFTIEKLELNEKMVKLKRE
+KNSRDQNFVILEFPVEEQDRVLSFRCQARIISGIHMQTSESTKSELVTVTESFSTPKFHI
+SPTGMIMEGAQLHIKCTIQVTHLAQEFPEIIIQKDKAIVAHNRHGNKAVYSVMAMVEHSG
+NYTCKVESSRISKVSSIVVNITELFSKPELESSFTHLDQGERLNLSCSIPGAPPANFTIQ
+KEDTIVSQTQDFTKIASKSDSGTYICTAGIDKVVKKSNTVQIVVCEMLSQPRISYDAQFE
+VIKGQTIEVRCESISGTLPISYQLLKTSKVLENSTKNSNDPAVFKDNPTEDVEYQCVADN
+CHSHAKMLSEVLRVKVIAPVDEVQISILSSKVVESGEDIVLQCAVNEGSGPITYKFYREK
+EGKPFYQMTSNATQAFWTKQKASKEQEGEYYCTAFNRANHASSVPRSKILTVRVILAPWK
+KGLIAVVIIGVIIALLIIAAKCYFLRKAKAKQMPVEMSRPAVPLLNSNNEKMSDPNMEAN
+SHYGHNDDVRNHAMKPINDNKEPLNSDVQYTEVQVSSAESHKDLGKKDTETVYSEVRKAV
+PDAVESRYSRTEGSLDGT

ext/marker_embeddings/fasta/P34810.fasta

@@ -0,0 +1,7 @@
+>sp|P34810|CD68_HUMAN Macrosialin OS=Homo sapiens OX=9606 GN=CD68 PE=1 SV=2
+MRLAVLFSGALLGLLAAQGTGNDCPHKKSATLLPSFTVTPTVTESTGTTSHRTTKSHKTT
+THRTTTTGTTSHGPTTATHNPTTTSHGNVTVHPTSNSTATSQGPSTATHSPATTSHGNAT
+VHPTSNSTATSPGFTSSAHPEPPPPSPSPSPTSKETIGDYTWTNGSQPCVHLQAQIQIRV
+MYTTQGGGEAWGISVLNPNKTKVQGSCEGAHPHLLLSFPYGHLSFGFMQDLQQKVVYLSY
+MAVEYNVSFPHAAQWTFSAQNASLRDLQAPLGQSFSCSNSSIILSPAVHLDLLSLRLQAA
+QLPHTGVFGQSFSCPSDRSILLPLIIGLILLGLLALVLIAFCIIRRRPSAYQAL

ext/marker_embeddings/fasta/P46013.fasta

@@ -0,0 +1,56 @@
+>sp|P46013|KI67_HUMAN Proliferation marker protein Ki-67 OS=Homo sapiens OX=9606 GN=MKI67 PE=1 SV=2
+MWPTRRLVTIKRSGVDGPHFPLSLSTCLFGRGIECDIRIQLPVVSKQHCKIEIHEQEAIL
+HNFSSTNPTQVNGSVIDEPVRLKHGDVITIIDRSFRYENESLQNGRKSTEFPRKIREQEP
+ARRVSRSSFSSDPDEKAQDSKAYSKITEGKVSGNPQVHIKNVKEDSTADDSKDSVAQGTT
+NVHSSEHAGRNGRNAADPISGDFKEISSVKLVSRYGELKSVPTTQCLDNSKKNESPFWKL
+YESVKKELDVKSQKENVLQYCRKSGLQTDYATEKESADGLQGETQLLVSRKSRPKSGGSG
+HAVAEPASPEQELDQNKGKGRDVESVQTPSKAVGASFPLYEPAKMKTPVQYSQQQNSPQK
+HKNKDLYTTGRRESVNLGKSEGFKAGDKTLTPRKLSTRNRTPAKVEDAADSATKPENLSS
+KTRGSIPTDVEVLPTETEIHNEPFLTLWLTQVERKIQKDSLSKPEKLGTTAGQMCSGLPG
+LSSVDINNFGDSINESEGIPLKRRRVSFGGHLRPELFDENLPPNTPLKRGEAPTKRKSLV
+MHTPPVLKKIIKEQPQPSGKQESGSEIHVEVKAQSLVISPPAPSPRKTPVASDQRRRSCK
+TAPASSSKSQTEVPKRGGRKSGNLPSKRVSISRSQHDILQMICSKRRSGASEANLIVAKS
+WADVVKLGAKQTQTKVIKHGPQRSMNKRQRRPATPKKPVGEVHSQFSTGHANSPCTIIIG
+KAHTEKVHVPARPYRVLNNFISNQKMDFKEDLSGIAEMFKTPVKEQPQLTSTCHIAISNS
+ENLLGKQFQGTDSGEEPLLPTSESFGGNVFFSAQNAAKQPSDKCSASPPLRRQCIRENGN
+VAKTPRNTYKMTSLETKTSDTETEPSKTVSTANRSGRSTEFRNIQKLPVESKSEETNTEI
+VECILKRGQKATLLQQRREGEMKEIERPFETYKENIELKENDEKMKAMKRSRTWGQKCAP
+MSDLTDLKSLPDTELMKDTARGQNLLQTQDHAKAPKSEKGKITKMPCQSLQPEPINTPTH
+TKQQLKASLGKVGVKEELLAVGKFTRTSGETTHTHREPAGDGKSIRTFKESPKQILDPAA
+RVTGMKKWPRTPKEEAQSLEDLAGFKELFQTPGPSEESMTDEKTTKIACKSPPPESVDTP
+TSTKQWPKRSLRKADVEEEFLALRKLTPSAGKAMLTPKPAGGDEKDIKAFMGTPVQKLDL
+AGTLPGSKRQLQTPKEKAQALEDLAGFKELFQTPGHTEELVAAGKTTKIPCDSPQSDPVD
+TPTSTKQRPKRSIRKADVEGELLACRNLMPSAGKAMHTPKPSVGEEKDIIIFVGTPVQKL
+DLTENLTGSKRRPQTPKEEAQALEDLTGFKELFQTPGHTEEAVAAGKTTKMPCESSPPES
+ADTPTSTRRQPKTPLEKRDVQKELSALKKLTQTSGETTHTDKVPGGEDKSINAFRETAKQ
+KLDPAASVTGSKRHPKTKEKAQPLEDLAGLKELFQTPVCTDKPTTHEKTTKIACRSQPDP
+VDTPTSSKPQSKRSLRKVDVEEEFFALRKRTPSAGKAMHTPKPAVSGEKNIYAFMGTPVQ
+KLDLTENLTGSKRRLQTPKEKAQALEDLAGFKELFQTRGHTEESMTNDKTAKVACKSSQP
+DPDKNPASSKRRLKTSLGKVGVKEELLAVGKLTQTSGETTHTHTEPTGDGKSMKAFMESP
+KQILDSAASLTGSKRQLRTPKGKSEVPEDLAGFIELFQTPSHTKESMTNEKTTKVSYRAS
+QPDLVDTPTSSKPQPKRSLRKADTEEEFLAFRKQTPSAGKAMHTPKPAVGEEKDINTFLG
+TPVQKLDQPGNLPGSNRRLQTRKEKAQALEELTGFRELFQTPCTDNPTTDEKTTKKILCK
+SPQSDPADTPTNTKQRPKRSLKKADVEEEFLAFRKLTPSAGKAMHTPKAAVGEEKDINTF
+VGTPVEKLDLLGNLPGSKRRPQTPKEKAKALEDLAGFKELFQTPGHTEESMTDDKITEVS
+CKSPQPDPVKTPTSSKQRLKISLGKVGVKEEVLPVGKLTQTSGKTTQTHRETAGDGKSIK
+AFKESAKQMLDPANYGTGMERWPRTPKEEAQSLEDLAGFKELFQTPDHTEESTTDDKTTK
+IACKSPPPESMDTPTSTRRRPKTPLGKRDIVEELSALKQLTQTTHTDKVPGDEDKGINVF
+RETAKQKLDPAASVTGSKRQPRTPKGKAQPLEDLAGLKELFQTPICTDKPTTHEKTTKIA
+CRSPQPDPVGTPTIFKPQSKRSLRKADVEEESLALRKRTPSVGKAMDTPKPAGGDEKDMK
+AFMGTPVQKLDLPGNLPGSKRWPQTPKEKAQALEDLAGFKELFQTPGTDKPTTDEKTTKI
+ACKSPQPDPVDTPASTKQRPKRNLRKADVEEEFLALRKRTPSAGKAMDTPKPAVSDEKNI
+NTFVETPVQKLDLLGNLPGSKRQPQTPKEKAEALEDLVGFKELFQTPGHTEESMTDDKIT
+EVSCKSPQPESFKTSRSSKQRLKIPLVKVDMKEEPLAVSKLTRTSGETTQTHTEPTGDSK
+SIKAFKESPKQILDPAASVTGSRRQLRTRKEKARALEDLVDFKELFSAPGHTEESMTIDK
+NTKIPCKSPPPELTDTATSTKRCPKTRPRKEVKEELSAVERLTQTSGQSTHTHKEPASGD
+EGIKVLKQRAKKKPNPVEEEPSRRRPRAPKEKAQPLEDLAGFTELSETSGHTQESLTAGK
+ATKIPCESPPLEVVDTTASTKRHLRTRVQKVQVKEEPSAVKFTQTSGETTDADKEPAGED
+KGIKALKESAKQTPAPAASVTGSRRRPRAPRESAQAIEDLAGFKDPAAGHTEESMTDDKT
+TKIPCKSSPELEDTATSSKRRPRTRAQKVEVKEELLAVGKLTQTSGETTHTDKEPVGEGK
+GTKAFKQPAKRKLDAEDVIGSRRQPRAPKEKAQPLEDLASFQELSQTPGHTEELANGAAD
+SFTSAPKQTPDSGKPLKISRRVLRAPKVEPVGDVVSTRDPVKSQSKSNTSLPPLPFKRGG
+GKDGSVTGTKRLRCMPAPEEIVEELPASKKQRVAPRARGKSSEPVVIMKRSLRTSAKRIE
+PAEELNSNDMKTNKEEHKLQDSVPENKGISLRSRRQNKTEAEQQITEVFVLAERIEINRN
+EKKPMKTSPEMDIQNPDDGARKPIPRDKVTENKRCLRSARQNESSQPKVAEESGGQKSAK
+VLMQNQKGKGEAGNSDSMCLRSRKTKSQPAASTLESKSVQRVTRSVKRCAENPKKAEDNV
+CVKKIRTRSHRDSEDI

ext/marker_embeddings/fasta/P62736.fasta

@@ -0,0 +1,8 @@
+>sp|P62736|ACTA_HUMAN Actin, aortic smooth muscle OS=Homo sapiens OX=9606 GN=ACTA2 PE=1 SV=1
+MCEEEDSTALVCDNGSGLCKAGFAGDDAPRAVFPSIVGRPRHQGVMVGMGQKDSYVGDEA
+QSKRGILTLKYPIEHGIITNWDDMEKIWHHSFYNELRVAPEEHPTLLTEAPLNPKANREK
+MTQIMFETFNVPAMYVAIQAVLSLYASGRTTGIVLDSGDGVTHNVPIYEGYALPHAIMRL
+DLAGRDLTDYLMKILTERGYSFVTTAEREIVRDIKEKLCYVALDFENEMATAASSSSLEK
+SYELPDGQVITIGNERFRCPETLFQPSFIGMESAGIHETTYNSIMKCDIDIRKDLYANNV
+LSGGTTMYPGIADRMQKEITALAPSTMKIKIIAPPERKYSVWIGGSILASLSTFQQMWIS
+KQEYDEAGPSIVHRKCF

ext/marker_embeddings/fasta/P68431.fasta

@@ -0,0 +1,4 @@
+>sp|P68431|H31_HUMAN Histone H3.1 OS=Homo sapiens OX=9606 GN=H3C1 PE=1 SV=2
+MARTKQTARKSTGGKAPRKQLATKAARKSAPATGGVKKPHRYRPGTVALREIRRYQKSTE
+LLIRKLPFQRLVREIAQDFKTDLRFQSSAVMALQEACEAYLVGLFEDTNLCAIHAKRVTI
+MPKDIQLARRIRGERA

ext/marker_embeddings/fasta/Q15116.fasta

@@ -0,0 +1,6 @@
+>sp|Q15116|PDCD1_HUMAN Programmed cell death protein 1 OS=Homo sapiens OX=9606 GN=PDCD1 PE=1 SV=3
+MQIPQAPWPVVWAVLQLGWRPGWFLDSPDRPWNPPTFSPALLVVTEGDNATFTCSFSNTS
+ESFVLNWYRMSPSNQTDKLAAFPEDRSQPGQDCRFRVTQLPNGRDFHMSVVRARRNDSGT
+YLCGAISLAPKAQIKESLRAELRVTERRAEVPTAHPSPSPRPAGQFQTLVVGVVGGLLGS
+LVLLVWVLAVICSRAARGTIGARRTGQPLKEDPSAVPVFSVDYGELDFQWREKTPEPPVP
+CVPEQTEYATIVFPSGMGTSSPARRGSADGPRSAQPLRPEDGHCSWPL

ext/marker_embeddings/fasta/Q86VB7.fasta

@@ -0,0 +1,21 @@
+>sp|Q86VB7|C163A_HUMAN Scavenger receptor cysteine-rich type 1 protein M130 OS=Homo sapiens OX=9606 GN=CD163 PE=1 SV=2
+MSKLRMVLLEDSGSADFRRHFVNLSPFTITVVLLLSACFVTSSLGGTDKELRLVDGENKC
+SGRVEVKVQEEWGTVCNNGWSMEAVSVICNQLGCPTAIKAPGWANSSAGSGRIWMDHVSC
+RGNESALWDCKHDGWGKHSNCTHQQDAGVTCSDGSNLEMRLTRGGNMCSGRIEIKFQGRW
+GTVCDDNFNIDHASVICRQLECGSAVSFSGSSNFGEGSGPIWFDDLICNGNESALWNCKH
+QGWGKHNCDHAEDAGVICSKGADLSLRLVDGVTECSGRLEVRFQGEWGTICDDGWDSYDA
+AVACKQLGCPTAVTAIGRVNASKGFGHIWLDSVSCQGHEPAIWQCKHHEWGKHYCNHNED
+AGVTCSDGSDLELRLRGGGSRCAGTVEVEIQRLLGKVCDRGWGLKEADVVCRQLGCGSAL
+KTSYQVYSKIQATNTWLFLSSCNGNETSLWDCKNWQWGGLTCDHYEEAKITCSAHREPRL
+VGGDIPCSGRVEVKHGDTWGSICDSDFSLEAASVLCRELQCGTVVSILGGAHFGEGNGQI
+WAEEFQCEGHESHLSLCPVAPRPEGTCSHSRDVGVVCSRYTEIRLVNGKTPCEGRVELKT
+LGAWGSLCNSHWDIEDAHVLCQQLKCGVALSTPGGARFGKGNGQIWRHMFHCTGTEQHMG
+DCPVTALGASLCPSEQVASVICSGNQSQTLSSCNSSSLGPTRPTIPEESAVACIESGQLR
+LVNGGGRCAGRVEIYHEGSWGTICDDSWDLSDAHVVCRQLGCGEAINATGSAHFGEGTGP
+IWLDEMKCNGKESRIWQCHSHGWGQQNCRHKEDAGVICSEFMSLRLTSEASREACAGRLE
+VFYNGAWGTVGKSSMSETTVGVVCRQLGCADKGKINPASLDKAMSIPMWVDNVQCPKGPD
+TLWQCPSSPWEKRLASPSEETWITCDNKIRLQEGPTSCSGRVEIWHGGSWGTVCDDSWDL
+DDAQVVCQQLGCGPALKAFKEAEFGQGTGPIWLNEVKCKGNESSLWDCPARRWGHSECGH
+KEDAAVNCTDISVQKTPQKATTGRSSRQSSFIAVGILGVVLLAIFVALFFLTKKRRQRQR
+LAVSSRGENLVHQIQYREMNSCLNADDLDLMNSSENSHESADFSAAELISVSKFLPISGM
+EKEAILSHTEKENGNL

ext/marker_embeddings/fasta/Q9BZS1.fasta

@@ -0,0 +1,9 @@
+>sp|Q9BZS1|FOXP3_HUMAN Forkhead box protein P3 OS=Homo sapiens OX=9606 GN=FOXP3 PE=1 SV=1
+MPNPRPGKPSAPSLALGPSPGASPSWRAAPKASDLLGARGPGGTFQGRDLRGGAHASSSS
+LNPMPPSQLQLPTLPLVMVAPSGARLGPLPHLQALLQDRPHFMHQLSTVDAHARTPVLQV
+HPLESPAMISLTPPTTATGVFSLKARPGLPPGINVASLEWVSREPALLCTFPNPSAPRKD
+STLSAVPQSSYPLLANGVCKWPGCEKVFEEPEDFLKHCQADHLLDEKGRAQCLLQREMVQ
+SLEQQLVLEKEKLSAMQAHLAGKMALTKASSVASSDKGSCCIVAAGSQGPVVPAWSGPRE
+APDSLFAVRRHLWGSHGNSTFPEFLHNMDYFKFHNMRPPFTYATLIRWAILEAPEKQRTL
+NEIYHWFTRMFAFFRNHPATWKNAIRHNLSLHKCFVRVESEKGAVWTVDELEFRKKRSQR
+PSRCSNPTPGP

ext/marker_embeddings/fasta/Q9NZQ7.fasta

@@ -0,0 +1,6 @@
+>sp|Q9NZQ7|PD1L1_HUMAN Programmed cell death 1 ligand 1 OS=Homo sapiens OX=9606 GN=CD274 PE=1 SV=1
+MRIFAVFIFMTYWHLLNAFTVTVPKDLYVVEYGSNMTIECKFPVEKQLDLAALIVYWEME
+DKNIIQFVHGEEDLKVQHSSYRQRARLLKDQLSLGNAALQITDVKLQDAGVYRCMISYGG
+ADYKRITVKVNAPYNKINQRILVVDPVTSEHELTCQAEGYPKAEVIWTSSDHQVLSGKTT
+TTNSKREEKLFNVTSTLRINTTTNEIFYCTFRRLDPEENHTAELVIPELPLAHPPNERTH
+LVILGAILLCLGVALTFIFRLRKGRMMDVKKCGIQDTNSKKQSDTHLEET

models/ej_ad_mv/meta.json

@@ -0,0 +1,2074 @@
+{
+ "config": "EJ-ad+MV",
+ "stage2_rule": "ens-es",
+ "n_adapters": 3,
+ "mode": "release",
+ "created": "2026-10-28 07:05",
+ "dims": {
+  "mif": 512,
+  "rna:hvg": 2000,
+  "rna:tahoex1": 512,
+  "rna:se600m": 2048,
+  "rna:aidocell": 640,
+  "text:keep": 768,
+  "text:biomedclip": 512,
+  "text:qwen3-0.6b": 1024
+ },
+ "adapter": "cat",
+ "raw_encoders": [
+  "rna:hvg",
+  "text:biomedclip"
+ ],
+ "hvg_genes": [
+  "A2M",
+  "AAMP",
+  "ABHD2",
+  "ABLIM1",
+  "ABR",
+  "ACAA1",
+  "ACAA2",
+  "ACADVL",
+  "ACAT1",
+  "ACLY",
+  "ACO2",
+  "ACOT7",
+  "ACSL1",
+  "ACSL3",
+  "ACSS1",
+  "ACTA2",
+  "ACTB",
+  "ACTC1",
+  "ACTG2",
+  "ACTN1",
+  "ACTN2",
+  "ACTN4",
+  "ACTR3",
+  "ADAM15",
+  "ADAM9",
+  "ADAMTS1",
+  "ADAR",
+  "ADD1",
+  "ADD3",
+  "ADGRG1",
+  "ADH5",
+  "ADI1",
+  "ADIRF",
+  "ADNP",
+  "ADRM1",
+  "AEBP1",
+  "AFDN",
+  "AFF1",
+  "AGAP3",
+  "AGPAT2",
+  "AGR2",
+  "AGRN",
+  "AGT",
+  "AHCYL1",
+  "AHNAK",
+  "AHSA1",
+  "AHSG",
+  "AIDA",
+  "AK1",
+  "AKAP1",
+  "AKAP12",
+  "AKAP13",
+  "AKAP9",
+  "AKR1A1",
+  "AKT1",
+  "AKT2",
+  "ALB",
+  "ALDH1A1",
+  "ALDH1L1",
+  "ALDH2",
+  "ALDH3A2",
+  "ALDOB",
+  "ALDOC",
+  "ALKBH5",
+  "ALKBH7",
+  "ANAPC11",
+  "ANAPC16",
+  "ANAPC5",
+  "ANG",
+  "ANGPTL4",
+  "ANK2",
+  "ANKH",
+  "ANKRD10",
+  "ANKRD11",
+  "ANKRD12",
+  "ANP32A",
+  "ANP32B",
+  "ANP32E",
+  "ANPEP",
+  "ANXA1",
+  "ANXA11",
+  "ANXA2",
+  "ANXA4",
+  "ANXA5",
+  "ANXA6",
+  "ANXA7",
+  "AP2A2",
+  "AP2M1",
+  "AP2S1",
+  "AP3D1",
+  "APBB1",
+  "APEX1",
+  "APH1A",
+  "APLP2",
+  "APMAP",
+  "APOA2",
+  "APOB",
+  "APOC1",
+  "APOC2",
+  "APOD",
+  "APOE",
+  "APOL1",
+  "APP",
+  "APRT",
+  "AQP1",
+  "AQP3",
+  "ARAP1",
+  "ARCN1",
+  "ARF1",
+  "ARF3",
+  "ARF4",
+  "ARGLU1",
+  "ARHGDIA",
+  "ARHGDIB",
+  "ARHGEF12",
+  "ARL2",
+  "ARL6IP4",
+  "ARL6IP5",
+  "ARPC1A",
+  "ARPC1B",
+  "ARPC2",
+  "ARPC3",
+  "ARPC4",
+  "ARPC5",
+  "ARPP19",
+  "ARRDC3",
+  "ASAH1",
+  "ASPH",
+  "ASS1",
+  "ATF4",
+  "ATN1",
+  "ATOX1",
+  "ATP1A1",
+  "ATP1A2",
+  "ATP1B1",
+  "ATP2A2",
+  "ATP2B4",
+  "ATP2C1",
+  "ATP5F1A",
+  "ATP5F1B",
+  "ATP5F1D",
+  "ATP5F1E",
+  "ATP5IF1",
+  "ATP5MC2",
+  "ATP5MC3",
+  "ATP5ME",
+  "ATP5MF",
+  "ATP5MG",
+  "ATP5MPL",
+  "ATP5PB",
+  "ATP5PD",
+  "ATP5PF",
+  "ATP6AP1",
+  "ATP6AP2",
+  "ATP6V0A1",
+  "ATP6V0B",
+  "ATP6V0D1",
+  "ATP6V0E1",
+  "ATP6V1A",
+  "ATP6V1B2",
+  "ATP6V1E1",
+  "ATP6V1F",
+  "ATP6V1G1",
+  "ATP9A",
+  "ATRAID",
+  "ATRX",
+  "ATXN10",
+  "ATXN7L3B",
+  "AUP1",
+  "AURKAIP1",
+  "AXIN2",
+  "AZGP1",
+  "AZIN1",
+  "B2M",
+  "B4GALT1",
+  "BACE2",
+  "BAD",
+  "BAG1",
+  "BAG6",
+  "BANF1",
+  "BCAM",
+  "BCAP31",
+  "BCL2L1",
+  "BCL6",
+  "BCL7C",
+  "BEX3",
+  "BEX4",
+  "BGN",
+  "BHLHE40",
+  "BIN1",
+  "BLCAP",
+  "BLOC1S1",
+  "BLVRB",
+  "BNIP3L",
+  "BPTF",
+  "BRD2",
+  "BRD4",
+  "BRI3",
+  "BRK1",
+  "BSG",
+  "BST2",
+  "BTBD2",
+  "BTF3",
+  "BTG2",
+  "BZW1",
+  "C11orf58",
+  "C11orf96",
+  "C12orf57",
+  "C19orf33",
+  "C19orf48",
+  "C19orf53",
+  "C1QA",
+  "C1QB",
+  "C1QC",
+  "C1QTNF1",
+  "C1R",
+  "C1S",
+  "C1orf122",
+  "C1orf198",
+  "C1orf43",
+  "C1orf61",
+  "C3",
+  "C4orf3",
+  "C4orf48",
+  "C6orf62",
+  "C7",
+  "C7orf50",
+  "CA12",
+  "CALCOCO2",
+  "CALD1",
+  "CALM3",
+  "CALR",
+  "CALU",
+  "CAMK2N1",
+  "CAMLG",
+  "CAMTA1",
+  "CANT1",
+  "CANX",
+  "CAP1",
+  "CAPG",
+  "CAPN1",
+  "CAPN2",
+  "CAPNS1",
+  "CAPRIN1",
+  "CAPS",
+  "CAPZA2",
+  "CAPZB",
+  "CASC3",
+  "CAST",
+  "CAT",
+  "CAV1",
+  "CAV2",
+  "CAVIN1",
+  "CAVIN3",
+  "CBR1",
+  "CBX3",
+  "CBX5",
+  "CBX6",
+  "CCDC12",
+  "CCDC124",
+  "CCDC47",
+  "CCDC6",
+  "CCDC80",
+  "CCDC85B",
+  "CCND1",
+  "CCND2",
+  "CCNI",
+  "CCNL1",
+  "CCNL2",
+  "CCT2",
+  "CCT3",
+  "CCT4",
+  "CCT8",
+  "CD14",
+  "CD151",
+  "CD163",
+  "CD164",
+  "CD24",
+  "CD36",
+  "CD44",
+  "CD46",
+  "CD47",
+  "CD55",
+  "CD63",
+  "CD68",
+  "CD74",
+  "CD81",
+  "CD9",
+  "CD99",
+  "CDC123",
+  "CDC34",
+  "CDC42BPB",
+  "CDC42EP1",
+  "CDC42EP5",
+  "CDC42SE1",
+  "CDC42SE2",
+  "CDH1",
+  "CDIPT",
+  "CDK4",
+  "CDK6",
+  "CDKN1A",
+  "CDV3",
+  "CEACAM5",
+  "CEBPD",
+  "CELF1",
+  "CENPX",
+  "CERCAM",
+  "CERS2",
+  "CES2",
+  "CFB",
+  "CFD",
+  "CFH",
+  "CFL2",
+  "CFLAR",
+  "CHCHD1",
+  "CHCHD10",
+  "CHCHD2",
+  "CHD4",
+  "CHGA",
+  "CHI3L1",
+  "CHID1",
+  "CHMP1B",
+  "CHMP2A",
+  "CHMP3",
+  "CHMP4B",
+  "CHMP5",
+  "CHN1",
+  "CHP1",
+  "CHPF",
+  "CHTOP",
+  "CHURC1",
+  "CIB1",
+  "CIRBP",
+  "CISD3",
+  "CKAP4",
+  "CKB",
+  "CKMT2",
+  "CLDN3",
+  "CLDN4",
+  "CLDN5",
+  "CLDN7",
+  "CLIC1",
+  "CLIC4",
+  "CLIP1",
+  "CLK1",
+  "CLPTM1",
+  "CLPTM1L",
+  "CLSTN1",
+  "CLTA",
+  "CLTB",
+  "CLTC",
+  "CLU",
+  "CLUH",
+  "CMBL",
+  "CMPK1",
+  "CMYA5",
+  "CNBP",
+  "CNDP2",
+  "CNN1",
+  "CNN2",
+  "CNN3",
+  "CNP",
+  "CNPY2",
+  "COA3",
+  "COA4",
+  "COL16A1",
+  "COL18A1",
+  "COL1A1",
+  "COL1A2",
+  "COL3A1",
+  "COL4A1",
+  "COL4A2",
+  "COL5A1",
+  "COL5A2",
+  "COL6A1",
+  "COL6A2",
+  "COL6A3",
+  "COLGALT1",
+  "COMMD6",
+  "COMT",
+  "COPA",
+  "COPB2",
+  "COPE",
+  "COPG1",
+  "COPS6",
+  "COPS9",
+  "COPZ1",
+  "COQ8A",
+  "CORO1C",
+  "COTL1",
+  "COX14",
+  "COX17",
+  "COX4I1",
+  "COX5B",
+  "COX6A1",
+  "COX6B1",
+  "COX6C",
+  "COX7A1",
+  "COX7A2",
+  "COX7A2L",
+  "COX7B",
+  "COX7C",
+  "COX8A",
+  "CP",
+  "CPE",
+  "CPNE1",
+  "CRABP2",
+  "CREB3L1",
+  "CREBZF",
+  "CREG1",
+  "CRELD2",
+  "CRIM1",
+  "CRIP1",
+  "CRIP2",
+  "CRISPLD2",
+  "CRP",
+  "CRTAP",
+  "CRYAB",
+  "CS",
+  "CSDE1",
+  "CSNK1D",
+  "CSNK1G2",
+  "CSNK2B",
+  "CSRP3",
+  "CST3",
+  "CSTA",
+  "CSTB",
+  "CTDNEP1",
+  "CTDSP1",
+  "CTDSP2",
+  "CTNNA1",
+  "CTNNB1",
+  "CTNNBIP1",
+  "CTNND1",
+  "CTSA",
+  "CTSB",
+  "CTSC",
+  "CTSD",
+  "CTSF",
+  "CTSH",
+  "CTSL",
+  "CTSS",
+  "CTSZ",
+  "CTTN",
+  "CTXN1",
+  "CUTA",
+  "CUX1",
+  "CXCL12",
+  "CXCL14",
+  "CXCR4",
+  "CYB5A",
+  "CYB5B",
+  "CYB5R3",
+  "CYBA",
+  "CYBRD1",
+  "CYC1",
+  "CYCS",
+  "CYHR1",
+  "CYP1B1",
+  "CYP2C8",
+  "CYP2E1",
+  "CYSTM1",
+  "CYTH2",
+  "DAB2",
+  "DAD1",
+  "DAG1",
+  "DAP",
+  "DAZAP1",
+  "DAZAP2",
+  "DBI",
+  "DBNL",
+  "DCAF7",
+  "DCAF8",
+  "DCN",
+  "DCTN1",
+  "DCTN2",
+  "DCTN3",
+  "DCXR",
+  "DDAH1",
+  "DDAH2",
+  "DDB1",
+  "DDIT4",
+  "DDR1",
+  "DDRGK1",
+  "DDT",
+  "DDX1",
+  "DDX17",
+  "DDX21",
+  "DDX23",
+  "DDX24",
+  "DDX39B",
+  "DDX3X",
+  "DDX5",
+  "DDX6",
+  "DECR1",
+  "DEFB1",
+  "DEGS1",
+  "DEK",
+  "DEPP1",
+  "DES",
+  "DHCR24",
+  "DHRS3",
+  "DHRS7",
+  "DHX15",
+  "DHX30",
+  "DIDO1",
+  "DKK3",
+  "DLGAP4",
+  "DMKN",
+  "DMPK",
+  "DNAJA1",
+  "DNAJB1",
+  "DNAJB2",
+  "DNAJB6",
+  "DNAJC15",
+  "DNAJC7",
+  "DNM1",
+  "DNM2",
+  "DNPEP",
+  "DNPH1",
+  "DPEP1",
+  "DPM3",
+  "DPP7",
+  "DPYSL2",
+  "DPYSL3",
+  "DRAP1",
+  "DSP",
+  "DST",
+  "DSTN",
+  "DUS1L",
+  "DUSP1",
+  "DUSP23",
+  "DUSP3",
+  "DUT",
+  "DYNC1H1",
+  "DYNC1I2",
+  "DYNC1LI2",
+  "DYNLL1",
+  "DYNLL2",
+  "DYNLT1",
+  "EBPL",
+  "ECE1",
+  "ECH1",
+  "ECHDC2",
+  "ECHS1",
+  "ECI1",
+  "EDF1",
+  "EEF1A2",
+  "EEF1B2",
+  "EEF1G",
+  "EEF2",
+  "EFEMP1",
+  "EFHD1",
+  "EFHD2",
+  "EFNA1",
+  "EGFL7",
+  "EGR1",
+  "EHBP1L1",
+  "EHD2",
+  "EI24",
+  "EID1",
+  "EIF1",
+  "EIF1AX",
+  "EIF1B",
+  "EIF2S2",
+  "EIF2S3",
+  "EIF3A",
+  "EIF3B",
+  "EIF3D",
+  "EIF3E",
+  "EIF3G",
+  "EIF3H",
+  "EIF3I",
+  "EIF3L",
+  "EIF3M",
+  "EIF4A1",
+  "EIF4A2",
+  "EIF4B",
+  "EIF4EBP2",
+  "EIF4G1",
+  "EIF4G2",
+  "EIF4H",
+  "EIF5",
+  "EIF5B",
+  "EIF6",
+  "ELAVL1",
+  "ELF3",
+  "ELL2",
+  "ELN",
+  "ELOVL5",
+  "EMC10",
+  "EMC4",
+  "EMILIN1",
+  "EMP1",
+  "EMP2",
+  "EMP3",
+  "ENAH",
+  "ENC1",
+  "ENG",
+  "ENO1",
+  "ENO2",
+  "ENTPD6",
+  "ENY2",
+  "EPAS1",
+  "EPCAM",
+  "EPHX1",
+  "EPN1",
+  "EPS8L2",
+  "ERBB2",
+  "ERBB3",
+  "ERGIC1",
+  "ERGIC3",
+  "ERH",
+  "ERO1A",
+  "ERP29",
+  "ERRFI1",
+  "ESD",
+  "ESYT2",
+  "ETFA",
+  "ETFB",
+  "ETHE1",
+  "ETS2",
+  "EVL",
+  "EZR",
+  "F2",
+  "F3",
+  "FABP1",
+  "FABP4",
+  "FABP5",
+  "FAM107A",
+  "FAM120A",
+  "FAM162A",
+  "FAM3C",
+  "FAM3D",
+  "FAM50A",
+  "FARP1",
+  "FASN",
+  "FAT1",
+  "FBLN1",
+  "FBLN2",
+  "FBN1",
+  "FBP1",
+  "FBXL5",
+  "FBXW5",
+  "FCER1G",
+  "FCGBP",
+  "FCGRT",
+  "FDFT1",
+  "FDPS",
+  "FGA",
+  "FGFRL1",
+  "FGG",
+  "FHL2",
+  "FIS1",
+  "FKBP10",
+  "FKBP3",
+  "FKBP5",
+  "FKBP8",
+  "FKBP9",
+  "FLII",
+  "FLNA",
+  "FLNB",
+  "FLNC",
+  "FLOT1",
+  "FLOT2",
+  "FMOD",
+  "FN1",
+  "FNDC3B",
+  "FOS",
+  "FOSB",
+  "FOXA1",
+  "FOXN3",
+  "FOXO3",
+  "FOXP1",
+  "FSTL1",
+  "FTH1",
+  "FTL",
+  "FUNDC2",
+  "FURIN",
+  "FUS",
+  "FXR1",
+  "FXYD1",
+  "FXYD2",
+  "FXYD3",
+  "FXYD5",
+  "FXYD6",
+  "G0S2",
+  "G3BP2",
+  "GAA",
+  "GABARAP",
+  "GABARAPL2",
+  "GADD45B",
+  "GADD45G",
+  "GADD45GIP1",
+  "GALNT2",
+  "GAMT",
+  "GANAB",
+  "GAS6",
+  "GATAD2A",
+  "GATD1",
+  "GATM",
+  "GDF15",
+  "GDI1",
+  "GDI2",
+  "GGT5",
+  "GHITM",
+  "GID8",
+  "GIPC1",
+  "GJA1",
+  "GLG1",
+  "GLO1",
+  "GLRX5",
+  "GLS",
+  "GLUD1",
+  "GLUL",
+  "GM2A",
+  "GNA11",
+  "GNAI2",
+  "GNAQ",
+  "GNB1",
+  "GNG11",
+  "GNG5",
+  "GNPTG",
+  "GNS",
+  "GOLGB1",
+  "GOLM1",
+  "GOLPH3",
+  "GOT1",
+  "GOT2",
+  "GPAA1",
+  "GPC1",
+  "GPI",
+  "GPM6A",
+  "GPNMB",
+  "GPRC5A",
+  "GPRC5B",
+  "GPS1",
+  "GPX2",
+  "GPX3",
+  "GPX4",
+  "GRHPR",
+  "GRINA",
+  "GRK2",
+  "GRN",
+  "GRSF1",
+  "GSN",
+  "GSPT1",
+  "GSTK1",
+  "GSTM3",
+  "GSTO1",
+  "GSTP1",
+  "GTF2I",
+  "GTF3A",
+  "GTF3C1",
+  "GTF3C6",
+  "GUK1",
+  "GYPC",
+  "HADHA",
+  "HADHB",
+  "HAGH",
+  "HAMP",
+  "HBA2",
+  "HCFC1R1",
+  "HDAC1",
+  "HDGF",
+  "HDLBP",
+  "HEBP2",
+  "HERPUD1",
+  "HES4",
+  "HEXA",
+  "HEXB",
+  "HGS",
+  "HIF1A",
+  "HINT1",
+  "HIPK2",
+  "HIPK3",
+  "HK1",
+  "HM13",
+  "HMG20B",
+  "HMGA1",
+  "HMGCS2",
+  "HMGN3",
+  "HMOX1",
+  "HNRNPA0",
+  "HNRNPA2B1",
+  "HNRNPA3",
+  "HNRNPC",
+  "HNRNPD",
+  "HNRNPDL",
+  "HNRNPF",
+  "HNRNPH3",
+  "HNRNPK",
+  "HNRNPR",
+  "HNRNPU",
+  "HNRNPUL1",
+  "HNRNPUL2",
+  "HOPX",
+  "HP1BP3",
+  "HPCAL1",
+  "HPD",
+  "HPX",
+  "HRC",
+  "HSBP1",
+  "HSD11B2",
+  "HSD17B10",
+  "HSD17B4",
+  "HSF1",
+  "HSP90AA1",
+  "HSP90AB1",
+  "HSP90B1",
+  "HSPA1A",
+  "HSPA1B",
+  "HSPA5",
+  "HSPA8",
+  "HSPA9",
+  "HSPB1",
+  "HSPB6",
+  "HSPB7",
+  "HSPB8",
+  "HSPD1",
+  "HSPE1",
+  "HSPG2",
+  "HSPH1",
+  "HTRA1",
+  "HUWE1",
+  "ICAM1",
+  "ID1",
+  "ID2",
+  "ID3",
+  "ID4",
+  "IDH2",
+  "IDI1",
+  "IDS",
+  "IER2",
+  "IER3",
+  "IFI16",
+  "IFI27",
+  "IFI27L2",
+  "IFI30",
+  "IFI6",
+  "IFITM2",
+  "IFITM3",
+  "IFNAR1",
+  "IFNGR2",
+  "IGFBP2",
+  "IGFBP3",
+  "IGFBP4",
+  "IGFBP5",
+  "IGFBP6",
+  "IGFBP7",
+  "IGHG1",
+  "IGHG3",
+  "IGHM",
+  "IGKC",
+  "IGLC1",
+  "IL1R1",
+  "IL32",
+  "ILF2",
+  "ILF3",
+  "ILK",
+  "IMPDH2",
+  "INF2",
+  "INSIG1",
+  "INSR",
+  "INTS1",
+  "INTS11",
+  "IP6K2",
+  "IPO5",
+  "IQGAP1",
+  "IRAK1",
+  "IRF1",
+  "ISCU",
+  "ISG15",
+  "ISLR",
+  "ITFG1",
+  "ITGA3",
+  "ITGA5",
+  "ITGA6",
+  "ITGAV",
+  "ITGB1",
+  "ITGB4",
+  "ITGB5",
+  "ITM2B",
+  "ITM2C",
+  "ITPK1",
+  "IVNS1ABP",
+  "JCHAIN",
+  "JPT1",
+  "JTB",
+  "JUN",
+  "JUNB",
+  "JUP",
+  "KANK2",
+  "KCTD12",
+  "KDELR1",
+  "KDELR2",
+  "KHDRBS1",
+  "KHSRP",
+  "KIAA1522",
+  "KIF1B",
+  "KIF1C",
+  "KIF5B",
+  "KLC1",
+  "KLF5",
+  "KLF6",
+  "KLF9",
+  "KLHDC3",
+  "KLK2",
+  "KLK4",
+  "KPNA4",
+  "KPNB1",
+  "KRT1",
+  "KRT10",
+  "KRT14",
+  "KRT16",
+  "KRT6B",
+  "KRT7",
+  "KRT8",
+  "KRTCAP2",
+  "KTN1",
+  "KXD1",
+  "LAMA4",
+  "LAMA5",
+  "LAMB1",
+  "LAMB2",
+  "LAMC1",
+  "LAMP1",
+  "LAMP2",
+  "LAMTOR1",
+  "LAMTOR4",
+  "LAP3",
+  "LAPTM4A",
+  "LAPTM4B",
+  "LAPTM5",
+  "LARP1",
+  "LASP1",
+  "LBH",
+  "LCN2",
+  "LDB3",
+  "LENG8",
+  "LGALS1",
+  "LGALS3",
+  "LGALS3BP",
+  "LGALS4",
+  "LGMN",
+  "LIMS2",
+  "LITAF",
+  "LMAN1",
+  "LMAN2",
+  "LMNA",
+  "LMO4",
+  "LMO7",
+  "LPCAT1",
+  "LPP",
+  "LRP1",
+  "LRP10",
+  "LRPAP1",
+  "LRRC59",
+  "LRRFIP1",
+  "LSM14A",
+  "LSM3",
+  "LSM4",
+  "LSM7",
+  "LSP1",
+  "LSR",
+  "LTBP3",
+  "LTBP4",
+  "LTBR",
+  "LTF",
+  "LUC7L",
+  "LUC7L2",
+  "LUC7L3",
+  "LUM",
+  "LY6E",
+  "LYZ",
+  "MACF1",
+  "MAF",
+  "MAF1",
+  "MAGED1",
+  "MAGED2",
+  "MAL2",
+  "MANF",
+  "MAOA",
+  "MAP1B",
+  "MAP1LC3A",
+  "MAP2K2",
+  "MAP2K3",
+  "MAP3K20",
+  "MAP4",
+  "MAP7",
+  "MAP7D1",
+  "MAPK1",
+  "MAPK1IP1L",
+  "MAPK3",
+  "MAPKAPK2",
+  "MAPRE1",
+  "MARCKS",
+  "MARCKSL1",
+  "MAT2A",
+  "MAZ",
+  "MB",
+  "MBNL1",
+  "MBNL2",
+  "MBOAT7",
+  "MBP",
+  "MCAM",
+  "MCL1",
+  "MCM7",
+  "MCRIP1",
+  "MDH2",
+  "MDK",
+  "MDM4",
+  "MEA1",
+  "MEAF6",
+  "METAP2",
+  "METRN",
+  "METRNL",
+  "METTL26",
+  "METTL9",
+  "MFAP4",
+  "MFGE8",
+  "MFN2",
+  "MFSD10",
+  "MGAT1",
+  "MGAT4B",
+  "MGLL",
+  "MGST1",
+  "MGST3",
+  "MICAL2",
+  "MIDN",
+  "MIEN1",
+  "MIF",
+  "MKNK2",
+  "MLEC",
+  "MLF2",
+  "MLLT1",
+  "MLLT6",
+  "MLPH",
+  "MMP14",
+  "MMP2",
+  "MMP24OS",
+  "MMP7",
+  "MOB1A",
+  "MORF4L1",
+  "MORF4L2",
+  "MPC1",
+  "MPC2",
+  "MPRIP",
+  "MPST",
+  "MRC2",
+  "MRFAP1L1",
+  "MSI2",
+  "MSN",
+  "MSRB2",
+  "MT1E",
+  "MT1F",
+  "MT1G",
+  "MT1X",
+  "MT2A",
+  "MT3",
+  "MTCH1",
+  "MTDH",
+  "MTPN",
+  "MTURN",
+  "MUC1",
+  "MUC2",
+  "MUC5B",
+  "MVP",
+  "MXD4",
+  "MXRA7",
+  "MXRA8",
+  "MYADM",
+  "MYBPC3",
+  "MYC",
+  "MYDGF",
+  "MYH14",
+  "MYH7",
+  "MYH9",
+  "MYL12A",
+  "MYL12B",
+  "MYL3",
+  "MYL9",
+  "MYLK",
+  "MYO15B",
+  "MYO1C",
+  "MYO6",
+  "MYOZ2",
+  "N4BP2L2",
+  "NAA38",
+  "NAMPT",
+  "NAP1L4",
+  "NAPA",
+  "NAXE",
+  "NBL1",
+  "NBR1",
+  "NCAM1",
+  "NCDN",
+  "NCKAP1",
+  "NCL",
+  "NCOA4",
+  "NCOA7",
+  "NCOR1",
+  "NCOR2",
+  "NDFIP1",
+  "NDRG1",
+  "NDRG2",
+  "NDRG4",
+  "NDUFA1",
+  "NDUFA10",
+  "NDUFA11",
+  "NDUFA12",
+  "NDUFA13",
+  "NDUFA2",
+  "NDUFA3",
+  "NDUFA4",
+  "NDUFA4L2",
+  "NDUFA6",
+  "NDUFA7",
+  "NDUFA8",
+  "NDUFAB1",
+  "NDUFAF3",
+  "NDUFAF8",
+  "NDUFB10",
+  "NDUFB11",
+  "NDUFB2",
+  "NDUFB5",
+  "NDUFB6",
+  "NDUFB7",
+  "NDUFB9",
+  "NDUFC1",
+  "NDUFC2",
+  "NDUFS1",
+  "NDUFS2",
+  "NDUFS3",
+  "NDUFS4",
+  "NDUFS5",
+  "NDUFS6",
+  "NDUFS7",
+  "NDUFS8",
+  "NDUFV1",
+  "NDUFV2",
+  "NDUFV3",
+  "NEBL",
+  "NECTIN2",
+  "NEDD8",
+  "NENF",
+  "NES",
+  "NET1",
+  "NEXN",
+  "NFE2L1",
+  "NFE2L2",
+  "NFIA",
+  "NFIB",
+  "NFIC",
+  "NFIX",
+  "NFKBIA",
+  "NHP2",
+  "NID1",
+  "NINJ1",
+  "NIPSNAP2",
+  "NISCH",
+  "NKTR",
+  "NME1",
+  "NME2",
+  "NME3",
+  "NME4",
+  "NNMT",
+  "NONO",
+  "NOP10",
+  "NOP53",
+  "NOTCH3",
+  "NPC2",
+  "NPDC1",
+  "NPTN",
+  "NQO1",
+  "NR2F2",
+  "NR2F6",
+  "NR4A1",
+  "NRGN",
+  "NRP1",
+  "NSA2",
+  "NSMF",
+  "NTRK2",
+  "NUCB1",
+  "NUCKS1",
+  "NUDC",
+  "NUDT3",
+  "NUMA1",
+  "NUPR1",
+  "NUTF2",
+  "OAF",
+  "OAZ1",
+  "OAZ2",
+  "OBSL1",
+  "OCIAD1",
+  "OCIAD2",
+  "ODC1",
+  "OGA",
+  "OGDH",
+  "OGT",
+  "OLFM1",
+  "OLFM4",
+  "OPTN",
+  "ORM2",
+  "ORMDL3",
+  "OS9",
+  "OST4",
+  "OTUB1",
+  "OXA1L",
+  "P4HB",
+  "PA2G4",
+  "PABPC4",
+  "PAFAH1B1",
+  "PAFAH1B2",
+  "PAIP2",
+  "PALLD",
+  "PAM",
+  "PAPOLA",
+  "PARVA",
+  "PATJ",
+  "PBX1",
+  "PBXIP1",
+  "PCBD1",
+  "PCBP1",
+  "PCBP2",
+  "PCK1",
+  "PCM1",
+  "PCMT1",
+  "PCOLCE",
+  "PCP4",
+  "PCSK1N",
+  "PDCD4",
+  "PDCD5",
+  "PDCD6",
+  "PDCD6IP",
+  "PDGFRB",
+  "PDHA1",
+  "PDHB",
+  "PDIA3",
+  "PDIA4",
+  "PDIA6",
+  "PDK4",
+  "PDLIM3",
+  "PDLIM5",
+  "PDLIM7",
+  "PDS5A",
+  "PDXK",
+  "PDZK1IP1",
+  "PEA15",
+  "PEBP1",
+  "PECAM1",
+  "PER1",
+  "PERP",
+  "PET100",
+  "PFDN2",
+  "PFDN5",
+  "PFKM",
+  "PFKP",
+  "PFN1",
+  "PFN2",
+  "PGAM1",
+  "PGAM2",
+  "PGD",
+  "PGGHG",
+  "PGK1",
+  "PGLS",
+  "PGRMC1",
+  "PGRMC2",
+  "PHB",
+  "PHB2",
+  "PHC2",
+  "PHGDH",
+  "PHGR1",
+  "PHLDA1",
+  "PHLDB1",
+  "PHPT1",
+  "PI3",
+  "PI4KA",
+  "PICALM",
+  "PIEZO1",
+  "PIGR",
+  "PIGT",
+  "PILRB",
+  "PIM3",
+  "PIN1",
+  "PINK1",
+  "PITPNA",
+  "PJA2",
+  "PKD1",
+  "PKIG",
+  "PLA2G2A",
+  "PLAC9",
+  "PLD3",
+  "PLEC",
+  "PLEKHB2",
+  "PLEKHO1",
+  "PLIN2",
+  "PLN",
+  "PLP1",
+  "PLP2",
+  "PLPP1",
+  "PLPP3",
+  "PLSCR1",
+  "PLTP",
+  "PLXNB1",
+  "PLXNB2",
+  "PLXND1",
+  "PMEPA1",
+  "PMP22",
+  "PNISR",
+  "PNKD",
+  "PNN",
+  "PNPLA2",
+  "PNRC1",
+  "PNRC2",
+  "POLD2",
+  "POLD4",
+  "POLDIP2",
+  "POLR1D",
+  "POLR2A",
+  "POLR2F",
+  "POLR2G",
+  "POLR2I",
+  "POLR2K",
+  "POLR2L",
+  "POMP",
+  "PON2",
+  "POR",
+  "POSTN",
+  "PPDPF",
+  "PPFIBP1",
+  "PPIB",
+  "PPIF",
+  "PPM1G",
+  "PPP1CA",
+  "PPP1CB",
+  "PPP1CC",
+  "PPP1R12B",
+  "PPP1R12C",
+  "PPP1R14A",
+  "PPP1R1A",
+  "PPP1R1B",
+  "PPP1R9B",
+  "PPP2CB",
+  "PPP2R5C",
+  "PPP3CA",
+  "PPP3CB",
+  "PPP4C",
+  "PPP4R2",
+  "PPP6R2",
+  "PRAP1",
+  "PRB3",
+  "PRDX3",
+  "PRDX4",
+  "PRDX5",
+  "PRDX6",
+  "PRELID3B",
+  "PRELP",
+  "PREPL",
+  "PRKACA",
+  "PRKCSH",
+  "PRMT2",
+  "PRNP",
+  "PRPF6",
+  "PRPF8",
+  "PRRC2A",
+  "PRRC2B",
+  "PRRC2C",
+  "PRSS23",
+  "PRSS8",
+  "PSAP",
+  "PSENEN",
+  "PSMA1",
+  "PSMA2",
+  "PSMA4",
+  "PSMA5",
+  "PSMA7",
+  "PSMB1",
+  "PSMB2",
+  "PSMB3",
+  "PSMB4",
+  "PSMB5",
+  "PSMB6",
+  "PSMB7",
+  "PSMB8",
+  "PSMC3",
+  "PSMC5",
+  "PSMD11",
+  "PSMD13",
+  "PSMD2",
+  "PSMD3",
+  "PSMD4",
+  "PSMD7",
+  "PSME1",
+  "PSME2",
+  "PSMF1",
+  "PTBP3",
+  "PTEN",
+  "PTGDS",
+  "PTGES2",
+  "PTGES3",
+  "PTGR1",
+  "PTK2",
+  "PTMS",
+  "PTN",
+  "PTOV1",
+  "PTP4A3",
+  "PTPA",
+  "PTPN12",
+  "PTPRF",
+  "PTTG1IP",
+  "PUF60",
+  "PYGB",
+  "PYURF",
+  "QDPR",
+  "QKI",
+  "QSOX1",
+  "RAB10",
+  "RAB11A",
+  "RAB11B",
+  "RAB13",
+  "RAB14",
+  "RAB18",
+  "RAB1A",
+  "RAB1B",
+  "RAB21",
+  "RAB25",
+  "RAB2A",
+  "RAB5A",
+  "RAB5B",
+  "RAB5C",
+  "RAB5IF",
+  "RAB7A",
+  "RABAC1",
+  "RABL6",
+  "RAC1",
+  "RACK1",
+  "RAD21",
+  "RAD23A",
+  "RALY",
+  "RAMP1",
+  "RAP1A",
+  "RARRES2",
+  "RBCK1",
+  "RBM17",
+  "RBM25",
+  "RBM3",
+  "RBM39",
+  "RBM42",
+  "RBM47",
+  "RBM5",
+  "RBM6",
+  "RBM8A",
+  "RBP4",
+  "RBPMS",
+  "RBX1",
+  "RCC2",
+  "RCN1",
+  "RCN2",
+  "RDH11",
+  "REEP5",
+  "REG1A",
+  "RELA",
+  "REPIN1",
+  "RER1",
+  "RERE",
+  "RETREG2",
+  "REXO2",
+  "RGCC",
+  "RGS5",
+  "RHBDD2",
+  "RHOA",
+  "RHOB",
+  "RHOBTB3",
+  "RHOQ",
+  "RHOT2",
+  "RIC8A",
+  "RIDA",
+  "RING1",
+  "RMND5A",
+  "RNASE1",
+  "RNASEK",
+  "RNASET2",
+  "RNF10",
+  "RNF11",
+  "RNF114",
+  "RNF130",
+  "RNF145",
+  "RNF187",
+  "RNF213",
+  "RNH1",
+  "RNPS1",
+  "ROMO1",
+  "RPN1",
+  "RPN2",
+  "RRAD",
+  "RRAS",
+  "RSL1D1",
+  "RSRP1",
+  "RTF2",
+  "RTL8C",
+  "RTN1",
+  "RTN4",
+  "RTRAF",
+  "RUNX1",
+  "RUVBL2",
+  "RWDD1",
+  "RXRA",
+  "S100A1",
+  "S100A10",
+  "S100A11",
+  "S100A13",
+  "S100A14",
+  "S100A16",
+  "S100A2",
+  "S100A4",
+  "S100A6",
+  "S100A8",
+  "S100A9",
+  "S100B",
+  "S100P",
+  "SAFB",
+  "SAFB2",
+  "SAMHD1",
+  "SAP18",
+  "SAR1A",
+  "SAT1",
+  "SAT2",
+  "SBDS",
+  "SCAF11",
+  "SCAMP2",
+  "SCAND1",
+  "SCARB2",
+  "SCD",
+  "SCGB2A2",
+  "SCP2",
+  "SDC1",
+  "SDC2",
+  "SDC3",
+  "SDC4",
+  "SDCBP",
+  "SDF4",
+  "SDHA",
+  "SDHB",
+  "SEC11A",
+  "SEC11C",
+  "SEC13",
+  "SEC31A",
+  "SEC61A1",
+  "SEC61G",
+  "SEC62",
+  "SEL1L",
+  "SELENBP1",
+  "SELENOF",
+  "SELENOH",
+  "SELENOK",
+  "SELENOM",
+  "SELENON",
+  "SELENOP",
+  "SELENOW",
+  "SEM1",
+  "SEPHS2",
+  "SERBP1",
+  "SERF2",
+  "SERINC1",
+  "SERINC2",
+  "SERINC3",
+  "SERP1",
+  "SERPINA1",
+  "SERPINA3",
+  "SERPINB1",
+  "SERPINB6",
+  "SERPINC1",
+  "SERPINE1",
+  "SERPINE2",
+  "SERPINF1",
+  "SERPINF2",
+  "SERPING1",
+  "SET",
+  "SF1",
+  "SF3B1",
+  "SF3B2",
+  "SF3B5",
+  "SF3B6",
+  "SFPQ",
+  "SFRP2",
+  "SFTPB",
+  "SGK1",
+  "SH3BGRL",
+  "SH3BGRL3",
+  "SH3GLB1",
+  "SH3GLB2",
+  "SHISA5",
+  "SIGIRR",
+  "SIVA1",
+  "SLC12A2",
+  "SLC1A2",
+  "SLC1A3",
+  "SLC22A17",
+  "SLC25A1",
+  "SLC25A11",
+  "SLC25A39",
+  "SLC25A4",
+  "SLC2A1",
+  "SLC2A4RG",
+  "SLC38A1",
+  "SLC38A10",
+  "SLC38A2",
+  "SLC39A1",
+  "SLC39A14",
+  "SLC39A6",
+  "SLC39A7",
+  "SLC3A2",
+  "SLC40A1",
+  "SLC44A1",
+  "SLC44A2",
+  "SLC44A4",
+  "SLC45A3",
+  "SLC9A3R1",
+  "SLC9A3R2",
+  "SLIRP",
+  "SLPI",
+  "SLTM",
+  "SMARCA5",
+  "SMARCC1",
+  "SMARCE1",
+  "SMCHD1",
+  "SMDT1",
+  "SMIM26",
+  "SMIM4",
+  "SMS",
+  "SMTN",
+  "SNAP25",
+  "SND1",
+  "SNRNP200",
+  "SNRNP70",
+  "SNRPB",
+  "SNRPC",
+  "SNRPD1",
+  "SNRPE",
+  "SNRPF",
+  "SNRPG",
+  "SNU13",
+  "SNX1",
+  "SNX17",
+  "SNX3",
+  "SOCS3",
+  "SOD1",
+  "SOD2",
+  "SOD3",
+  "SON",
+  "SORBS1",
+  "SORBS2",
+  "SORBS3",
+  "SORL1",
+  "SORT1",
+  "SOX4",
+  "SPAG9",
+  "SPARC",
+  "SPARCL1",
+  "SPATS2L",
+  "SPCS1",
+  "SPCS3",
+  "SPDEF",
+  "SPIN1",
+  "SPINK1",
+  "SPINK4",
+  "SPINT1",
+  "SPINT2",
+  "SPON2",
+  "SPP1",
+  "SPSB3",
+  "SPTAN1",
+  "SPTBN1",
+  "SQOR",
+  "SQSTM1",
+  "SREBF1",
+  "SREBF2",
+  "SRGN",
+  "SRI",
+  "SRM",
+  "SRP9",
+  "SRPRA",
+  "SRRM2",
+  "SRRT",
+  "SRSF1",
+  "SRSF11",
+  "SRSF2",
+  "SRSF3",
+  "SRSF5",
+  "SRSF7",
+  "SRSF9",
+  "SSBP1",
+  "SSBP3",
+  "SSR1",
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models/ej_ad_mv_fold0/meta.json

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+  "CEBPD",
+  "CELF1",
+  "CENPX",
+  "CERCAM",
+  "CERS2",
+  "CES2",
+  "CFB",
+  "CFD",
+  "CFH",
+  "CFL2",
+  "CFLAR",
+  "CHCHD1",
+  "CHCHD10",
+  "CHCHD2",
+  "CHD4",
+  "CHGA",
+  "CHI3L1",
+  "CHID1",
+  "CHMP1B",
+  "CHMP2A",
+  "CHMP3",
+  "CHMP4B",
+  "CHMP5",
+  "CHN1",
+  "CHP1",
+  "CHPF",
+  "CHTOP",
+  "CHURC1",
+  "CIB1",
+  "CIRBP",
+  "CISD3",
+  "CKAP4",
+  "CKB",
+  "CKMT2",
+  "CLDN3",
+  "CLDN4",
+  "CLDN5",
+  "CLDN7",
+  "CLIC1",
+  "CLIC4",
+  "CLIP1",
+  "CLK1",
+  "CLPTM1",
+  "CLPTM1L",
+  "CLSTN1",
+  "CLTA",
+  "CLTB",
+  "CLTC",
+  "CLU",
+  "CLUH",
+  "CMBL",
+  "CMPK1",
+  "CMYA5",
+  "CNBP",
+  "CNDP2",
+  "CNN1",
+  "CNN2",
+  "CNN3",
+  "CNP",
+  "CNPY2",
+  "COA3",
+  "COA4",
+  "COL16A1",
+  "COL18A1",
+  "COL1A1",
+  "COL1A2",
+  "COL3A1",
+  "COL4A1",
+  "COL4A2",
+  "COL5A1",
+  "COL5A2",
+  "COL6A1",
+  "COL6A2",
+  "COL6A3",
+  "COLGALT1",
+  "COMMD6",
+  "COMT",
+  "COPA",
+  "COPB2",
+  "COPE",
+  "COPG1",
+  "COPS6",
+  "COPS9",
+  "COPZ1",
+  "COQ8A",
+  "CORO1C",
+  "COTL1",
+  "COX14",
+  "COX17",
+  "COX4I1",
+  "COX5B",
+  "COX6A1",
+  "COX6B1",
+  "COX6C",
+  "COX7A1",
+  "COX7A2",
+  "COX7A2L",
+  "COX7B",
+  "COX7C",
+  "COX8A",
+  "CP",
+  "CPE",
+  "CPNE1",
+  "CRABP2",
+  "CREB3L1",
+  "CREBZF",
+  "CREG1",
+  "CRELD2",
+  "CRIM1",
+  "CRIP1",
+  "CRIP2",
+  "CRISPLD2",
+  "CRP",
+  "CRTAP",
+  "CRYAB",
+  "CS",
+  "CSDE1",
+  "CSNK1D",
+  "CSNK1G2",
+  "CSNK2B",
+  "CSRP3",
+  "CST3",
+  "CSTA",
+  "CSTB",
+  "CTDNEP1",
+  "CTDSP1",
+  "CTDSP2",
+  "CTNNA1",
+  "CTNNB1",
+  "CTNNBIP1",
+  "CTNND1",
+  "CTSA",
+  "CTSB",
+  "CTSC",
+  "CTSD",
+  "CTSF",
+  "CTSH",
+  "CTSL",
+  "CTSS",
+  "CTSZ",
+  "CTTN",
+  "CTXN1",
+  "CUTA",
+  "CUX1",
+  "CXCL12",
+  "CXCL14",
+  "CXCR4",
+  "CYB5A",
+  "CYB5B",
+  "CYB5R3",
+  "CYBA",
+  "CYBRD1",
+  "CYC1",
+  "CYCS",
+  "CYHR1",
+  "CYP1B1",
+  "CYP2C8",
+  "CYP2E1",
+  "CYSTM1",
+  "CYTH2",
+  "DAB2",
+  "DAD1",
+  "DAG1",
+  "DAP",
+  "DAZAP1",
+  "DAZAP2",
+  "DBI",
+  "DBNL",
+  "DCAF7",
+  "DCAF8",
+  "DCN",
+  "DCTN1",
+  "DCTN2",
+  "DCTN3",
+  "DCXR",
+  "DDAH1",
+  "DDAH2",
+  "DDB1",
+  "DDIT4",
+  "DDR1",
+  "DDRGK1",
+  "DDT",
+  "DDX1",
+  "DDX17",
+  "DDX21",
+  "DDX23",
+  "DDX24",
+  "DDX39B",
+  "DDX3X",
+  "DDX5",
+  "DDX6",
+  "DECR1",
+  "DEFB1",
+  "DEGS1",
+  "DEK",
+  "DEPP1",
+  "DES",
+  "DHCR24",
+  "DHRS3",
+  "DHRS7",
+  "DHX15",
+  "DHX30",
+  "DIDO1",
+  "DKK3",
+  "DLGAP4",
+  "DMKN",
+  "DMPK",
+  "DNAJA1",
+  "DNAJB1",
+  "DNAJB2",
+  "DNAJB6",
+  "DNAJC15",
+  "DNAJC7",
+  "DNM1",
+  "DNM2",
+  "DNPEP",
+  "DNPH1",
+  "DPEP1",
+  "DPM3",
+  "DPP7",
+  "DPYSL2",
+  "DPYSL3",
+  "DRAP1",
+  "DSP",
+  "DST",
+  "DSTN",
+  "DUS1L",
+  "DUSP1",
+  "DUSP23",
+  "DUSP3",
+  "DUT",
+  "DYNC1H1",
+  "DYNC1I2",
+  "DYNC1LI2",
+  "DYNLL1",
+  "DYNLL2",
+  "DYNLT1",
+  "EBPL",
+  "ECE1",
+  "ECH1",
+  "ECHDC2",
+  "ECHS1",
+  "ECI1",
+  "EDF1",
+  "EEF1A2",
+  "EEF1B2",
+  "EEF1G",
+  "EEF2",
+  "EFEMP1",
+  "EFHD1",
+  "EFHD2",
+  "EFNA1",
+  "EGFL7",
+  "EGR1",
+  "EHBP1L1",
+  "EHD2",
+  "EI24",
+  "EID1",
+  "EIF1",
+  "EIF1AX",
+  "EIF1B",
+  "EIF2S2",
+  "EIF2S3",
+  "EIF3A",
+  "EIF3B",
+  "EIF3D",
+  "EIF3E",
+  "EIF3G",
+  "EIF3H",
+  "EIF3I",
+  "EIF3L",
+  "EIF3M",
+  "EIF4A1",
+  "EIF4A2",
+  "EIF4B",
+  "EIF4EBP2",
+  "EIF4G1",
+  "EIF4G2",
+  "EIF4H",
+  "EIF5",
+  "EIF5B",
+  "EIF6",
+  "ELAVL1",
+  "ELF3",
+  "ELL2",
+  "ELN",
+  "ELOVL5",
+  "EMC10",
+  "EMC4",
+  "EMILIN1",
+  "EMP1",
+  "EMP2",
+  "EMP3",
+  "ENAH",
+  "ENC1",
+  "ENG",
+  "ENO1",
+  "ENO2",
+  "ENTPD6",
+  "ENY2",
+  "EPAS1",
+  "EPCAM",
+  "EPHX1",
+  "EPN1",
+  "EPS8L2",
+  "ERBB2",
+  "ERBB3",
+  "ERGIC1",
+  "ERGIC3",
+  "ERH",
+  "ERO1A",
+  "ERP29",
+  "ERRFI1",
+  "ESD",
+  "ESYT2",
+  "ETFA",
+  "ETFB",
+  "ETHE1",
+  "ETS2",
+  "EVL",
+  "EZR",
+  "F2",
+  "F3",
+  "FABP1",
+  "FABP4",
+  "FABP5",
+  "FAM107A",
+  "FAM120A",
+  "FAM162A",
+  "FAM3C",
+  "FAM3D",
+  "FAM50A",
+  "FARP1",
+  "FASN",
+  "FAT1",
+  "FBLN1",
+  "FBLN2",
+  "FBN1",
+  "FBP1",
+  "FBXL5",
+  "FBXW5",
+  "FCER1G",
+  "FCGBP",
+  "FCGRT",
+  "FDFT1",
+  "FDPS",
+  "FGA",
+  "FGFRL1",
+  "FGG",
+  "FHL2",
+  "FIS1",
+  "FKBP10",
+  "FKBP3",
+  "FKBP5",
+  "FKBP8",
+  "FKBP9",
+  "FLII",
+  "FLNA",
+  "FLNB",
+  "FLNC",
+  "FLOT1",
+  "FLOT2",
+  "FMOD",
+  "FN1",
+  "FNDC3B",
+  "FOS",
+  "FOSB",
+  "FOXA1",
+  "FOXN3",
+  "FOXO3",
+  "FOXP1",
+  "FSTL1",
+  "FTH1",
+  "FTL",
+  "FUNDC2",
+  "FURIN",
+  "FUS",
+  "FXR1",
+  "FXYD1",
+  "FXYD2",
+  "FXYD3",
+  "FXYD5",
+  "FXYD6",
+  "G0S2",
+  "G3BP2",
+  "GAA",
+  "GABARAP",
+  "GABARAPL2",
+  "GADD45B",
+  "GADD45G",
+  "GADD45GIP1",
+  "GALNT2",
+  "GAMT",
+  "GANAB",
+  "GAS6",
+  "GATAD2A",
+  "GATD1",
+  "GATM",
+  "GDF15",
+  "GDI1",
+  "GDI2",
+  "GGT5",
+  "GHITM",
+  "GID8",
+  "GIPC1",
+  "GJA1",
+  "GLG1",
+  "GLO1",
+  "GLRX5",
+  "GLS",
+  "GLUD1",
+  "GLUL",
+  "GM2A",
+  "GNA11",
+  "GNAI2",
+  "GNAQ",
+  "GNB1",
+  "GNG11",
+  "GNG5",
+  "GNPTG",
+  "GNS",
+  "GOLGB1",
+  "GOLM1",
+  "GOLPH3",
+  "GOT1",
+  "GOT2",
+  "GPAA1",
+  "GPC1",
+  "GPI",
+  "GPM6A",
+  "GPNMB",
+  "GPRC5A",
+  "GPRC5B",
+  "GPS1",
+  "GPX2",
+  "GPX3",
+  "GPX4",
+  "GRHPR",
+  "GRINA",
+  "GRK2",
+  "GRN",
+  "GRSF1",
+  "GSN",
+  "GSPT1",
+  "GSTK1",
+  "GSTM3",
+  "GSTO1",
+  "GSTP1",
+  "GTF2I",
+  "GTF3A",
+  "GTF3C1",
+  "GTF3C6",
+  "GUK1",
+  "GYPC",
+  "HADHA",
+  "HADHB",
+  "HAGH",
+  "HAMP",
+  "HBA2",
+  "HCFC1R1",
+  "HDAC1",
+  "HDGF",
+  "HDLBP",
+  "HEBP2",
+  "HERPUD1",
+  "HES4",
+  "HEXA",
+  "HEXB",
+  "HGS",
+  "HIF1A",
+  "HINT1",
+  "HIPK2",
+  "HIPK3",
+  "HK1",
+  "HM13",
+  "HMG20B",
+  "HMGA1",
+  "HMGCS2",
+  "HMGN3",
+  "HMOX1",
+  "HNRNPA0",
+  "HNRNPA2B1",
+  "HNRNPA3",
+  "HNRNPC",
+  "HNRNPD",
+  "HNRNPDL",
+  "HNRNPF",
+  "HNRNPH3",
+  "HNRNPK",
+  "HNRNPR",
+  "HNRNPU",
+  "HNRNPUL1",
+  "HNRNPUL2",
+  "HOPX",
+  "HP1BP3",
+  "HPCAL1",
+  "HPD",
+  "HPX",
+  "HRC",
+  "HSBP1",
+  "HSD11B2",
+  "HSD17B10",
+  "HSD17B4",
+  "HSF1",
+  "HSP90AA1",
+  "HSP90AB1",
+  "HSP90B1",
+  "HSPA1A",
+  "HSPA1B",
+  "HSPA5",
+  "HSPA8",
+  "HSPA9",
+  "HSPB1",
+  "HSPB6",
+  "HSPB7",
+  "HSPB8",
+  "HSPD1",
+  "HSPE1",
+  "HSPG2",
+  "HSPH1",
+  "HTRA1",
+  "HUWE1",
+  "ICAM1",
+  "ID1",
+  "ID2",
+  "ID3",
+  "ID4",
+  "IDH2",
+  "IDI1",
+  "IDS",
+  "IER2",
+  "IER3",
+  "IFI16",
+  "IFI27",
+  "IFI27L2",
+  "IFI30",
+  "IFI6",
+  "IFITM2",
+  "IFITM3",
+  "IFNAR1",
+  "IFNGR2",
+  "IGFBP2",
+  "IGFBP3",
+  "IGFBP4",
+  "IGFBP5",
+  "IGFBP6",
+  "IGFBP7",
+  "IGHG1",
+  "IGHG3",
+  "IGHM",
+  "IGKC",
+  "IGLC1",
+  "IL1R1",
+  "IL32",
+  "ILF2",
+  "ILF3",
+  "ILK",
+  "IMPDH2",
+  "INF2",
+  "INSIG1",
+  "INSR",
+  "INTS1",
+  "INTS11",
+  "IP6K2",
+  "IPO5",
+  "IQGAP1",
+  "IRAK1",
+  "IRF1",
+  "ISCU",
+  "ISG15",
+  "ISLR",
+  "ITFG1",
+  "ITGA3",
+  "ITGA5",
+  "ITGA6",
+  "ITGAV",
+  "ITGB1",
+  "ITGB4",
+  "ITGB5",
+  "ITM2B",
+  "ITM2C",
+  "ITPK1",
+  "IVNS1ABP",
+  "JCHAIN",
+  "JPT1",
+  "JTB",
+  "JUN",
+  "JUNB",
+  "JUP",
+  "KANK2",
+  "KCTD12",
+  "KDELR1",
+  "KDELR2",
+  "KHDRBS1",
+  "KHSRP",
+  "KIAA1522",
+  "KIF1B",
+  "KIF1C",
+  "KIF5B",
+  "KLC1",
+  "KLF5",
+  "KLF6",
+  "KLF9",
+  "KLHDC3",
+  "KLK2",
+  "KLK4",
+  "KPNA4",
+  "KPNB1",
+  "KRT1",
+  "KRT10",
+  "KRT14",
+  "KRT16",
+  "KRT6B",
+  "KRT7",
+  "KRT8",
+  "KRTCAP2",
+  "KTN1",
+  "KXD1",
+  "LAMA4",
+  "LAMA5",
+  "LAMB1",
+  "LAMB2",
+  "LAMC1",
+  "LAMP1",
+  "LAMP2",
+  "LAMTOR1",
+  "LAMTOR4",
+  "LAP3",
+  "LAPTM4A",
+  "LAPTM4B",
+  "LAPTM5",
+  "LARP1",
+  "LASP1",
+  "LBH",
+  "LCN2",
+  "LDB3",
+  "LENG8",
+  "LGALS1",
+  "LGALS3",
+  "LGALS3BP",
+  "LGALS4",
+  "LGMN",
+  "LIMS2",
+  "LITAF",
+  "LMAN1",
+  "LMAN2",
+  "LMNA",
+  "LMO4",
+  "LMO7",
+  "LPCAT1",
+  "LPP",
+  "LRP1",
+  "LRP10",
+  "LRPAP1",
+  "LRRC59",
+  "LRRFIP1",
+  "LSM14A",
+  "LSM3",
+  "LSM4",
+  "LSM7",
+  "LSP1",
+  "LSR",
+  "LTBP3",
+  "LTBP4",
+  "LTBR",
+  "LTF",
+  "LUC7L",
+  "LUC7L2",
+  "LUC7L3",
+  "LUM",
+  "LY6E",
+  "LYZ",
+  "MACF1",
+  "MAF",
+  "MAF1",
+  "MAGED1",
+  "MAGED2",
+  "MAL2",
+  "MANF",
+  "MAOA",
+  "MAP1B",
+  "MAP1LC3A",
+  "MAP2K2",
+  "MAP2K3",
+  "MAP3K20",
+  "MAP4",
+  "MAP7",
+  "MAP7D1",
+  "MAPK1",
+  "MAPK1IP1L",
+  "MAPK3",
+  "MAPKAPK2",
+  "MAPRE1",
+  "MARCKS",
+  "MARCKSL1",
+  "MAT2A",
+  "MAZ",
+  "MB",
+  "MBNL1",
+  "MBNL2",
+  "MBOAT7",
+  "MBP",
+  "MCAM",
+  "MCL1",
+  "MCM7",
+  "MCRIP1",
+  "MDH2",
+  "MDK",
+  "MDM4",
+  "MEA1",
+  "MEAF6",
+  "METAP2",
+  "METRN",
+  "METRNL",
+  "METTL26",
+  "METTL9",
+  "MFAP4",
+  "MFGE8",
+  "MFN2",
+  "MFSD10",
+  "MGAT1",
+  "MGAT4B",
+  "MGLL",
+  "MGST1",
+  "MGST3",
+  "MICAL2",
+  "MIDN",
+  "MIEN1",
+  "MIF",
+  "MKNK2",
+  "MLEC",
+  "MLF2",
+  "MLLT1",
+  "MLLT6",
+  "MLPH",
+  "MMP14",
+  "MMP2",
+  "MMP24OS",
+  "MMP7",
+  "MOB1A",
+  "MORF4L1",
+  "MORF4L2",
+  "MPC1",
+  "MPC2",
+  "MPRIP",
+  "MPST",
+  "MRC2",
+  "MRFAP1L1",
+  "MSI2",
+  "MSN",
+  "MSRB2",
+  "MT1E",
+  "MT1F",
+  "MT1G",
+  "MT1X",
+  "MT2A",
+  "MT3",
+  "MTCH1",
+  "MTDH",
+  "MTPN",
+  "MTURN",
+  "MUC1",
+  "MUC2",
+  "MUC5B",
+  "MVP",
+  "MXD4",
+  "MXRA7",
+  "MXRA8",
+  "MYADM",
+  "MYBPC3",
+  "MYC",
+  "MYDGF",
+  "MYH14",
+  "MYH7",
+  "MYH9",
+  "MYL12A",
+  "MYL12B",
+  "MYL3",
+  "MYL9",
+  "MYLK",
+  "MYO15B",
+  "MYO1C",
+  "MYO6",
+  "MYOZ2",
+  "N4BP2L2",
+  "NAA38",
+  "NAMPT",
+  "NAP1L4",
+  "NAPA",
+  "NAXE",
+  "NBL1",
+  "NBR1",
+  "NCAM1",
+  "NCDN",
+  "NCKAP1",
+  "NCL",
+  "NCOA4",
+  "NCOA7",
+  "NCOR1",
+  "NCOR2",
+  "NDFIP1",
+  "NDRG1",
+  "NDRG2",
+  "NDRG4",
+  "NDUFA1",
+  "NDUFA10",
+  "NDUFA11",
+  "NDUFA12",
+  "NDUFA13",
+  "NDUFA2",
+  "NDUFA3",
+  "NDUFA4",
+  "NDUFA4L2",
+  "NDUFA6",
+  "NDUFA7",
+  "NDUFA8",
+  "NDUFAB1",
+  "NDUFAF3",
+  "NDUFAF8",
+  "NDUFB10",
+  "NDUFB11",
+  "NDUFB2",
+  "NDUFB5",
+  "NDUFB6",
+  "NDUFB7",
+  "NDUFB9",
+  "NDUFC1",
+  "NDUFC2",
+  "NDUFS1",
+  "NDUFS2",
+  "NDUFS3",
+  "NDUFS4",
+  "NDUFS5",
+  "NDUFS6",
+  "NDUFS7",
+  "NDUFS8",
+  "NDUFV1",
+  "NDUFV2",
+  "NDUFV3",
+  "NEBL",
+  "NECTIN2",
+  "NEDD8",
+  "NENF",
+  "NES",
+  "NET1",
+  "NEXN",
+  "NFE2L1",
+  "NFE2L2",
+  "NFIA",
+  "NFIB",
+  "NFIC",
+  "NFIX",
+  "NFKBIA",
+  "NHP2",
+  "NID1",
+  "NINJ1",
+  "NIPSNAP2",
+  "NISCH",
+  "NKTR",
+  "NME1",
+  "NME2",
+  "NME3",
+  "NME4",
+  "NNMT",
+  "NONO",
+  "NOP10",
+  "NOP53",
+  "NOTCH3",
+  "NPC2",
+  "NPDC1",
+  "NPTN",
+  "NQO1",
+  "NR2F2",
+  "NR2F6",
+  "NR4A1",
+  "NRGN",
+  "NRP1",
+  "NSA2",
+  "NSMF",
+  "NTRK2",
+  "NUCB1",
+  "NUCKS1",
+  "NUDC",
+  "NUDT3",
+  "NUMA1",
+  "NUPR1",
+  "NUTF2",
+  "OAF",
+  "OAZ1",
+  "OAZ2",
+  "OBSL1",
+  "OCIAD1",
+  "OCIAD2",
+  "ODC1",
+  "OGA",
+  "OGDH",
+  "OGT",
+  "OLFM1",
+  "OLFM4",
+  "OPTN",
+  "ORM2",
+  "ORMDL3",
+  "OS9",
+  "OST4",
+  "OTUB1",
+  "OXA1L",
+  "P4HB",
+  "PA2G4",
+  "PABPC4",
+  "PAFAH1B1",
+  "PAFAH1B2",
+  "PAIP2",
+  "PALLD",
+  "PAM",
+  "PAPOLA",
+  "PARVA",
+  "PATJ",
+  "PBX1",
+  "PBXIP1",
+  "PCBD1",
+  "PCBP1",
+  "PCBP2",
+  "PCK1",
+  "PCM1",
+  "PCMT1",
+  "PCOLCE",
+  "PCP4",
+  "PCSK1N",
+  "PDCD4",
+  "PDCD5",
+  "PDCD6",
+  "PDCD6IP",
+  "PDGFRB",
+  "PDHA1",
+  "PDHB",
+  "PDIA3",
+  "PDIA4",
+  "PDIA6",
+  "PDK4",
+  "PDLIM3",
+  "PDLIM5",
+  "PDLIM7",
+  "PDS5A",
+  "PDXK",
+  "PDZK1IP1",
+  "PEA15",
+  "PEBP1",
+  "PECAM1",
+  "PER1",
+  "PERP",
+  "PET100",
+  "PFDN2",
+  "PFDN5",
+  "PFKM",
+  "PFKP",
+  "PFN1",
+  "PFN2",
+  "PGAM1",
+  "PGAM2",
+  "PGD",
+  "PGGHG",
+  "PGK1",
+  "PGLS",
+  "PGRMC1",
+  "PGRMC2",
+  "PHB",
+  "PHB2",
+  "PHC2",
+  "PHGDH",
+  "PHGR1",
+  "PHLDA1",
+  "PHLDB1",
+  "PHPT1",
+  "PI3",
+  "PI4KA",
+  "PICALM",
+  "PIEZO1",
+  "PIGR",
+  "PIGT",
+  "PILRB",
+  "PIM3",
+  "PIN1",
+  "PINK1",
+  "PITPNA",
+  "PJA2",
+  "PKD1",
+  "PKIG",
+  "PLA2G2A",
+  "PLAC9",
+  "PLD3",
+  "PLEC",
+  "PLEKHB2",
+  "PLEKHO1",
+  "PLIN2",
+  "PLN",
+  "PLP1",
+  "PLP2",
+  "PLPP1",
+  "PLPP3",
+  "PLSCR1",
+  "PLTP",
+  "PLXNB1",
+  "PLXNB2",
+  "PLXND1",
+  "PMEPA1",
+  "PMP22",
+  "PNISR",
+  "PNKD",
+  "PNN",
+  "PNPLA2",
+  "PNRC1",
+  "PNRC2",
+  "POLD2",
+  "POLD4",
+  "POLDIP2",
+  "POLR1D",
+  "POLR2A",
+  "POLR2F",
+  "POLR2G",
+  "POLR2I",
+  "POLR2K",
+  "POLR2L",
+  "POMP",
+  "PON2",
+  "POR",
+  "POSTN",
+  "PPDPF",
+  "PPFIBP1",
+  "PPIB",
+  "PPIF",
+  "PPM1G",
+  "PPP1CA",
+  "PPP1CB",
+  "PPP1CC",
+  "PPP1R12B",
+  "PPP1R12C",
+  "PPP1R14A",
+  "PPP1R1A",
+  "PPP1R1B",
+  "PPP1R9B",
+  "PPP2CB",
+  "PPP2R5C",
+  "PPP3CA",
+  "PPP3CB",
+  "PPP4C",
+  "PPP4R2",
+  "PPP6R2",
+  "PRAP1",
+  "PRB3",
+  "PRDX3",
+  "PRDX4",
+  "PRDX5",
+  "PRDX6",
+  "PRELID3B",
+  "PRELP",
+  "PREPL",
+  "PRKACA",
+  "PRKCSH",
+  "PRMT2",
+  "PRNP",
+  "PRPF6",
+  "PRPF8",
+  "PRRC2A",
+  "PRRC2B",
+  "PRRC2C",
+  "PRSS23",
+  "PRSS8",
+  "PSAP",
+  "PSENEN",
+  "PSMA1",
+  "PSMA2",
+  "PSMA4",
+  "PSMA5",
+  "PSMA7",
+  "PSMB1",
+  "PSMB2",
+  "PSMB3",
+  "PSMB4",
+  "PSMB5",
+  "PSMB6",
+  "PSMB7",
+  "PSMB8",
+  "PSMC3",
+  "PSMC5",
+  "PSMD11",
+  "PSMD13",
+  "PSMD2",
+  "PSMD3",
+  "PSMD4",
+  "PSMD7",
+  "PSME1",
+  "PSME2",
+  "PSMF1",
+  "PTBP3",
+  "PTEN",
+  "PTGDS",
+  "PTGES2",
+  "PTGES3",
+  "PTGR1",
+  "PTK2",
+  "PTMS",
+  "PTN",
+  "PTOV1",
+  "PTP4A3",
+  "PTPA",
+  "PTPN12",
+  "PTPRF",
+  "PTTG1IP",
+  "PUF60",
+  "PYGB",
+  "PYURF",
+  "QDPR",
+  "QKI",
+  "QSOX1",
+  "RAB10",
+  "RAB11A",
+  "RAB11B",
+  "RAB13",
+  "RAB14",
+  "RAB18",
+  "RAB1A",
+  "RAB1B",
+  "RAB21",
+  "RAB25",
+  "RAB2A",
+  "RAB5A",
+  "RAB5B",
+  "RAB5C",
+  "RAB5IF",
+  "RAB7A",
+  "RABAC1",
+  "RABL6",
+  "RAC1",
+  "RACK1",
+  "RAD21",
+  "RAD23A",
+  "RALY",
+  "RAMP1",
+  "RAP1A",
+  "RARRES2",
+  "RBCK1",
+  "RBM17",
+  "RBM25",
+  "RBM3",
+  "RBM39",
+  "RBM42",
+  "RBM47",
+  "RBM5",
+  "RBM6",
+  "RBM8A",
+  "RBP4",
+  "RBPMS",
+  "RBX1",
+  "RCC2",
+  "RCN1",
+  "RCN2",
+  "RDH11",
+  "REEP5",
+  "REG1A",
+  "RELA",
+  "REPIN1",
+  "RER1",
+  "RERE",
+  "RETREG2",
+  "REXO2",
+  "RGCC",
+  "RGS5",
+  "RHBDD2",
+  "RHOA",
+  "RHOB",
+  "RHOBTB3",
+  "RHOQ",
+  "RHOT2",
+  "RIC8A",
+  "RIDA",
+  "RING1",
+  "RMND5A",
+  "RNASE1",
+  "RNASEK",
+  "RNASET2",
+  "RNF10",
+  "RNF11",
+  "RNF114",
+  "RNF130",
+  "RNF145",
+  "RNF187",
+  "RNF213",
+  "RNH1",
+  "RNPS1",
+  "ROMO1",
+  "RPN1",
+  "RPN2",
+  "RRAD",
+  "RRAS",
+  "RSL1D1",
+  "RSRP1",
+  "RTF2",
+  "RTL8C",
+  "RTN1",
+  "RTN4",
+  "RTRAF",
+  "RUNX1",
+  "RUVBL2",
+  "RWDD1",
+  "RXRA",
+  "S100A1",
+  "S100A10",
+  "S100A11",
+  "S100A13",
+  "S100A14",
+  "S100A16",
+  "S100A2",
+  "S100A4",
+  "S100A6",
+  "S100A8",
+  "S100A9",
+  "S100B",
+  "S100P",
+  "SAFB",
+  "SAFB2",
+  "SAMHD1",
+  "SAP18",
+  "SAR1A",
+  "SAT1",
+  "SAT2",
+  "SBDS",
+  "SCAF11",
+  "SCAMP2",
+  "SCAND1",
+  "SCARB2",
+  "SCD",
+  "SCGB2A2",
+  "SCP2",
+  "SDC1",
+  "SDC2",
+  "SDC3",
+  "SDC4",
+  "SDCBP",
+  "SDF4",
+  "SDHA",
+  "SDHB",
+  "SEC11A",
+  "SEC11C",
+  "SEC13",
+  "SEC31A",
+  "SEC61A1",
+  "SEC61G",
+  "SEC62",
+  "SEL1L",
+  "SELENBP1",
+  "SELENOF",
+  "SELENOH",
+  "SELENOK",
+  "SELENOM",
+  "SELENON",
+  "SELENOP",
+  "SELENOW",
+  "SEM1",
+  "SEPHS2",
+  "SERBP1",
+  "SERF2",
+  "SERINC1",
+  "SERINC2",
+  "SERINC3",
+  "SERP1",
+  "SERPINA1",
+  "SERPINA3",
+  "SERPINB1",
+  "SERPINB6",
+  "SERPINC1",
+  "SERPINE1",
+  "SERPINE2",
+  "SERPINF1",
+  "SERPINF2",
+  "SERPING1",
+  "SET",
+  "SF1",
+  "SF3B1",
+  "SF3B2",
+  "SF3B5",
+  "SF3B6",
+  "SFPQ",
+  "SFRP2",
+  "SFTPB",
+  "SGK1",
+  "SH3BGRL",
+  "SH3BGRL3",
+  "SH3GLB1",
+  "SH3GLB2",
+  "SHISA5",
+  "SIGIRR",
+  "SIVA1",
+  "SLC12A2",
+  "SLC1A2",
+  "SLC1A3",
+  "SLC22A17",
+  "SLC25A1",
+  "SLC25A11",
+  "SLC25A39",
+  "SLC25A4",
+  "SLC2A1",
+  "SLC2A4RG",
+  "SLC38A1",
+  "SLC38A10",
+  "SLC38A2",
+  "SLC39A1",
+  "SLC39A14",
+  "SLC39A6",
+  "SLC39A7",
+  "SLC3A2",
+  "SLC40A1",
+  "SLC44A1",
+  "SLC44A2",
+  "SLC44A4",
+  "SLC45A3",
+  "SLC9A3R1",
+  "SLC9A3R2",
+  "SLIRP",
+  "SLPI",
+  "SLTM",
+  "SMARCA5",
+  "SMARCC1",
+  "SMARCE1",
+  "SMCHD1",
+  "SMDT1",
+  "SMIM26",
+  "SMIM4",
+  "SMS",
+  "SMTN",
+  "SNAP25",
+  "SND1",
+  "SNRNP200",
+  "SNRNP70",
+  "SNRPB",
+  "SNRPC",
+  "SNRPD1",
+  "SNRPE",
+  "SNRPF",
+  "SNRPG",
+  "SNU13",
+  "SNX1",
+  "SNX17",
+  "SNX3",
+  "SOCS3",
+  "SOD1",
+  "SOD2",
+  "SOD3",
+  "SON",
+  "SORBS1",
+  "SORBS2",
+  "SORBS3",
+  "SORL1",
+  "SORT1",
+  "SOX4",
+  "SPAG9",
+  "SPARC",
+  "SPARCL1",
+  "SPATS2L",
+  "SPCS1",
+  "SPCS3",
+  "SPDEF",
+  "SPIN1",
+  "SPINK1",
+  "SPINK4",
+  "SPINT1",
+  "SPINT2",
+  "SPON2",
+  "SPP1",
+  "SPSB3",
+  "SPTAN1",
+  "SPTBN1",
+  "SQOR",
+  "SQSTM1",
+  "SREBF1",
+  "SREBF2",
+  "SRGN",
+  "SRI",
+  "SRM",
+  "SRP9",
+  "SRPRA",
+  "SRRM2",
+  "SRRT",
+  "SRSF1",
+  "SRSF11",
+  "SRSF2",
+  "SRSF3",
+  "SRSF5",
+  "SRSF7",
+  "SRSF9",
+  "SSBP1",
+  "SSBP3",
+  "SSR1",
+  "SSR2",
+  "SSR3",
+  "SSR4",
+  "SSU72",
+  "ST13",
+  "ST14",
+  "ST6GAL1",
+  "STAB1",
+  "STARD10",
+  "STARD7",
+  "STAT1",
+  "STAT2",
+  "STAT3",
+  "STAT6",
+  "STAU1",
+  "STEAP2",
+  "STK25",
+  "STMN1",
+  "STOM",
+  "STOML2",
+  "STRAP",
+  "STT3B",
+  "STUB1",
+  "STX16",
+  "SUCLG1",
+  "SULF1",
+  "SULF2",
+  "SUMF2",
+  "SUMO3",
+  "SUN2",
+  "SUPT5H",
+  "SURF4",
+  "SVIL",
+  "SYAP1",
+  "SYNE2",
+  "SYNGR2",
+  "SYNM",
+  "SYNPO",
+  "SYNPO2",
+  "SYPL1",
+  "SZRD1",
+  "TACC1",
+  "TACSTD2",
+  "TAF10",
+  "TAF15",
+  "TAF7",
+  "TAGLN",
+  "TAGLN2",
+  "TALDO1",
+  "TAP1",
+  "TAPBP",
+  "TAT",
+  "TAX1BP1",
+  "TAX1BP3",
+  "TBC1D9B",
+  "TBCB",
+  "TBL1XR1",
+  "TCAP",
+  "TCEA3",
+  "TCEAL4",
+  "TCF25",
+  "TCF4",
+  "TCP1",
+  "TERF2IP",
+  "TF",
+  "TFF1",
+  "TFF3",
+  "TFG",
+  "TFPI",
+  "TFRC",
+  "TGFBI",
+  "TGFBR2",
+  "TGM2",
+  "TGOLN2",
+  "THBS1",
+  "THBS2",
+  "THOC7",
+  "THRA",
+  "THRAP3",
+  "THY1",
+  "TIMM13",
+  "TIMM8B",
+  "TIMP1",
+  "TIMP2",
+  "TIMP3",
+  "TINAGL1",
+  "TJP1",
+  "TKT",
+  "TLN1",
+  "TM4SF1",
+  "TM9SF2",
+  "TM9SF3",
+  "TMBIM1",
+  "TMBIM4",
+  "TMBIM6",
+  "TMCO1",
+  "TMED10",
+  "TMED2",
+  "TMED4",
+  "TMED9",
+  "TMEM109",
+  "TMEM123",
+  "TMEM134",
+  "TMEM141",
+  "TMEM147",
+  "TMEM14C",
+  "TMEM160",
+  "TMEM165",
+  "TMEM176A",
+  "TMEM176B",
+  "TMEM205",
+  "TMEM219",
+  "TMEM230",
+  "TMEM248",
+  "TMEM256",
+  "TMEM258",
+  "TMEM259",
+  "TMEM30A",
+  "TMEM50A",
+  "TMEM54",
+  "TMEM59",
+  "TMEM63A",
+  "TMEM9",
+  "TMPRSS2",
+  "TMSB4X",
+  "TMX2",
+  "TMX4",
+  "TNC",
+  "TNFRSF12A",
+  "TNFRSF1A",
+  "TNFSF10",
+  "TNIP1",
+  "TNNC1",
+  "TNNI3",
+  "TNNT2",
+  "TNPO1",
+  "TNS1",
+  "TNXB",
+  "TOB1",
+  "TOLLIP",
+  "TOMM20",
+  "TOMM7",
+  "TOP1",
+  "TOP2B",
+  "TP53I11",
+  "TPD52",
+  "TPD52L2",
+  "TPM1",
+  "TPM2",
+  "TPP1",
+  "TPPP3",
+  "TRA2A",
+  "TRA2B",
+  "TRAM1",
+  "TRAP1",
+  "TRAPPC1",
+  "TRAPPC5",
+  "TRIM2",
+  "TRIM28",
+  "TRIM29",
+  "TRIM8",
+  "TRIOBP",
+  "TRIP12",
+  "TRIP6",
+  "TRIR",
+  "TRMT112",
+  "TRPM4",
+  "TSC22D1",
+  "TSC22D3",
+  "TSC22D4",
+  "TSPAN1",
+  "TSPAN13",
+  "TSPAN3",
+  "TSPAN4",
+  "TSPAN7",
+  "TSPAN8",
+  "TSPO",
+  "TSPYL1",
+  "TST",
+  "TSTA3",
+  "TSTD1",
+  "TTC3",
+  "TTN",
+  "TTR",
+  "TUBA1B",
+  "TUBA4A",
+  "TUBB2A",
+  "TUBB6",
+  "TUFM",
+  "TXN2",
+  "TXNDC17",
+  "TXNDC5",
+  "TXNIP",
+  "TXNL4A",
+  "TYMP",
+  "TYROBP",
+  "UBA1",
+  "UBA52",
+  "UBB",
+  "UBC",
+  "UBE2B",
+  "UBE2D2",
+  "UBE2E3",
+  "UBE2G2",
+  "UBE2H",
+  "UBE2I",
+  "UBE2L3",
+  "UBE2L6",
+  "UBE2Q1",
+  "UBE2R2",
+  "UBE2V1",
+  "UBL3",
+  "UBL5",
+  "UBQLN1",
+  "UBTF",
+  "UBXN1",
+  "UBXN4",
+  "UBXN6",
+  "UCHL1",
+  "UFC1",
+  "UGDH",
+  "UGP2",
+  "UQCC2",
+  "UQCC3",
+  "UQCR11",
+  "UQCRB",
+  "UQCRC1",
+  "UQCRC2",
+  "UQCRFS1",
+  "UQCRQ",
+  "USF2",
+  "USP22",
+  "USP7",
+  "UXT",
+  "VAMP2",
+  "VAMP5",
+  "VAMP8",
+  "VAPA",
+  "VASP",
+  "VAT1",
+  "VCAN",
+  "VCL",
+  "VCP",
+  "VDAC1",
+  "VDAC2",
+  "VDAC3",
+  "VEGFB",
+  "VIM",
+  "VKORC1",
+  "VMP1",
+  "VOPP1",
+  "VPS28",
+  "VPS29",
+  "VPS4A",
+  "VSNL1",
+  "VTN",
+  "VWA1",
+  "VWF",
+  "WAC",
+  "WASF2",
+  "WBP2",
+  "WDR1",
+  "WDR13",
+  "WDR26",
+  "WDR45B",
+  "WDR6",
+  "WDR82",
+  "WDR83OS",
+  "WFDC2",
+  "WFS1",
+  "WLS",
+  "WNK1",
+  "WSB1",
+  "WSB2",
+  "XBP1",
+  "XIRP1",
+  "XRCC5",
+  "XRCC6",
+  "YBX1",
+  "YIPF3",
+  "YIPF4",
+  "YME1L1",
+  "YPEL3",
+  "YPEL5",
+  "YWHAB",
+  "YWHAE",
+  "YWHAG",
+  "YWHAH",
+  "YWHAQ",
+  "YY1",
+  "ZBTB7A",
+  "ZEB2",
+  "ZFP36",
+  "ZFP36L1",
+  "ZFP36L2",
+  "ZKSCAN1",
+  "ZMAT2",
+  "ZMIZ1",
+  "ZMIZ2",
+  "ZNF106",
+  "ZNF207",
+  "ZNF358",
+  "ZNF706",
+  "ZRANB2",
+  "ZYX"
+ ],
+ "c_mv": 0.2476593255996704,
+ "split": "fold0 of splits/patient_5fold (ORION), splits/final/hest_fold0, tcga_fold0; test held out",
+ "sizes": {
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+   "val": 187,
+   "test": 692
+  },
+  "hest": {
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+   "val": 546,
+   "test": 1896
+  },
+  "tcga_text": {
+   "train": 4392,
+   "val": 500,
+   "test": 1223
+  }
+ },
+ "stage1_val_R@1": {
+  "mif": 0.5347594022750854,
+  "rna:hvg": 0.044871795922517776,
+  "rna:tahoex1": 0.049450550228357315,
+  "rna:se600m": 0.03846153989434242,
+  "rna:aidocell": 0.053113553673028946,
+  "text:keep": 0.09791667014360428,
+  "text:biomedclip": 0.08020833879709244,
+  "text:qwen3-0.6b": 0.09375
+ },
+ "es_steps": [
+  700,
+  150,
+  150
+ ],
+ "seeds": [
+  0,
+  1000,
+  2000
+ ],
+ "anchor": "UNI2-h CLS (1536-d), frozen",
+ "image_extra": "MedVTok feats (1152-d), frozen",
+ "mif_markers": "embed.MIF_MARKERS",
+ "rna_encoders": [
+  "hvg",
+  "tahoex1",
+  "se600m",
+  "aidocell"
+ ],
+ "text_encoders": [
+  "keep",
+  "biomedclip",
+  "qwen3-0.6b"
+ ]
+}

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+<header>
+  <div class="eyebrow">ImageBind-style · H&amp;E / mIF / RNA / text · 最终结果与独立复现 · 2026-10-30</div>
+  <h1>四模态病理嵌入模型</h1>
+  <p class="lede col">把 H&amp;E 图像、多重免疫荧光（mIF，蛋白）、空间转录组（RNA）和病理文本放进同一个 1536 维空间。
+  锚点是冻结的 UNI2-h 图像空间；所有模态只用真实配对数据训练，虚拟和合成数据只用于评估。
+  最终模型（EJ-ad+MV，3 种子适配器平均）已训练完成，并提供从原始输入直接生成嵌入的接口 <code>embed.py</code>。
+  2026-10-29 又在独立 A800 环境中完成了发布模型评估、fold 0 重训、5 折重训和 release 重训，全部复现检查通过。</p>
+  <nav class="toc" aria-label="目录">
+    <a href="#setup">设定与数据</a><a href="#model">最终模型</a><a href="#results">结果</a><a href="#reproduction">独立复现</a><a href="#findings">主要发现</a>
+    <a href="#encoders">编码器选择</a><a href="#virtual">虚拟模态</a><a href="#limits">局限</a><a href="#usage">使用方法</a><a href="#files">文件</a>
+  </nav>
+</header>
+
+<section id="setup">
+<h2>设定与数据</h2>
+<div class="col">
+<p>没有任何数据集同时测量四种模态，所以采用 ImageBind 的思路：每个模态只和 H&amp;E 配对训练，H&amp;E 以外的模态两两之间的对齐是“涌现”出来的。</p>
+<ul>
+  <li><b>训练配对只用真实数据：</b>ORION 结直肠癌（H&amp;E–mIF）、HEST-1k Visium（H&amp;E–RNA）、TCGA/PathGen（H&amp;E–文本）。</li>
+  <li><b>划分：</b>按病人（HEST 按研究|病人组）分成 train/val/test，5 折交叉验证；val 只用于早停，所有数字都是 test 上的。</li>
+  <li><b>虚拟和合成数据只用于测试：</b>STPath 虚拟 RNA、MIPHEI 虚拟 mIF、GPT 合成描述。它们只用来给“没有真实配对”的模态对构建测试集。</li>
+  <li><b>指标：</b>100 个样本的检索库里的 R@1（双向平均，随机水平 0.01），抽 50 次取平均；配对准确率是同一 100 库里的一对一匈牙利匹配（随机水平 0.01）。</li>
+</ul>
+</div>
+<div class="tbl">
+<table>
+  <thead><tr><th>数据集</th><th>配对</th><th>规模</th><th>用途</th></tr></thead>
+  <tbody>
+    <tr><td>ORION CRC</td><td>H&amp;E – mIF（16 个标记）</td><td class="mono">3,187 图块 · 约 40 名病人</td><td>训练 + 测试</td></tr>
+    <tr><td>HEST-1k Visium</td><td>H&amp;E – RNA（14,802 基因）</td><td class="mono">9,484 spots · 57 项研究 · 16 器官</td><td>训练 + 测试</td></tr>
+    <tr><td>TCGA / PathGen-1.6M</td><td>H&amp;E – 文本</td><td class="mono">6,144 图像 · 6,115 条清洗后文本</td><td>训练 + 测试</td></tr>
+    <tr><td>STPath / MIPHEI / GPT 描述</td><td>虚拟 RNA、虚拟 mIF、合成文本</td><td class="mono">ORION、TCGA 测试图块</td><td>只用于测试</td></tr>
+    <tr><td>DLPFC（spatialLIBD）</td><td>H&amp;E – RNA（脑）</td><td class="mono">482 spots · 3 名供体</td><td>外部测试</td></tr>
+  </tbody>
+</table>
+</div>
+</section>
+
+<section id="model">
+<h2>最终模型</h2>
+<div class="col">
+<p>两阶段训练。第一阶段给每个编码器单独训练一个映射头，映射到冻结的 UNI2 空间。第二阶段冻结所有映射头，只训练一个 H&amp;E 残差适配器，它同时读 UNI2 和 MedVTok 的特征。</p>
+</div>
+<div class="flow" role="img" aria-label="模型结构：四种模态各自经编码器和映射头进入 1536 维共享空间">
+<div class="row he"><div class="b in">H&amp;E 图像</div><div class="ar">→</div><div class="b">UNI2-h（冻结）<br>+ MedVTok（冻结）</div><div class="ar">→</div><div class="b">UNI2 + 残差适配器<small>3 个种子取平均</small></div><div class="ar">→</div><div class="b z">1536 维共享空间</div></div>
+<div class="row "><div class="b in">mIF 图块</div><div class="ar">→</div><div class="b">VirTues<small>16 个标志物</small></div><div class="ar">→</div><div class="b">MLP 头</div><div class="ar">→</div><div class="b z">1536 维共享空间</div></div>
+<div class="row "><div class="b in">RNA 计数</div><div class="ar">→</div><div class="b">hvg · Tahoe-x1<br>SE-600M · AIDO.Cell</div><div class="ar">→</div><div class="b">4 个线性头<small>后期融合</small></div><div class="ar">→</div><div class="b z">1536 维共享空间</div></div>
+<div class="row "><div class="b in">文本</div><div class="ar">→</div><div class="b">KEEP · BiomedCLIP<br>Qwen3-Emb-0.6B</div><div class="ar">→</div><div class="b">3 个线性头<small>后期融合</small></div><div class="ar">→</div><div class="b z">1536 维共享空间</div></div>
+</div>
+<div class="col">
+<ul>
+  <li><b>第一阶段：</b>每个映射头用 InfoNCE 对齐冻结的 UNI2（文本是多正样本 InfoNCE，同一图像的多条文本都算正样本）。RNA 和文本是后期融合：<code>z = normalise(Σ normalise(head_e(x_e)))</code>。</li>
+  <li><b>第二阶段：</b>只训练 H&amp;E 适配器和温度参数：<code>H&amp;E = UNI2 + mean_s A_s([UNI2, c·MedVTok])</code>。损失是三种配对损失之和加上对 UNI2 相似度结构的蒸馏（λ=1），学习率 1e-4，1000 步，按验证集三种 R@1 的几何平均早停。用 3 个随机种子各训练一个适配器，取平均。</li>
+  <li><b>后果：</b>mIF、RNA、文本的嵌入和第一阶段完全一样，所以涌现配对不受第二阶段影响；只有 H&amp;E 这一侧变好。</li>
+  <li><b>发布版：</b><code>models/ej_ad_mv/</code>，用 fold 0 的 train + test 训练（ORION 3,000 图块、HEST 8,938 spots、TCGA 5,615 条文本），fold 0 的 val 用于早停。它没有自己的测试集，预期性能就是下面的 5 折交叉验证结果。</li>
+</ul>
+</div>
+</section>
+
+<section id="results">
+<h2>结果</h2>
+<h3>最终模型，5 折测试集</h3>
+<div class="tbl">
+<table>
+  <thead><tr><th>配对</th><th>类型</th><th>数据集</th><th class="n">R@1</th><th class="n">R@10</th><th class="n">配对准确率</th></tr></thead>
+  <tbody>
+    <tr><td>H&amp;E ↔ mIF</td><td><span class="kind trained">训练</span></td><td>ORION</td><td class="n">0.801 ± 0.043</td><td class="n">0.991</td><td class="n">0.942</td></tr>
+    <tr><td>H&amp;E ↔ RNA</td><td><span class="kind trained">训练</span></td><td>HEST</td><td class="n">0.203 ± 0.033</td><td class="n">0.625</td><td class="n">0.258</td></tr>
+    <tr><td>H&amp;E ↔ 文本</td><td><span class="kind trained">训练</span></td><td>TCGA</td><td class="n">0.323 ± 0.007</td><td class="n">0.813</td><td class="n">0.347</td></tr>
+    <tr><td>mIF ↔ RNA（虚拟）</td><td><span class="kind emergent">涌现</span></td><td>ORION</td><td class="n">0.141 ± 0.007</td><td class="n">0.657</td><td class="n">0.194</td></tr>
+    <tr><td>mIF ↔ 文本（合成）</td><td><span class="kind emergent">涌现</span></td><td>ORION</td><td class="n">0.089 ± 0.008</td><td class="n">0.491</td><td class="n">0.104</td></tr>
+    <tr><td>文本 ↔ RNA（虚拟）</td><td><span class="kind emergent">涌现</span></td><td>TCGA</td><td class="n">0.095 ± 0.006</td><td class="n">0.436</td><td class="n">0.100</td></tr>
+    <tr><td>文本 ↔ mIF（MIPHEI 虚拟）</td><td><span class="kind emergent">涌现</span></td><td>TCGA</td><td class="n">0.046 ± 0.005</td><td class="n">0.271</td><td class="n">0.051</td></tr>
+    <tr><td>H&amp;E ↔ RNA</td><td><span class="kind virtual">外部</span></td><td>DLPFC（脑）</td><td class="n">0.012</td><td class="n">0.112</td><td class="n">0.012</td></tr>
+  </tbody>
+</table>
+</div>
+<p class="note col">随机水平：R@1 0.01，R@10 0.10，配对准确率 0.01。涌现配对的一侧是虚拟或合成数据，这些数据本身有误差，所以数值偏保守。DLPFC 是第一阶段（E）的结果；第二阶段不改变 RNA 侧。</p>
+
+<h3>各阶段的提升（训练配对 R@1，5 折均值）</h3>
+<div class="panels" id="chart"></div>
+<div class="legend" aria-hidden="true">
+  <span style="--c: var(--steel)">单编码器（S4）</span>
+  <span style="--c: var(--eosin)">多编码器融合（E）</span>
+  <span style="--c: color-mix(in srgb, var(--hema) 55%, var(--bg))">+ H&amp;E 适配器 / + MedVTok</span>
+  <span style="--c: var(--hema)">最终（3 种子平均）</span>
+</div>
+
+<h3>涌现配对（R@1）</h3>
+<div class="tbl">
+<table>
+  <thead><tr><th>阶段</th><th class="n">mIF↔RNA（虚拟）</th><th class="n">mIF↔文本（合成）</th><th class="n">文本↔RNA（虚拟）</th><th class="n">文本↔mIF（虚拟）</th></tr></thead>
+  <tbody>
+    <tr><td>单编码器，单独训练（S4）</td><td class="n">0.122</td><td class="n">0.076</td><td class="n">0.069</td><td class="n">0.038</td></tr>
+    <tr><td>单编码器，联合微调所有头（J8）</td><td class="n">0.122</td><td class="n">0.073</td><td class="n">0.065</td><td class="n">0.035</td></tr>
+    <tr><td>多编码器融合（E）</td><td class="n">0.141</td><td class="n">0.089</td><td class="n">0.095</td><td class="n">0.046</td></tr>
+    <tr><td>融合 + 联合微调 mIF 头（EJ-frz）</td><td class="n">0.134</td><td class="n">0.087</td><td class="n">0.095</td><td class="n">0.042</td></tr>
+    <tr class="final"><td>最终：只训练 H&amp;E 适配器</td><td class="n">0.141</td><td class="n">0.089</td><td class="n">0.095</td><td class="n">0.046</td></tr>
+  </tbody>
+</table>
+</div>
+</section>
+
+<section id="reproduction">
+<h2>独立复现：发布结果可重现</h2>
+<div class="col">
+<p><strong>总体结论：</strong>在 cuipeng 服务器的一张 NVIDIA A800-SXM4-80GB 上，从发布的编码器特征重新执行完整的 <code>reproduce.sh</code>。流程包括评估已发布 fold-0 checkpoint、重训 fold 0、重训 5 折、逐项比较发布结果，以及用 fold-0 train + test 重训 release 模型。任务最终状态为 <strong class="ok">Success</strong>，日志给出 <code>REPRODUCED within tolerance</code> 和 <code>FOURMODAL_REPRODUCTION_COMPLETE</code>。</p>
+<ul>
+  <li><b>环境：</b>Python 3.12.1、PyTorch 2.7.1+cu128、CUDA 12.8、NumPy 2.4.6、Pandas 2.3.3、SciPy 1.16.3。</li>
+  <li><b>数据检查：</b>26 个特征数组，共 0.933 GiB；全部可读取、非空且无 NaN/Inf；三组数据的 5 折划分完整。</li>
+  <li><b>发布模型检查：</b>重新评估发布 fold-0 模型，7 个模态对与随模型发布的 <code>test.csv</code> 最大 R@1 差异为 0.0001。</li>
+</ul>
+</div>
+
+<h3>fold 0 重训：留出测试集</h3>
+<div class="tbl">
+<table>
+  <thead><tr><th>模态对</th><th class="n">本次重训 R@1</th><th class="n">发布 R@1</th><th class="n">绝对差异</th><th>复现检查</th></tr></thead>
+  <tbody>
+    <tr><td>H&amp;E ↔ mIF（ORION）</td><td class="n">0.7608</td><td class="n">0.7834</td><td class="n">0.0226</td><td class="ok">通过</td></tr>
+    <tr><td>H&amp;E ↔ RNA（HEST）</td><td class="n">0.1853</td><td class="n">0.1917</td><td class="n">0.0064</td><td class="ok">通过</td></tr>
+    <tr><td>H&amp;E ↔ 文本（TCGA）</td><td class="n">0.3240</td><td class="n">0.3203</td><td class="n">0.0037</td><td class="ok">通过</td></tr>
+    <tr><td>mIF ↔ RNA（虚拟，ORION）</td><td class="n">0.1358</td><td class="n">0.1352</td><td class="n">0.0006</td><td class="ok">通过</td></tr>
+    <tr><td>mIF ↔ 文本（合成，ORION）</td><td class="n">0.0978</td><td class="n">0.0987</td><td class="n">0.0009</td><td class="ok">通过</td></tr>
+    <tr><td>文本 ↔ RNA（虚拟，TCGA）</td><td class="n">0.0999</td><td class="n">0.1000</td><td class="n">0.0001</td><td class="ok">通过</td></tr>
+    <tr><td>文本 ↔ mIF（MIPHEI，TCGA）</td><td class="n">0.0484</td><td class="n">0.0491</td><td class="n">0.0007</td><td class="ok">通过</td></tr>
+  </tbody>
+</table>
+</div>
+
+<h3>5 折重训：最终 <code>ens-es</code> 规则</h3>
+<div class="tbl">
+<table>
+  <thead><tr><th>模态对</th><th class="n">本次 5 折 R@1</th><th class="n">发布 R@1</th><th class="n">绝对差异</th><th>复现检查</th></tr></thead>
+  <tbody>
+    <tr><td>H&amp;E ↔ mIF（ORION）</td><td class="n">0.7967</td><td class="n">0.8010</td><td class="n">0.0042</td><td class="ok">通过</td></tr>
+    <tr><td>H&amp;E ↔ RNA（HEST）</td><td class="n">0.2021</td><td class="n">0.2030</td><td class="n">0.0009</td><td class="ok">通过</td></tr>
+    <tr><td>H&amp;E ↔ 文本（TCGA）</td><td class="n">0.3231</td><td class="n">0.3232</td><td class="n">0.0001</td><td class="ok">通过</td></tr>
+    <tr><td>mIF ↔ RNA（虚拟，ORION）</td><td class="n">0.1414</td><td class="n">0.1414</td><td class="n">0.0000</td><td class="ok">通过</td></tr>
+    <tr><td>mIF ↔ 文本（合成，ORION）</td><td class="n">0.0885</td><td class="n">0.0887</td><td class="n">0.0001</td><td class="ok">通过</td></tr>
+    <tr><td>文本 ↔ RNA（虚拟，TCGA）</td><td class="n">0.0966</td><td class="n">0.0953</td><td class="n">0.0013</td><td class="ok">通过</td></tr>
+    <tr><td>文本 ↔ mIF（MIPHEI，TCGA）</td><td class="n">0.0464</td><td class="n">0.0465</td><td class="n">0.0001</td><td class="ok">通过</td></tr>
+  </tbody>
+</table>
+</div>
+<p class="note col">所有 fold-0 和 5 折对比均落在发布代码预定义的容差内。最终还生成并独立加载验证了 <code>models/repro_fold0/model.pt</code>、<code>models/repro_release/model.pt</code> 和三张 <code>final_cv_*_repro.csv</code>。本次���行的是特征级复现；没有执行可选的 <code>RAW=1</code> 原始输入编码器检查。</p>
+</section>
+
+<section id="findings">
+<h2>主要发现</h2>
+<ol class="findings col">
+  <li><div><b>UNI2-h 是最好的冻结锚点。</b>在 mIF、RNA、文本三种训练配对上都没有被显著超过；GigaPath 接近（RNA 差 0.035），CONCH 在 H&amp;E↔mIF 上低 0.155。MedVTok 当锚点也更差（H&amp;E↔RNA 0.131 对 0.192）。</div></li>
+  <li><div><b>多编码器后期融合是最大的单项提升。</b>RNA 用 4 个编码器、文本用 3 个，H&amp;E↔RNA +0.037、H&amp;E↔文本 +0.062，4 个涌现配对也全部提升（5/5 折）。拼接（早期融合）和同一编码器多种子平均都达不到这个效果，说明这些编码器是互补的。</div></li>
+  <li><div><b>联合训练要只动 H&amp;E 一侧。</b>从头训练共享的 H&amp;E 头会让 H&amp;E↔mIF 变好，但涌现配对损失 26–74%。冻结所有模态头、只训练零初始化的残差适配器，H&amp;E↔mIF +0.10，涌现配对完全不变。</div></li>
+  <li><div><b>MedVTok 作为适配器的额外输入有效，作为锚点无效。</b>额外输入使 H&amp;E↔mIF +0.015、H&amp;E↔文本 +0.016。换成同尺寸的 UNI2 随机投影就没有提升，说明增益来自 MedVTok 的信息而不是参数量。</div></li>
+  <li><div><b>第二阶段的早停不稳定，3 个种子平均解决了这个问题。</b>验证曲线在 100 步后基本是平的，单次早停选中的步数在 100–900 之间波动，同一设置重跑 H&amp;E↔mIF 可以差 0.05。3 个早停适配器取平均后，H&amp;E↔文本比单种子再 +0.015（5/5 折，p=0.02），也是三种规则里几何平均最高的。</div></li>
+  <li><div><b>线性头比 MLP 头更适合 RNA 和文本。</b>训练配对持平，涌现配对 +5%；mIF 保留 MLP 头。</div></li>
+  <li><div><b>用虚拟配对直接训练不如走锚点的涌现路线。</b>文本↔蛋白在真实 mIF 上 0.596 对 0.678（AUROC）。所以虚拟数据只用作测试，从不进入训练。</div></li>
+  <li><div><b>实例级的涌现对齐仍然弱。</b>mIF↔RNA 0.141 是随机水平的 14 倍，但比训练配对低一个数量级；概念级对齐（AUROC 0.6–0.7）更可靠。</div></li>
+</ol>
+</section>
+
+<section id="encoders">
+<h2>编码器选择</h2>
+<div class="tbl">
+<table>
+  <thead><tr><th>模态</th><th>最终使用</th><th>依据（5 折配对检验）</th></tr></thead>
+  <tbody>
+    <tr><td>H&amp;E</td><td>UNI2-h + MedVTok（只进适配器）</td><td>UNI2 在所有训练配对上不被显著超过；MedVTok 额外输入 mIF +0.015、文本 +0.016</td></tr>
+    <tr><td>mIF</td><td>VirTues（16 标记）+ MLP 头</td><td>从头训练的 ConvNeXt-T 在 H&amp;E↔mIF 上高 0.03，但 VirTues 的跨模态迁移好得多（mIF↔markers 0.66 对 0.48），且不绑定固定标记面板</td></tr>
+    <tr><td>RNA</td><td>hvg + Tahoe-x1 + SE-600M + AIDO.Cell，各一个线性头</td><td>单个基础模型最多 +0.016；4 个融合 +0.037，接近 10 个融合（+0.044）</td></tr>
+    <tr><td>文本</td><td>KEEP + BiomedCLIP + Qwen3-Emb-0.6B，各一个线性头</td><td>KEEP 单个最好（0.278）；3 个融合 0.299，接近 5 个融合（0.303）</td></tr>
+  </tbody>
+</table>
+</div>
+</section>
+
+<section id="virtual">
+<h2>虚拟模态（只用于评估）</h2>
+<div class="col">
+<p>每种虚拟模态先做校准：在有真实数据的同一批样本上，用虚拟数据替换真实数据，看配对结果是否接近。</p>
+</div>
+<div class="tbl">
+<table>
+  <thead><tr><th>虚拟模态</th><th>校准（真实 → 虚拟，同一批样本）</th><th>结论</th></tr></thead>
+  <tbody>
+    <tr><td>STPath 虚拟 RNA</td><td>HEST H&amp;E↔RNA 0.148 → 0.126；STPath 未见过的样本 0.086 → 0.080</td><td class="ok">可用</td></tr>
+    <tr><td>GPT 合成描述</td><td>TCGA H&amp;E↔文本 0.219 → 0.162（约 0.75 倍）</td><td class="ok">可用，偏保守</td></tr>
+    <tr><td>MIPHEI 虚拟 mIF</td><td>ORION 未见过的测试图块：配对准确率 0.92 → 0.55（约 0.6 倍）</td><td class="ok">可用</td></tr>
+    <tr><td>GigaTIME 虚拟 mIF</td><td>ORION H&amp;E↔mIF 0.644 → 0.038</td><td class="bad">不可用，已弃用</td></tr>
+  </tbody>
+</table>
+</div>
+</section>
+
+<section id="limits">
+<h2>局限</h2>
+<ul class="col">
+  <li><b>外部泛化差：</b>脑组织 DLPFC 上所有非循环配对都在随机水平（H&amp;E↔RNA 0.012）。训练集 HEST 里脑组织也只有 0.021。模型目前适用于训练数据覆盖的组织类型。</li>
+  <li><b>H&amp;E↔文本的 MedVTok 增益可能偏高：</b>MedVTok 的预训练图像包含 PathGen 1.6M，见过我们的 TCGA 测试图像（只有图像，没有文本）。ORION 上的 mIF 增益不受影响。</li>
+  <li><b>验证集小：</b>ORION 每折只有 187–276 个验证图块，所以第二阶段用了 3 种子平均来降低早停的随机性。</li>
+  <li><b>涌现配对的测试数据一侧是虚拟或合成的，</b>数值是保守估计，不是真实数据上的精确值。</li>
+  <li><b>新数据的 RNA 批次效应：</b>默认用 HEST 训练集的统计量做标准化；新平台或新实验室的数据建议用 <code>zscore="self"</code>（外部测试就是这样做的）。</li>
+</ul>
+</section>
+
+<section id="usage">
+<h2>使用方法</h2>
+<div class="col">
+<p>运行环境：<code>.venv/bin/python -I</code>，需要 GPU。所有输出都是 L2 归一化的 (N, 1536) 向量，相似度就是点积。</p>
+</div>
+<pre class="code">from embed import Embedder
+E = Embedder("models/ej_ad_mv")                 # 发布版模型
+
+z_he  = E.he(images)                            # H&amp;E 图块：PIL 图像或 (N,H,W,3) uint8；约 0.5 µm/px，112–166 µm 视野
+z_txt = E.text(["Tumor cells with ...", ...])
+z_rna = E.rna(counts, genes, zscore="train")    # 原始计数（spots × 基因）+ HGNC 基因名；新数据集可用 zscore="self"
+z_mif = E.mif(tiles, slide)                     # (N,16,H,W) mIF 图块，通道顺序 = embed.MIF_MARKERS，8 位强度；附每个图块的切片 ID
+
+sim = z_he @ z_rna.T                            # 跨模态相似度
+# 已有特征时：E.he_from_feats(uni2, medvtok)、E.mif_from_feats(virtues)、E.rna_from_feats({...})、E.text_from_feats({...})</pre>
+
+<h3>接口验证（<code>53_embed_check.py</code>）</h3>
+<div class="col"><p>从原始像素、字符串和计数矩阵出发，用 <code>embed.py</code> 重新计算特征，和训练时缓存的特征逐项比较；再用 fold 0 模型在留出测试集上做端到端检索。</p></div>
+<div class="tbl">
+<table>
+  <thead><tr><th>检查</th><th>结果</th></tr></thead>
+  <tbody>
+    <tr><td>UNI2-h、MedVTok（ORION、PathGen、HEST 图像）</td><td class="mono">余弦中位数 1.0000，最低 ≥ 0.9997</td></tr>
+    <tr><td>KEEP、BiomedCLIP、Qwen3（TCGA 文本）</td><td class="mono">中位数 1.0000 / 1.0000 / 0.9998（BiomedCLIP 个别 0.93，bf16 批次差异）</td></tr>
+    <tr><td>hvg、AIDO.Cell / Tahoe-x1、SE-600M（HEST）</td><td class="mono">1.0000 / 0.991、0.994（后两者按官方做法随机采样基因）</td></tr>
+    <tr><td>VirTues（全部 3,187 个 ORION 图块）</td><td class="mono">中位数 1.0000，最低 1.0000</td></tr>
+    <tr><td>端到端 R@1：原始输入 vs 缓存特征</td><td class="mono">mIF 0.792 / 0.792 · RNA 0.194 / 0.194 · 文本 0.335 / 0.336</td></tr>
+  </tbody>
+</table>
+</div>
+
+</section>
+
+<section id="files">
+<h2>文件</h2>
+<div class="tbl">
+<table>
+  <thead><tr><th>路径</th><th>内容</th></tr></thead>
+  <tbody>
+    <tr><td><code>embed.py</code></td><td>推理接口（Embedder、Bind4）</td></tr>
+    <tr><td><code>52_final_model.py</code></td><td>最终模型训练：<code>cv</code>（选择规则）、<code>fold0</code>、<code>release</code></td></tr>
+    <tr><td><code>53_embed_check.py</code></td><td>原始输入验证，结果在 <code>results/embed_check.csv</code></td></tr>
+    <tr><td><code>models/ej_ad_mv/</code></td><td>发布版模型：<code>model.pt</code>（77 MB，含标准化统计量）、<code>meta.json</code>、验证曲线</td></tr>
+    <tr><td><code>models/ej_ad_mv_fold0/</code></td><td>fold 0 模型及其留出测试结果 <code>test.csv</code></td></tr>
+    <tr><td><code>results/final_cv_*.csv</code></td><td>5 折 × 3 种子的选择规则实验</td></tr>
+    <tr><td><code>RESULTS.md</code></td><td>全部实验的完整记录（01_–53_）</td></tr>
+  </tbody>
+</table>
+</div>
+</section>
+</div>
+
+<script>
+(function () {
+  // Trained-pair R@1, 5-fold means (RESULTS.md: 48_ S4 / E, 51_ EJ-ad / EJ-ad+MV, 52_ cv ens-es)
+  var stages = ["单编码器 S4", "多编码器融合 E", "+ H&E 适配器", "+ MedVTok", "最终（3 种子）"];
+  var colors = ["var(--steel)", "var(--eosin)", "color-mix(in srgb, var(--hema) 55%, var(--bg))",
+                "color-mix(in srgb, var(--hema) 55%, var(--bg))", "var(--hema)"];
+  var pairs = [
+    { name: "H&E ↔ mIF（ORION）", max: 1.0, ticks: [0, 0.25, 0.5, 0.75, 1.0], v: [0.675, 0.675, 0.776, 0.792, 0.801] },
+    { name: "H&E ↔ RNA（HEST）", max: 0.25, ticks: [0, 0.05, 0.1, 0.15, 0.2, 0.25], v: [0.155, 0.192, 0.201, 0.200, 0.203] },
+    { name: "H&E ↔ 文本（TCGA）", max: 0.35, ticks: [0, 0.1, 0.2, 0.3], v: [0.236, 0.299, 0.299, 0.315, 0.323] }
+  ];
+  var NS = "http://www.w3.org/2000/svg";
+  var W = 320, labelW = 104, valW = 40, rowH = 26, top = 6, axisH = 22;
+  var plotW = W - labelW - valW;
+  var H = top + stages.length * rowH + axisH;
+  function el(n, a, t) { var e = document.createElementNS(NS, n); for (var k in a) e.setAttribute(k, a[k]); if (t != null) e.textContent = t; return e; }
+  var host = document.getElementById("chart");
+  pairs.forEach(function (p) {
+    var div = document.createElement("div"); div.className = "panel";
+    var h = document.createElement("h4"); h.textContent = p.name; div.appendChild(h);
+    var svg = el("svg", { viewBox: "0 0 " + W + " " + H, role: "img", "aria-label": p.name + " R@1: " + stages.map(function (s, i) { return s + " " + p.v[i].toFixed(3); }).join("，") });
+    var x = function (v) { return labelW + v / p.max * plotW; };
+    p.ticks.forEach(function (t) {
+      svg.appendChild(el("line", { x1: x(t), x2: x(t), y1: top, y2: top + stages.length * rowH, stroke: "var(--rule)", "stroke-width": 1 }));
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+      var y = top + i * rowH;
+      svg.appendChild(el("text", { x: labelW - 8, y: y + rowH / 2 + 4, "text-anchor": "end", "font-size": 11, fill: "var(--fg)" }, s));
+      svg.appendChild(el("rect", { x: labelW, y: y + 5, width: x(p.v[i]) - labelW, height: rowH - 10, rx: 2, fill: colors[i] }));
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+    });
+    div.appendChild(svg); host.appendChild(div);
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+})();
+</script>
+
+</body>
+</html>

reproduce.sh

@@ -0,0 +1,30 @@
+#!/usr/bin/env bash
+# Reproduce the final model from the cached encoder features (GPU, ~20 min on one RTX A5000).
+#
+#   PYTHON=python bash reproduce.sh            # feature-level checks + retraining (no frozen encoders needed)
+#   RAW=1 PYTHON=python bash reproduce.sh      # + raw-input check of embed.py (run setup_encoders.sh first)
+#
+# Steps
+#   0. download cache/ + splits/ (features of the real paired data + virtual / synthetic test data, ~1.1 GB)
+#      from the dataset repo Pathstudy/fourmodal-pathology-features (skipped if present)
+#   1. evaluate_saved.py: shipped fold-0 checkpoint on its held-out test -> must equal models/ej_ad_mv_fold0/test.csv
+#   2. retrain fold 0 (models/repro_fold0) and the 5-fold CV (results/final_cv_*_repro.csv), compare with the shipped
+#      numbers (compare_reproduction.py); shipped checkpoints / results are not overwritten
+#   3. retrain the release model (models/repro_release; train = fold-0 train + test, val = fold-0 val)
+#   4. (RAW=1) example_check.py: raw images / text / counts / mIF tiles in examples/ -> embed.py
+set -euo pipefail
+cd "$(dirname "$0")"
+PY=${PYTHON:-python}
+
+if [ ! -f cache/he_uni2.npy ]; then
+  "$PY" -I -c "from huggingface_hub import snapshot_download as s; s('Pathstudy/fourmodal-pathology-features', repo_type='dataset', local_dir='.', allow_patterns=['cache/*', 'splits/*'])"
+fi
+"$PY" -I evaluate_saved.py models/ej_ad_mv_fold0
+"$PY" -I 52_final_model.py fold0 --out repro_fold0
+"$PY" -I 52_final_model.py cv --out repro
+"$PY" -I compare_reproduction.py repro
+"$PY" -I 52_final_model.py release --out repro_release
+if [ "${RAW:-0}" = 1 ]; then
+  "$PY" -I example_check.py models/ej_ad_mv_fold0
+fi
+echo "reproduce.sh: all steps finished"

requirements.txt

@@ -0,0 +1,17 @@
+# Python 3.11, CUDA GPU. Versions the released model / features were produced with (torch 2.7.1 + CUDA 12.x).
+torch==2.7.1
+torchvision==0.22.1
+numpy==2.4.6
+pandas==2.3.3
+scipy==1.16.3
+huggingface-hub==0.36.0
+safetensors==0.6.2
+timm==1.0.30
+transformers==4.57.1
+tokenizers==0.22.1
+einops==0.8.1
+loguru==0.7.3
+pyyaml==6.0.3
+pillow==12.0.0
+tifffile==2026.3.3
+imagecodecs==2026.3.6

results/anchor_ifret.csv

@@ -0,0 +1,73 @@
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results/anchor_text_probes.csv

@@ -0,0 +1,841 @@
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results/before_text_clean/external_check.csv

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