feat: add latest data and fix plots

Dockerfile

@@ -1,6 +1,5 @@
 FROM python:3.13.5-slim
 
-
 WORKDIR /app
 
 RUN apt-get update && apt-get install -y \

data/bed_dataset.csv

@@ -8,7 +8,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.5455867648124695,NTv3 8M (pre),1.0,cattle,intron
 0.5453664064407349,NTv3 100M (pre),2.0,cattle,intron
 0.5628412365913391,NTv3 650M (pre),5.0,cattle,intron
-0.5682631134986877,NTv3 650M (post),7.0,cattle,intron
+0.5682631134986877,NTv3 650M (pos),7.0,cattle,intron
 0.3689357042312622,NTv2 500M,87.0,cattle,exon
 0.3250860869884491,BPNet arch. 6M,4.0,cattle,exon
 0.4674676060676574,Residual CNN 44M,19.0,cattle,exon
@@ -18,7 +18,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.5432836413383484,NTv3 8M (pre),1.0,cattle,exon
 0.5531933307647705,NTv3 100M (pre),2.0,cattle,exon
 0.591151773929596,NTv3 650M (pre),5.0,cattle,exon
-0.6253225207328796,NTv3 650M (post),7.0,cattle,exon
+0.6253225207328796,NTv3 650M (pos),7.0,cattle,exon
 0.118808165192604,NTv2 500M,86.0,cattle,splice acceptor
 0.4715546369552612,BPNet arch. 6M,4.0,cattle,splice acceptor
 0.6620649099349976,Residual CNN 44M,19.0,cattle,splice acceptor
@@ -28,7 +28,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7254849076271057,NTv3 8M (pre),1.0,cattle,splice acceptor
 0.7404072880744934,NTv3 100M (pre),2.0,cattle,splice acceptor
 0.7732946872711182,NTv3 650M (pre),5.0,cattle,splice acceptor
-0.7679624557495117,NTv3 650M (post),7.0,cattle,splice acceptor
+0.7679624557495117,NTv3 650M (pos),7.0,cattle,splice acceptor
 0.1412438601255417,NTv2 500M,88.0,cattle,start codon
 0.1490814685821533,BPNet arch. 6M,4.0,cattle,start codon
 0.3243320286273956,Residual CNN 44M,19.0,cattle,start codon
@@ -38,7 +38,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.5275959968566895,NTv3 8M (pre),1.0,cattle,start codon
 0.4962065815925598,NTv3 100M (pre),2.0,cattle,start codon
 0.5591813921928406,NTv3 650M (pre),5.0,cattle,start codon
-0.5492052435874939,NTv3 650M (post),7.0,cattle,start codon
+0.5492052435874939,NTv3 650M (pos),7.0,cattle,start codon
 0.0383123345673084,NTv2 500M,90.0,cattle,intron
 0.1015273928642273,BPNet arch. 6M,7.0,cattle,intron
 0.3299930691719055,Residual CNN 44M,23.0,cattle,intron
@@ -47,16 +47,16 @@ MCC,model_name,running_time_hours,species,datasets
 0.5645747780799866,NTv3 8M (pre),2.0,cattle,intron
 0.5765650272369385,NTv3 100M (pre),2.0,cattle,intron
 0.6140890121459961,NTv3 650M (pre),7.0,cattle,intron
-0.6709504723548889,NTv3 650M (post),10.0,cattle,intron
+0.6709504723548889,NTv3 650M (pos),10.0,cattle,intron
 0.3665516376495361,NTv2 500M,88.0,cattle,exon
 0.323502242565155,BPNet arch. 6M,7.0,cattle,exon
 0.519285261631012,Residual CNN 44M,23.0,cattle,exon
-0.1038060635328292,HyenaDNA 7M,21.0,cattle,splice acceptor
+0.2514283955097198,HyenaDNA 7M,23.0,cattle,exon
 0.5072187781333923,Caduceus 7M,39.0,cattle,exon
 0.593974232673645,NTv3 8M (pre),1.0,cattle,exon
 0.6014777421951294,NTv3 100M (pre),2.0,cattle,exon
 0.6433462500572205,NTv3 650M (pre),7.0,cattle,exon
-0.6648420095443726,NTv3 650M (post),9.0,cattle,exon
+0.6648420095443726,NTv3 650M (pos),9.0,cattle,exon
 0.0937248468399047,NTv2 500M,89.0,cattle,splice acceptor
 0.4435675740242004,BPNet arch. 6M,7.0,cattle,splice acceptor
 0.6590774655342102,Residual CNN 44M,23.0,cattle,splice acceptor
@@ -65,7 +65,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7248824238777161,NTv3 8M (pre),1.0,cattle,splice acceptor
 0.7345820069313049,NTv3 100M (pre),2.0,cattle,splice acceptor
 0.7439091801643372,NTv3 650M (pre),7.0,cattle,splice acceptor
-0.758992075920105,NTv3 650M (post),9.0,cattle,splice acceptor
+0.758992075920105,NTv3 650M (pos),9.0,cattle,splice acceptor
 0.1127461418509483,NTv2 500M,88.0,cattle,start codon
 0.0901669710874557,BPNet arch. 6M,7.0,cattle,start codon
 0.3548502624034881,Residual CNN 44M,23.0,cattle,start codon
@@ -74,25 +74,26 @@ MCC,model_name,running_time_hours,species,datasets
 0.5045616030693054,NTv3 8M (pre),1.0,cattle,start codon
 0.4762806594371795,NTv3 100M (pre),3.0,cattle,start codon
 0.5610686540603638,NTv3 650M (pre),7.0,cattle,start codon
-0.5782408118247986,NTv3 650M (post),9.0,cattle,start codon
+0.5782408118247986,NTv3 650M (pos),9.0,cattle,start codon
 0.1547228246927261,NTv2 500M,85.0,cattle,intron
-0.0639578104019165,BPNet arch. 6M,2.0,cattle,start codon
+0.1383400112390518,BPNet arch. 6M,6.0,cattle,intron
 0.3266464471817016,Residual CNN 44M,23.0,cattle,intron
 0.4240079522132873,HyenaDNA 7M,23.0,cattle,intron
 0.4552704095840454,Caduceus 7M,37.0,cattle,intron
 0.5063548684120178,NTv3 8M (pre),1.0,cattle,intron
 0.5619235038757324,NTv3 100M (pre),3.0,cattle,intron
 0.531277596950531,NTv3 650M (pre),7.0,cattle,intron
-0.6205132603645325,NTv3 650M (post),9.0,cattle,intron
+0.6205132603645325,NTv3 650M (pos),9.0,cattle,intron
 0.3413117229938507,NTv2 500M,87.0,cattle,exon
-0.1383400112390518,BPNet arch. 6M,6.0,cattle,intron
+0.2900931537151336,BPNet arch. 6M,7.0,cattle,exon
 0.4856111407279968,Residual CNN 44M,23.0,cattle,exon
 0.2246854901313781,HyenaDNA 7M,70.0,cattle,exon
 0.5370016098022461,Caduceus 7M,35.0,cattle,exon
 0.5721412897109985,NTv3 8M (pre),2.0,cattle,exon
 0.5819903612136841,NTv3 100M (pre),2.0,cattle,exon
 0.6183731555938721,NTv3 650M (pre),7.0,cattle,exon
-0.6233119964599609,NTv3 650M (post),9.0,cattle,exon
+0.6233119964599609,NTv3 650M (pos),9.0,cattle,exon
+0.1367750316858291,NTv2 500M,89.0,cattle,splice acceptor
 0.4220209121704101,BPNet arch. 6M,7.0,cattle,splice acceptor
 0.689546525478363,Residual CNN 44M,23.0,cattle,splice acceptor
 0.1121769621968269,HyenaDNA 7M,69.0,cattle,splice acceptor
@@ -100,7 +101,8 @@ MCC,model_name,running_time_hours,species,datasets
 0.74350905418396,NTv3 8M (pre),2.0,cattle,splice acceptor
 0.746654748916626,NTv3 100M (pre),2.0,cattle,splice acceptor
 0.7714020609855652,NTv3 650M (pre),7.0,cattle,splice acceptor
-0.7809271812438965,NTv3 650M (post),9.0,cattle,splice acceptor
+0.7809271812438965,NTv3 650M (pos),9.0,cattle,splice acceptor
+0.0901266038417816,NTv2 500M,89.0,cattle,start codon
 0.0930091217160224,BPNet arch. 6M,6.0,cattle,start codon
 0.423166275024414,Residual CNN 44M,23.0,cattle,start codon
 0.1253955662250518,HyenaDNA 7M,72.0,cattle,start codon
@@ -108,7 +110,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.4639334082603454,NTv3 8M (pre),1.0,cattle,start codon
 0.5102551579475403,NTv3 100M (pre),2.0,cattle,start codon
 0.5866840481758118,NTv3 650M (pre),7.0,cattle,start codon
-0.588148832321167,NTv3 650M (post),9.0,cattle,start codon
+0.588148832321167,NTv3 650M (pos),9.0,cattle,start codon
 0.4777896404266357,NTv2 500M,33.0,tomato,intron
 0.3216900527477264,BPNet arch. 6M,1.0,tomato,intron
 0.46840900182724,Residual CNN 44M,6.0,tomato,intron
@@ -117,7 +119,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.6858112812042236,NTv3 8M (pre),0.0,tomato,intron
 0.7038365006446838,NTv3 100M (pre),0.0,tomato,intron
 0.7481895685195923,NTv3 650M (pre),1.0,tomato,intron
-0.7458349466323853,NTv3 650M (post),2.0,tomato,intron
+0.7458349466323853,NTv3 650M (pos),2.0,tomato,intron
 0.6147475838661194,NTv2 500M,33.0,tomato,exon
 0.4551227986812591,BPNet arch. 6M,1.0,tomato,exon
 0.5068296194076538,Residual CNN 44M,6.0,tomato,exon
@@ -126,7 +128,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7537696361541748,NTv3 8M (pre),0.0,tomato,exon
 0.7484462857246399,NTv3 100M (pre),0.0,tomato,exon
 0.764011561870575,NTv3 650M (pre),1.0,tomato,exon
-0.7750575542449951,NTv3 650M (post),2.0,tomato,exon
+0.7750575542449951,NTv3 650M (pos),2.0,tomato,exon
 0.1691933125257492,NTv2 500M,33.0,tomato,splice acceptor
 0.125656172633171,BPNet arch. 6M,1.0,tomato,splice acceptor
 0.4359458982944488,Residual CNN 44M,6.0,tomato,splice acceptor
@@ -135,7 +137,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.6623862385749817,NTv3 8M (pre),0.0,tomato,splice acceptor
 0.6843105554580688,NTv3 100M (pre),0.0,tomato,splice acceptor
 0.7641868591308594,NTv3 650M (pre),1.0,tomato,splice acceptor
-0.7584431767463684,NTv3 650M (post),2.0,tomato,splice acceptor
+0.7584431767463684,NTv3 650M (pos),2.0,tomato,splice acceptor
 0.132934883236885,NTv2 500M,34.0,tomato,start codon
 0.0,BPNet arch. 6M,1.0,tomato,start codon
 0.088478960096836,Residual CNN 44M,6.0,tomato,start codon
@@ -144,22 +146,23 @@ MCC,model_name,running_time_hours,species,datasets
 0.2966536581516266,NTv3 8M (pre),0.0,tomato,start codon
 0.3968957066535949,NTv3 100M (pre),0.0,tomato,start codon
 0.4830105900764465,NTv3 650M (pre),1.0,tomato,start codon
-0.5007501244544983,NTv3 650M (post),2.0,tomato,start codon
+0.5007501244544983,NTv3 650M (pos),2.0,tomato,start codon
 0.6770024299621582,NTv2 500M,33.0,tomato,intron
 0.2927957773208618,BPNet arch. 6M,2.0,tomato,intron
-0.1383400112390518,Residual CNN 44M,6.0,tomato,intron
+0.557494580745697,Residual CNN 44M,8.0,tomato,intron
 0.7252154350280762,PlantCAD2 88M,46.0,tomato,intron
 0.712181031703949,NTv3 8M (pre),1.0,tomato,intron
 0.7515084147453308,NTv3 100M (pre),1.0,tomato,intron
 0.7400797009468079,NTv3 650M (pre),3.0,tomato,intron
-0.7532288432121277,NTv3 650M (post),4.0,tomato,intron
+0.7532288432121277,NTv3 650M (pos),4.0,tomato,intron
 0.5751976370811462,NTv2 500M,33.0,tomato,exon
 0.3057552278041839,BPNet arch. 6M,3.0,tomato,exon
+0.5581462979316711,Residual CNN 44M,8.0,tomato,exon
 0.7699167728424072,PlantCAD2 88M,50.0,tomato,exon
 0.748009443283081,NTv3 8M (pre),1.0,tomato,exon
 0.7629056572914124,NTv3 100M (pre),1.0,tomato,exon
 0.7755228877067566,NTv3 650M (pre),3.0,tomato,exon
-0.782516598701477,NTv3 650M (post),4.0,tomato,exon
+0.782516598701477,NTv3 650M (pos),4.0,tomato,exon
 0.168193981051445,NTv2 500M,33.0,tomato,splice acceptor
 0.0,BPNet arch. 6M,2.0,tomato,splice acceptor
 0.4833243191242218,Residual CNN 44M,8.0,tomato,splice acceptor
@@ -167,7 +170,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.6908777952194214,NTv3 8M (pre),1.0,tomato,splice acceptor
 0.7348777055740356,NTv3 100M (pre),1.0,tomato,splice acceptor
 0.7484620809555054,NTv3 650M (pre),3.0,tomato,splice acceptor
-0.7539154291152954,NTv3 650M (post),4.0,tomato,splice acceptor
+0.7539154291152954,NTv3 650M (pos),4.0,tomato,splice acceptor
 0.1586925536394119,NTv2 500M,33.0,tomato,start codon
 0.0,BPNet arch. 6M,2.0,tomato,start codon
 0.1107296794652938,Residual CNN 44M,8.0,tomato,start codon
@@ -175,7 +178,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.4113904237747192,NTv3 8M (pre),1.0,tomato,start codon
 0.4541433155536651,NTv3 100M (pre),1.0,tomato,start codon
 0.5002310872077942,NTv3 650M (pre),3.0,tomato,start codon
-0.5470007658004761,NTv3 650M (post),4.0,tomato,start codon
+0.5470007658004761,NTv3 650M (pos),4.0,tomato,start codon
 0.6712294220924377,NTv2 500M,33.0,tomato,intron
 0.3502058088779449,BPNet arch. 6M,2.0,tomato,intron
 0.5514466166496277,Residual CNN 44M,8.0,tomato,intron
@@ -183,7 +186,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7013162970542908,NTv3 8M (pre),1.0,tomato,intron
 0.747364342212677,NTv3 100M (pre),1.0,tomato,intron
 0.752423107624054,NTv3 650M (pre),3.0,tomato,intron
-0.7750566005706787,NTv3 650M (post),4.0,tomato,intron
+0.7750566005706787,NTv3 650M (pos),4.0,tomato,intron
 0.6022632718086243,NTv2 500M,33.0,tomato,exon
 0.3020758032798767,BPNet arch. 6M,2.0,tomato,exon
 0.4746756553649902,Residual CNN 44M,8.0,tomato,exon
@@ -191,7 +194,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7157281041145325,NTv3 8M (pre),1.0,tomato,exon
 0.7326820492744446,NTv3 100M (pre),1.0,tomato,exon
 0.7308483123779297,NTv3 650M (pre),3.0,tomato,exon
-0.7417197823524475,NTv3 650M (post),4.0,tomato,exon
+0.7417197823524475,NTv3 650M (pos),4.0,tomato,exon
 0.1558358669281005,NTv2 500M,33.0,tomato,splice acceptor
 0.0,BPNet arch. 6M,2.0,tomato,splice acceptor
 0.3391502797603607,Residual CNN 44M,8.0,tomato,splice acceptor
@@ -199,7 +202,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.6977006196975708,NTv3 8M (pre),1.0,tomato,splice acceptor
 0.6770275831222534,NTv3 100M (pre),1.0,tomato,splice acceptor
 0.6770390272140503,NTv3 650M (pre),3.0,tomato,splice acceptor
-0.7287323474884033,NTv3 650M (post),4.0,tomato,splice acceptor
+0.7287323474884033,NTv3 650M (pos),4.0,tomato,splice acceptor
 0.1887903958559036,NTv2 500M,33.0,tomato,start codon
 0.0639578104019165,BPNet arch. 6M,2.0,tomato,start codon
 0.0914037525653839,Residual CNN 44M,8.0,tomato,start codon
@@ -207,7 +210,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.4309621453285217,NTv3 8M (pre),1.0,tomato,start codon
 0.4028272926807403,NTv3 100M (pre),1.0,tomato,start codon
 0.4060510396957397,NTv3 650M (pre),3.0,tomato,start codon
-0.472331553697586,NTv3 650M (post),4.0,tomato,start codon
+0.472331553697586,NTv3 650M (pos),4.0,tomato,start codon
 0.1995969861745834,NTv2 500M,72.0,human,intron
 0.0296161584556102,BPNet arch. 6M,3.0,human,intron
 0.2347834408283233,Residual CNN 44M,15.0,human,intron
@@ -217,8 +220,8 @@ MCC,model_name,running_time_hours,species,datasets
 0.4695742726325989,NTv3 8M (pre),1.0,human,intron
 0.475054919719696,NTv3 100M (pre),2.0,human,intron
 0.5504136681556702,NTv3 650M (pre),5.0,human,intron
-0.5643875002861023,NTv3 650M (post),6.0,human,intron
-0.1995969861745834,NTv2 500M,72.0,human,intron
+0.5643875002861023,NTv3 650M (pos),6.0,human,intron
+0.0546500161290168,NTv2 500M,72.0,human,exon
 0.2706590592861175,BPNet arch. 6M,3.0,human,exon
 0.2678671479225158,Residual CNN 44M,15.0,human,exon
 0.179698497056961,HyenaDNA 7M,19.0,human,exon
@@ -227,7 +230,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.6089931726455688,NTv3 8M (pre),1.0,human,exon
 0.6492856740951538,NTv3 100M (pre),2.0,human,exon
 0.6975767016410828,NTv3 650M (pre),5.0,human,exon
-0.6822624206542969,NTv3 650M (post),8.0,human,exon
+0.6822624206542969,NTv3 650M (pos),8.0,human,exon
 0.1493269056081771,NTv2 500M,73.0,human,splice acceptor
 0.3807527124881744,BPNet arch. 6M,3.0,human,splice acceptor
 0.6632664203643799,Residual CNN 44M,15.0,human,splice acceptor
@@ -237,7 +240,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7726271748542786,NTv3 8M (pre),1.0,human,splice acceptor
 0.77947598695755,NTv3 100M (pre),2.0,human,splice acceptor
 0.8028115034103394,NTv3 650M (pre),5.0,human,splice acceptor
-0.7979229092597961,NTv3 650M (post),7.0,human,splice acceptor
+0.7979229092597961,NTv3 650M (pos),7.0,human,splice acceptor
 0.139576569199562,NTv2 500M,73.0,human,start codon
 0.1334401220083236,BPNet arch. 6M,3.0,human,start codon
 0.3876807987689972,Residual CNN 44M,15.0,human,start codon
@@ -247,7 +250,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.540923535823822,NTv3 8M (pre),1.0,human,start codon
 0.5464004278182983,NTv3 100M (pre),2.0,human,start codon
 0.6803378462791443,NTv3 650M (pre),5.0,human,start codon
-0.7310947179794312,NTv3 650M (post),7.0,human,start codon
+0.7310947179794312,NTv3 650M (pos),7.0,human,start codon
 0.0814515128731727,NTv2 500M,72.0,human,intron
 0.0172978900372982,BPNet arch. 6M,5.0,human,intron
 0.2740728259086609,Residual CNN 44M,19.0,human,intron
@@ -256,7 +259,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.5034915208816528,NTv3 8M (pre),1.0,human,intron
 0.5154411792755127,NTv3 100M (pre),2.0,human,intron
 0.5814740061759949,NTv3 650M (pre),6.0,human,intron
-0.5920455455780029,NTv3 650M (post),8.0,human,intron
+0.5920455455780029,NTv3 650M (pos),8.0,human,intron
 0.3505669236183166,NTv2 500M,72.0,human,exon
 0.2252149283885955,BPNet arch. 6M,5.0,human,exon
 0.4010578095912933,Residual CNN 44M,18.0,human,exon
@@ -265,7 +268,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.5931490063667297,NTv3 8M (pre),1.0,human,exon
 0.6058318018913269,NTv3 100M (pre),2.0,human,exon
 0.6738048791885376,NTv3 650M (pre),6.0,human,exon
-0.6738048791885376,NTv3 650M (post),6.0,human,exon
+0.6936564445495605,NTv3 650M (pos),8.0,human,exon
 0.1533636748790741,NTv2 500M,72.0,human,splice acceptor
 0.3751010596752167,BPNet arch. 6M,5.0,human,splice acceptor
 0.681228756904602,Residual CNN 44M,19.0,human,splice acceptor
@@ -274,7 +277,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7772909998893738,NTv3 8M (pre),1.0,human,splice acceptor
 0.794090747833252,NTv3 100M (pre),2.0,human,splice acceptor
 0.8239933252334595,NTv3 650M (pre),6.0,human,splice acceptor
-0.804115891456604,NTv3 650M (post),8.0,human,splice acceptor
+0.804115891456604,NTv3 650M (pos),8.0,human,splice acceptor
 0.0851806029677391,NTv2 500M,72.0,human,start codon
 0.0,BPNet arch. 6M,5.0,human,start codon
 0.3292546272277832,Residual CNN 44M,19.0,human,start codon
@@ -283,7 +286,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.60422682762146,NTv3 8M (pre),1.0,human,start codon
 0.6015576124191284,NTv3 100M (pre),2.0,human,start codon
 0.6452956795692444,NTv3 650M (pre),6.0,human,start codon
-0.6761345267295837,NTv3 650M (post),8.0,human,start codon
+0.6761345267295837,NTv3 650M (pos),8.0,human,start codon
 0.0558800511062145,NTv2 500M,70.0,human,intron
 0.0185965970158576,BPNet arch. 6M,5.0,human,intron
 0.2623045742511749,Residual CNN 44M,18.0,human,intron
@@ -292,16 +295,16 @@ MCC,model_name,running_time_hours,species,datasets
 0.4804849028587341,NTv3 8M (pre),1.0,human,intron
 0.482195496559143,NTv3 100M (pre),2.0,human,intron
 0.5425574779510498,NTv3 650M (pre),6.0,human,intron
-0.5443048477172852,NTv3 650M (post),8.0,human,intron
+0.5443048477172852,NTv3 650M (pos),8.0,human,intron
 0.3958893716335296,NTv2 500M,71.0,human,exon
 0.2360571771860122,BPNet arch. 6M,5.0,human,exon
-0.2360571771860122,Residual CNN 44M,5.0,human,exon
+0.3744256496429443,Residual CNN 44M,18.0,human,exon
 0.1936572045087814,HyenaDNA 7M,68.0,human,exon
 0.5046994090080261,Caduceus 7M,29.0,human,exon
 0.6339762210845947,NTv3 8M (pre),1.0,human,exon
 0.6433913111686707,NTv3 100M (pre),2.0,human,exon
 0.6518793702125549,NTv3 650M (pre),6.0,human,exon
-0.6812491416931152,NTv3 650M (post),8.0,human,exon
+0.6812491416931152,NTv3 650M (pos),8.0,human,exon
 0.1248077526688575,NTv2 500M,70.0,human,splice acceptor
 0.3842235207557678,BPNet arch. 6M,5.0,human,splice acceptor
 0.6810190081596375,Residual CNN 44M,18.0,human,splice acceptor
@@ -310,7 +313,7 @@ MCC,model_name,running_time_hours,species,datasets
 0.7796080708503723,NTv3 8M (pre),1.0,human,splice acceptor
 0.7596970200538635,NTv3 100M (pre),2.0,human,splice acceptor
 0.7915040850639343,NTv3 650M (pre),6.0,human,splice acceptor
-0.7957100868225098,NTv3 650M (post),8.0,human,splice acceptor
+0.7957100868225098,NTv3 650M (pos),8.0,human,splice acceptor
 0.1267423331737518,NTv2 500M,70.0,human,start codon
 0.1114460304379463,BPNet arch. 6M,5.0,human,start codon
 0.3342535495758056,Residual CNN 44M,18.0,human,start codon
@@ -319,4 +322,13 @@ MCC,model_name,running_time_hours,species,datasets
 0.5167152881622314,NTv3 8M (pre),1.0,human,start codon
 0.5340564250946045,NTv3 100M (pre),2.0,human,start codon
 0.6148532032966614,NTv3 650M (pre),6.0,human,start codon
-0.6582212448120117,NTv3 650M (post),8.0,human,start codon
+0.6582212448120117,NTv3 650M (pos),8.0,human,start codon
+0.6582212448120117,NTv3 650M (pre),8.0,human,start codon
+0.6582212448120117,BPNet arch. 6M,8.0,human,start codon
+0.6582212448120117,Caduceus 7M,8.0,human,start codon
+0.6582212448120117,NTv3 650M (pre),8.0,human,start codon
+0.6582212448120117,BPNet arch. 6M,8.0,human,start codon
+0.6582212448120117,Caduceus 7M,8.0,human,start codon
+0.6582212448120117,NTv3 650M (pre),8.0,human,start codon
+0.6582212448120117,BPNet arch. 6M,8.0,human,start codon
+0.6582212448120117,Caduceus 7M,8.0,human,start codon

data/bigwig_dataset.csv

@@ -27,20 +27,14 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.2919895648956299,BPNet arch. 6M,0.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
 0.2817385196685791,BPNet arch. 6M,0.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
 0.3134908080101013,BPNet arch. 6M,0.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
-0.2150303125381469,Residual CNN 44M,2.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
-0.203000858426094,Residual CNN 44M,2.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
-0.3181040287017822,Residual CNN 44M,2.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
-0.3007544279098511,Residual CNN 44M,2.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
-0.3750689625740051,Residual CNN 44M,2.0,ribo_seq (root),rice,SRR13808068,ribo-seq
-0.3484497368335724,Residual CNN 44M,2.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
-0.3496915698051452,Residual CNN 44M,2.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
-0.3874056935310364,Residual CNN 44M,2.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
-0.2943477630615234,Residual CNN 44M,2.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
-0.3148464560508728,Residual CNN 44M,2.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
-0.3588837385177612,Residual CNN 44M,2.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
-0.378544807434082,Residual CNN 44M,2.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
-0.3453188240528106,Residual CNN 44M,2.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
-0.3944509327411651,Residual CNN 44M,2.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
+0.3678567707538605,Residual CNN 44M,12.0,ribo_seq (ear),rice,SRR13808051,ribo-seq
+0.3232702910900116,Residual CNN 44M,12.0,ribo_seq (ear),rice,SRR13808052,ribo-seq
+0.2772392034530639,Residual CNN 44M,12.0,ribo_seq (root),rice,SRR13808056,ribo-seq
+0.2370112538337707,Residual CNN 44M,12.0,ribo_seq (seedling),rice,SRR13808058,ribo-seq
+0.224403977394104,Residual CNN 44M,12.0,ribo_seq (stem),rice,SRR13808059,ribo-seq
+0.3550889790058136,Residual CNN 44M,12.0,ribo_seq (stem),rice,SRR13808061,ribo-seq
+0.2398815304040908,Residual CNN 44M,12.0,ribo_seq (tassel),rice,SRR13808062,ribo-seq
+0.277915209531784,Residual CNN 44M,12.0,ribo_seq (tassel),rice,SRR13808063,ribo-seq
 0.2837843298912048,PlantCAD2 88M,16.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
 0.2707407474517822,PlantCAD2 88M,16.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
 0.3722770512104034,PlantCAD2 88M,16.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
@@ -111,20 +105,20 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.6019349694252014,NTv3 650M (pre),1.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
 0.5489044785499573,NTv3 650M (pre),1.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
 0.618698239326477,NTv3 650M (pre),1.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
-0.4607670605182647,NTv3 650M (post),1.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
-0.4394749999046325,NTv3 650M (post),1.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
-0.5848951935768127,NTv3 650M (post),1.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
-0.5622204542160034,NTv3 650M (post),1.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
-0.5916759967803955,NTv3 650M (post),1.0,ribo_seq (root),rice,SRR13808068,ribo-seq
-0.5764754414558411,NTv3 650M (post),1.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
-0.5878051519393921,NTv3 650M (post),1.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
-0.630181610584259,NTv3 650M (post),1.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
-0.5421943068504333,NTv3 650M (post),1.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
-0.5518381595611572,NTv3 650M (post),1.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
-0.5964754223823547,NTv3 650M (post),1.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
-0.6291244029998779,NTv3 650M (post),1.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
-0.5789201259613037,NTv3 650M (post),1.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
-0.6471180319786072,NTv3 650M (post),1.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
+0.4607670605182647,NTv3 650M (pos),1.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
+0.4394749999046325,NTv3 650M (pos),1.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
+0.5848951935768127,NTv3 650M (pos),1.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
+0.5622204542160034,NTv3 650M (pos),1.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
+0.5916759967803955,NTv3 650M (pos),1.0,ribo_seq (root),rice,SRR13808068,ribo-seq
+0.5764754414558411,NTv3 650M (pos),1.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
+0.5878051519393921,NTv3 650M (pos),1.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
+0.630181610584259,NTv3 650M (pos),1.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
+0.5421943068504333,NTv3 650M (pos),1.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
+0.5518381595611572,NTv3 650M (pos),1.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
+0.5964754223823547,NTv3 650M (pos),1.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
+0.6291244029998779,NTv3 650M (pos),1.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
+0.5789201259613037,NTv3 650M (pos),1.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
+0.6471180319786072,NTv3 650M (pos),1.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
 0.1415691971778869,NTv2 500M,17.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
 0.1381142288446426,NTv2 500M,17.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
 0.1857678592205047,NTv2 500M,17.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
@@ -223,20 +217,20 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.5863885283470154,NTv3 650M (pre),3.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
 0.5376706123352051,NTv3 650M (pre),3.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
 0.6103342175483704,NTv3 650M (pre),3.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
-0.4587286412715912,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
-0.4493650496006012,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
-0.4906429946422577,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
-0.4860836267471313,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
-0.5586262345314026,NTv3 650M (post),3.0,ribo_seq (root),rice,SRR13808068,ribo-seq
-0.5837969779968262,NTv3 650M (post),3.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
-0.6013871431350708,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
-0.6420598030090332,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
-0.5484504103660583,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
-0.5517898201942444,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
-0.5927240252494812,NTv3 650M (post),3.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
-0.6197990775108337,NTv3 650M (post),3.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
-0.5803423523902893,NTv3 650M (post),3.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
-0.6479265689849854,NTv3 650M (post),3.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
+0.4587286412715912,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
+0.4493650496006012,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
+0.4906429946422577,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
+0.4860836267471313,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
+0.5586262345314026,NTv3 650M (pos),3.0,ribo_seq (root),rice,SRR13808068,ribo-seq
+0.5837969779968262,NTv3 650M (pos),3.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
+0.6013871431350708,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
+0.6420598030090332,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
+0.5484504103660583,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
+0.5517898201942444,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
+0.5927240252494812,NTv3 650M (pos),3.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
+0.6197990775108337,NTv3 650M (pos),3.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
+0.5803423523902893,NTv3 650M (pos),3.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
+0.6479265689849854,NTv3 650M (pos),3.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
 0.1506477743387222,NTv2 500M,18.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
 0.1471661329269409,NTv2 500M,18.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
 0.183156132698059,NTv2 500M,18.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
@@ -335,20 +329,20 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.5842210054397583,NTv3 650M (pre),3.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
 0.5283579230308533,NTv3 650M (pre),3.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
 0.600659191608429,NTv3 650M (pre),3.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
-0.4478877484798431,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
-0.4366068840026855,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
-0.4791591167449951,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
-0.4743838906288147,NTv3 650M (post),3.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
-0.5484936237335205,NTv3 650M (post),3.0,ribo_seq (root),rice,SRR13808068,ribo-seq
-0.5838179588317871,NTv3 650M (post),3.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
-0.5923089981079102,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
-0.6353456974029541,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
-0.5277841091156006,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
-0.5345388054847717,NTv3 650M (post),3.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
-0.5861888527870178,NTv3 650M (post),3.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
-0.6099538803100586,NTv3 650M (post),3.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
-0.5744394063949585,NTv3 650M (post),3.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
-0.6472521424293518,NTv3 650M (post),3.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
+0.4478877484798431,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808064,ribo-seq
+0.4366068840026855,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808065,ribo-seq
+0.4791591167449951,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808066,ribo-seq
+0.4743838906288147,NTv3 650M (pos),3.0,ribo_seq (leaf),rice,SRR13808067,ribo-seq
+0.5484936237335205,NTv3 650M (pos),3.0,ribo_seq (root),rice,SRR13808068,ribo-seq
+0.5838179588317871,NTv3 650M (pos),3.0,ribo_seq (seedling),rice,SRR13808069,ribo-seq
+0.5923089981079102,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808070,ribo-seq
+0.6353456974029541,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808072,ribo-seq
+0.5277841091156006,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808073,ribo-seq
+0.5345388054847717,NTv3 650M (pos),3.0,ribo_seq (sheath),rice,SRR13808074,ribo-seq
+0.5861888527870178,NTv3 650M (pos),3.0,ribo_seq (spikelet),rice,SRR13808075,ribo-seq
+0.6099538803100586,NTv3 650M (pos),3.0,ribo_seq (spikelet),rice,SRR13808076,ribo-seq
+0.5744394063949585,NTv3 650M (pos),3.0,ribo_seq (stem),rice,SRR13808077,ribo-seq
+0.6472521424293518,NTv3 650M (pos),3.0,ribo_seq (stem),rice,SRR13808078,ribo-seq
 0.1417283415794372,NTv2 500M,3.0,ribo_seq (flower),arabidopsis,SRR13808079,ribo-seq
 0.1179740354418754,NTv2 500M,3.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.1458676308393478,NTv2 500M,3.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
@@ -389,18 +383,18 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.4816102683544159,NTv3 650M (pre),0.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.5676506757736206,NTv3 650M (pre),0.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
 0.5894543528556824,NTv3 650M (pre),0.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
-0.5641168355941772,NTv3 650M (post),0.0,ribo_seq (flower),arabidopsis,SRR13808079,ribo-seq
-0.4926825165748596,NTv3 650M (post),0.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
-0.5502273440361023,NTv3 650M (post),0.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
-0.632440984249115,NTv3 650M (post),0.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
+0.5641168355941772,NTv3 650M (pos),0.0,ribo_seq (flower),arabidopsis,SRR13808079,ribo-seq
+0.4926825165748596,NTv3 650M (pos),0.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
+0.5502273440361023,NTv3 650M (pos),0.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
+0.632440984249115,NTv3 650M (pos),0.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
 0.1411919593811035,NTv2 500M,7.0,ribo_seq (flower),arabidopsis,SRR13808079,ribo-seq
 0.1251052767038345,NTv2 500M,7.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.1281666010618209,NTv2 500M,7.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
 0.1290743798017501,NTv2 500M,7.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
-0.1174568757414817,BPNet arch. 100k,0.0,ribo_seq (flower),arabidopsis,SRR13808079,ribo-seq
-0.1109003499150276,BPNet arch. 100k,0.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
-0.1174564957618713,BPNet arch. 100k,0.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
-0.1074777469038963,BPNet arch. 100k,0.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
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+0.0877858027815818,BPNet arch. 100k,0.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
+0.0880207195878028,BPNet arch. 100k,0.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
+0.0817214399576187,BPNet arch. 100k,0.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
 0.1174568757414817,BPNet arch. 6M,0.0,ribo_seq (flower),arabidopsis,SRR13808079,ribo-seq
 0.1109003499150276,BPNet arch. 6M,0.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.1174564957618713,BPNet arch. 6M,0.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
@@ -429,10 +423,10 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.5614269375801086,NTv3 650M (pre),2.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.6194525361061096,NTv3 650M (pre),2.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
 0.6506752371788025,NTv3 650M (pre),2.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
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-0.7172045707702637,NTv3 650M (post),2.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
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 0.0663405656814575,NTv2 500M,6.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.0968577861785888,NTv2 500M,6.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
@@ -469,10 +463,10 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.5230018496513367,NTv3 650M (pre),2.0,ribo_seq (flower),arabidopsis,SRR13808080,ribo-seq
 0.5467196106910706,NTv3 650M (pre),2.0,ribo_seq (friut),arabidopsis,SRR13808081,ribo-seq
 0.5869554281234741,NTv3 650M (pre),2.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
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+0.7200157642364502,NTv3 650M (pos),2.0,ribo_seq (root),arabidopsis,SRR13808084,ribo-seq
 0.3767618238925934,NTv2 500M,42.0,RNA_seq (Uterus),chicken,ERX9662194,RNA-seq
 0.6090583205223083,NTv2 500M,42.0,ATAC_seq (bone_marrow),chicken,ERX9662174,ATAC-seq
 0.5254472494125366,NTv2 500M,42.0,RNA_seq (bone_marrow),chicken,ERX9662188,RNA-seq
@@ -599,20 +593,20 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.7538702487945557,NTv3 650M (pre),2.0,ATAC_seq (trachea),chicken,ERX9662186,ATAC-seq
 0.7186523079872131,NTv3 650M (pre),2.0,RNA_seq (trachea),chicken,ERX9662200,RNA-seq
 0.613059401512146,NTv3 650M (pre),2.0,ATAC_seq (uterus),chicken,ERX9662180,ATAC-seq
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+0.7020899057388306,NTv3 650M (pos),3.0,ATAC_seq (uterus),chicken,ERX9662180,ATAC-seq
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 0.5663936734199524,NTv2 500M,42.0,ATAC_seq (bone_marrow),chicken,ERX9662174,ATAC-seq
 0.4966712296009063,NTv2 500M,42.0,RNA_seq (bone_marrow),chicken,ERX9662188,RNA-seq
@@ -725,20 +719,20 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.7482877969741821,NTv3 650M (pre),4.0,ATAC_seq (trachea),chicken,ERX9662186,ATAC-seq
 0.7032458782196045,NTv3 650M (pre),4.0,RNA_seq (trachea),chicken,ERX9662200,RNA-seq
 0.597597599029541,NTv3 650M (pre),4.0,ATAC_seq (uterus),chicken,ERX9662180,ATAC-seq
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-0.8202974200248718,NTv3 650M (post),5.0,ATAC_seq (bone_marrow),chicken,ERX9662174,ATAC-seq
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-0.7317394018173218,NTv3 650M (post),5.0,ATAC_seq (heart),chicken,ERX9662177,ATAC-seq
-0.5619479417800903,NTv3 650M (post),5.0,RNA_seq (heart),chicken,ERX9662190,RNA-seq
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+0.699863076210022,NTv3 650M (pos),5.0,RNA_seq (trachea),chicken,ERX9662200,RNA-seq
+0.6796203851699829,NTv3 650M (pos),5.0,ATAC_seq (uterus),chicken,ERX9662180,ATAC-seq
 0.3368246853351593,NTv2 500M,53.0,RNA_seq (Uterus),chicken,ERX9662194,RNA-seq
 0.5521946549415588,NTv2 500M,53.0,ATAC_seq (bone_marrow),chicken,ERX9662174,ATAC-seq
 0.4927390515804291,NTv2 500M,53.0,RNA_seq (bone_marrow),chicken,ERX9662188,RNA-seq
@@ -851,20 +845,20 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.7431631684303284,NTv3 650M (pre),5.0,ATAC_seq (trachea),chicken,ERX9662186,ATAC-seq
 0.6717550158500671,NTv3 650M (pre),5.0,RNA_seq (trachea),chicken,ERX9662200,RNA-seq
 0.6055813431739807,NTv3 650M (pre),5.0,ATAC_seq (uterus),chicken,ERX9662180,ATAC-seq
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-0.8119961023330688,NTv3 650M (post),6.0,ATAC_seq (bone_marrow),chicken,ERX9662174,ATAC-seq
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-0.7413464784622192,NTv3 650M (post),6.0,ATAC_seq (heart),chicken,ERX9662177,ATAC-seq
-0.5783720016479492,NTv3 650M (post),6.0,RNA_seq (heart),chicken,ERX9662190,RNA-seq
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 0.2137461602687835,NTv2 500M,65.0,PRO_cap M (A673),human,ENCSR046BCI_M,PRO-cap
 0.173895314335823,NTv2 500M,65.0,PRO_cap P (A673),human,ENCSR046BCI_P,PRO-cap
 0.4677464365959167,NTv2 500M,65.0,Histone_ChIP_seq (BLaER1 - H3K4me1_human),human,ENCSR863PSM,Histone ChIP-seq
@@ -1239,40 +1233,40 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.7609084248542786,NTv3 650M (pre),8.0,ATAC_seq (ureter),human,ENCSR814RGG,ATAC-seq
 0.7134000062942505,NTv3 650M (pre),8.0,total_RNA_seq M (ureter),human,ENCSR619DQO_M,RNA-seq
 0.6713509559631348,NTv3 650M (pre),8.0,total_RNA_seq P (ureter),human,ENCSR619DQO_P,RNA-seq
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-0.7014502882957458,NTv3 650M (post),9.0,Histone_ChIP_seq (BLaER1 - H3K4me1_human),human,ENCSR863PSM,Histone ChIP-seq
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-0.5853492617607117,NTv3 650M (post),9.0,Histone_ChIP_seq (motor_neuron - H3K27ac_human),human,ENCSR754DRC,Histone ChIP-seq
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+0.915168821811676,NTv3 650M (pos),9.0,Histone_ChIP_seq (motor_neuron - H3K4me3_human),human,ENCSR962OTG,Histone ChIP-seq
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+0.6868586540222168,NTv3 650M (pos),9.0,total_RNA_seq P (ureter),human,ENCSR619DQO_P,RNA-seq
 0.2167430073022842,NTv2 500M,80.0,PRO_cap M (A673),human,ENCSR046BCI_M,PRO-cap
 0.1863466948270797,NTv2 500M,80.0,PRO_cap P (A673),human,ENCSR046BCI_P,PRO-cap
 0.4794709980487823,NTv2 500M,80.0,Histone_ChIP_seq (BLaER1 - H3K4me1_human),human,ENCSR863PSM,Histone ChIP-seq
@@ -1613,40 +1607,40 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.7566699981689453,NTv3 650M (pre),12.0,ATAC_seq (ureter),human,ENCSR814RGG,ATAC-seq
 0.6717830896377563,NTv3 650M (pre),12.0,total_RNA_seq M (ureter),human,ENCSR619DQO_M,RNA-seq
 0.6946780681610107,NTv3 650M (pre),12.0,total_RNA_seq P (ureter),human,ENCSR619DQO_P,RNA-seq
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-0.708307147026062,NTv3 650M (post),11.0,polyA_plus_RNA_seq M (BLaER1),human,ENCSR527JGN_M,RNA-seq
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-0.5756644010543823,NTv3 650M (post),11.0,eCLIP M (K562 - HNRNPA1_human),human,ENCSR154HRN_M,eCLIP
-0.5596388578414917,NTv3 650M (post),11.0,eCLIP P (K562 - HNRNPA1_human),human,ENCSR154HRN_P,eCLIP
-0.6537778377532959,NTv3 650M (post),11.0,eCLIP M (K562 - HNRNPC_human),human,ENCSR249ROI_M,eCLIP
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-0.4870648086071014,NTv3 650M (post),11.0,eCLIP P (K562 - NCBP2_human),human,ENCSR484LTQ_P,eCLIP
-0.6504180431365967,NTv3 650M (post),11.0,eCLIP M (K562 - SRSF1_human),human,ENCSR321PWZ_M,eCLIP
-0.7162089943885803,NTv3 650M (post),11.0,eCLIP P (K562 - SRSF1_human),human,ENCSR321PWZ_P,eCLIP
-0.6109191179275513,NTv3 650M (post),11.0,eCLIP M (K562 - U2AF1_human),human,ENCSR862QCH_M,eCLIP
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-0.5789141654968262,NTv3 650M (post),11.0,PRO_cap M (MCF_10A),human,ENCSR799DGV_M,PRO-cap
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+0.9042603373527528,NTv3 650M (pos),11.0,Histone_ChIP_seq (motor_neuron - H3K4me3_human),human,ENCSR962OTG,Histone ChIP-seq
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 0.4761865139007568,NTv2 500M,82.0,Histone_ChIP_seq (BLaER1 - H3K4me1_human),human,ENCSR863PSM,Histone ChIP-seq
@@ -1987,40 +1981,40 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.7325116395950317,NTv3 650M (pre),12.0,ATAC_seq (ureter),human,ENCSR814RGG,ATAC-seq
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-0.6959746479988098,NTv3 650M (post),12.0,Histone_ChIP_seq (BLaER1 - H3K4me1_human),human,ENCSR863PSM,Histone ChIP-seq
-0.8505153059959412,NTv3 650M (post),12.0,polyA_plus_RNA_seq M (BLaER1),human,ENCSR527JGN_M,RNA-seq
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-0.7304314970970154,NTv3 650M (post),12.0,eCLIP M (K562 - SRSF1_human),human,ENCSR321PWZ_M,eCLIP
-0.7275874614715576,NTv3 650M (post),12.0,eCLIP P (K562 - SRSF1_human),human,ENCSR321PWZ_P,eCLIP
-0.5746122002601624,NTv3 650M (post),12.0,eCLIP M (K562 - U2AF1_human),human,ENCSR862QCH_M,eCLIP
-0.5553757548332214,NTv3 650M (post),12.0,eCLIP P (K562 - U2AF1_human),human,ENCSR862QCH_P,eCLIP
-0.4990127086639404,NTv3 650M (post),12.0,PRO_cap M (MCF_10A),human,ENCSR799DGV_M,PRO-cap
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-0.8312347531318665,NTv3 650M (post),12.0,ATAC_seq (bile_duct),human,ENCSR325NFE,ATAC-seq
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-0.5725923180580139,NTv3 650M (post),12.0,Histone_ChIP_seq (motor_neuron - H3K27ac_human),human,ENCSR754DRC,Histone ChIP-seq
-0.6706770062446594,NTv3 650M (post),12.0,Histone_ChIP_seq (motor_neuron - H3K4me1_human),human,ENCSR682BFG,Histone ChIP-seq
-0.8982567191123962,NTv3 650M (post),12.0,Histone_ChIP_seq (motor_neuron - H3K4me3_human),human,ENCSR962OTG,Histone ChIP-seq
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+0.5725923180580139,NTv3 650M (pos),12.0,Histone_ChIP_seq (motor_neuron - H3K27ac_human),human,ENCSR754DRC,Histone ChIP-seq
+0.6706770062446594,NTv3 650M (pos),12.0,Histone_ChIP_seq (motor_neuron - H3K4me1_human),human,ENCSR682BFG,Histone ChIP-seq
+0.8982567191123962,NTv3 650M (pos),12.0,Histone_ChIP_seq (motor_neuron - H3K4me3_human),human,ENCSR962OTG,Histone ChIP-seq
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+0.7876009345054626,NTv3 650M (pos),12.0,ATAC_seq (ureter),human,ENCSR814RGG,ATAC-seq
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+0.6809684038162231,NTv3 650M (pos),12.0,total_RNA_seq P (ureter),human,ENCSR619DQO_P,RNA-seq
 0.3366053104400635,NTv2 500M,73.0,ribo_seq (ear),maize,SRR13808051,ribo-seq
 0.3023947179317474,NTv2 500M,73.0,ribo_seq (ear),maize,SRR13808052,ribo-seq
 0.2840931713581085,NTv2 500M,73.0,ribo_seq (root),maize,SRR13808056,ribo-seq
@@ -2085,14 +2079,14 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.5688028335571289,NTv3 650M (pre),4.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
 0.3758339583873749,NTv3 650M (pre),4.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
 0.4126724600791931,NTv3 650M (pre),4.0,ribo_seq (tassel),maize,SRR13808063,ribo-seq
-0.5840011239051819,NTv3 650M (post),6.0,ribo_seq (ear),maize,SRR13808051,ribo-seq
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-0.4323615729808807,NTv3 650M (post),6.0,ribo_seq (seedling),maize,SRR13808058,ribo-seq
-0.393085777759552,NTv3 650M (post),6.0,ribo_seq (stem),maize,SRR13808059,ribo-seq
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-0.3962268829345703,NTv3 650M (post),6.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
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+0.4323615729808807,NTv3 650M (pos),6.0,ribo_seq (seedling),maize,SRR13808058,ribo-seq
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+0.3962268829345703,NTv3 650M (pos),6.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
+0.428356260061264,NTv3 650M (pos),6.0,ribo_seq (tassel),maize,SRR13808063,ribo-seq
 0.288285493850708,NTv2 500M,71.0,ribo_seq (ear),maize,SRR13808051,ribo-seq
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 0.2758374810218811,NTv2 500M,71.0,ribo_seq (root),maize,SRR13808056,ribo-seq
@@ -2117,20 +2111,14 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.4002938866615295,Residual CNN 44M,18.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
 0.3250653743743896,Residual CNN 44M,18.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
 0.3172951340675354,Residual CNN 44M,18.0,ribo_seq (tassel),maize,SRR13808063,ribo-seq
-0.2963113188743591,PlantCAD2 88M,21.0,ribo_seq (leaf),maize,SRR13808064,ribo-seq
-0.2868160307407379,PlantCAD2 88M,21.0,ribo_seq (leaf),maize,SRR13808065,ribo-seq
-0.3480705320835113,PlantCAD2 88M,21.0,ribo_seq (leaf),maize,SRR13808066,ribo-seq
-0.3456166386604309,PlantCAD2 88M,21.0,ribo_seq (leaf),maize,SRR13808067,ribo-seq
-0.472971647977829,PlantCAD2 88M,21.0,ribo_seq (root),maize,SRR13808068,ribo-seq
-0.4647295475006103,PlantCAD2 88M,21.0,ribo_seq (seedling),maize,SRR13808069,ribo-seq
-0.4622688591480255,PlantCAD2 88M,21.0,ribo_seq (sheath),maize,SRR13808070,ribo-seq
-0.5197103023529053,PlantCAD2 88M,21.0,ribo_seq (sheath),maize,SRR13808072,ribo-seq
-0.398128479719162,PlantCAD2 88M,21.0,ribo_seq (sheath),maize,SRR13808073,ribo-seq
-0.4072911739349365,PlantCAD2 88M,21.0,ribo_seq (sheath),maize,SRR13808074,ribo-seq
-0.4800446331501007,PlantCAD2 88M,21.0,ribo_seq (spikelet),maize,SRR13808075,ribo-seq
-0.5034564137458801,PlantCAD2 88M,21.0,ribo_seq (spikelet),maize,SRR13808076,ribo-seq
-0.4551317393779754,PlantCAD2 88M,21.0,ribo_seq (stem),maize,SRR13808077,ribo-seq
-0.5189424753189087,PlantCAD2 88M,21.0,ribo_seq (stem),maize,SRR13808078,ribo-seq
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+0.4097760617733001,PlantCAD2 88M,103.0,ribo_seq (seedling),maize,SRR13808058,ribo-seq
+0.3393965065479278,PlantCAD2 88M,103.0,ribo_seq (stem),maize,SRR13808059,ribo-seq
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+0.4084210693836212,PlantCAD2 88M,103.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
+0.4090923964977264,PlantCAD2 88M,103.0,ribo_seq (tassel),maize,SRR13808063,ribo-seq
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 0.5301717519760132,NTv3 8M (pre),6.0,ribo_seq (root),maize,SRR13808056,ribo-seq
@@ -2155,14 +2143,14 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.6178003549575806,NTv3 650M (pre),6.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
 0.5222280621528625,NTv3 650M (pre),6.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
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-0.671734631061554,NTv3 650M (post),9.0,ribo_seq (ear),maize,SRR13808051,ribo-seq
-0.6138322353363037,NTv3 650M (post),9.0,ribo_seq (ear),maize,SRR13808052,ribo-seq
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-0.5859291553497314,NTv3 650M (post),9.0,ribo_seq (seedling),maize,SRR13808058,ribo-seq
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-0.5704927444458008,NTv3 650M (post),9.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
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+0.6506127119064331,NTv3 650M (pos),9.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
+0.5704927444458008,NTv3 650M (pos),9.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
+0.5555143356323242,NTv3 650M (pos),9.0,ribo_seq (tassel),maize,SRR13808063,ribo-seq
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 0.2377371788024902,NTv2 500M,73.0,ribo_seq (root),maize,SRR13808056,ribo-seq
@@ -2219,14 +2207,14 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.6381479501724243,NTv3 650M (pre),7.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
 0.5676515102386475,NTv3 650M (pre),7.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
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-0.6871418952941895,NTv3 650M (post),8.0,ribo_seq (ear),maize,SRR13808051,ribo-seq
-0.6451906561851501,NTv3 650M (post),8.0,ribo_seq (ear),maize,SRR13808052,ribo-seq
-0.6162436008453369,NTv3 650M (post),8.0,ribo_seq (root),maize,SRR13808056,ribo-seq
-0.5388527512550354,NTv3 650M (post),8.0,ribo_seq (seedling),maize,SRR13808058,ribo-seq
-0.5485992431640625,NTv3 650M (post),8.0,ribo_seq (stem),maize,SRR13808059,ribo-seq
-0.67100989818573,NTv3 650M (post),8.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
-0.5655654072761536,NTv3 650M (post),8.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
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+0.6871418952941895,NTv3 650M (pos),8.0,ribo_seq (ear),maize,SRR13808051,ribo-seq
+0.6451906561851501,NTv3 650M (pos),8.0,ribo_seq (ear),maize,SRR13808052,ribo-seq
+0.6162436008453369,NTv3 650M (pos),8.0,ribo_seq (root),maize,SRR13808056,ribo-seq
+0.5388527512550354,NTv3 650M (pos),8.0,ribo_seq (seedling),maize,SRR13808058,ribo-seq
+0.5485992431640625,NTv3 650M (pos),8.0,ribo_seq (stem),maize,SRR13808059,ribo-seq
+0.67100989818573,NTv3 650M (pos),8.0,ribo_seq (stem),maize,SRR13808061,ribo-seq
+0.5655654072761536,NTv3 650M (pos),8.0,ribo_seq (tassel),maize,SRR13808062,ribo-seq
+0.5315231680870056,NTv3 650M (pos),8.0,ribo_seq (tassel),maize,SRR13808063,ribo-seq
 0.5623048543930054,NTv2 500M,38.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
 0.5635078549385071,NTv2 500M,38.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
 0.5693665146827698,NTv2 500M,38.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
@@ -2387,26 +2375,26 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.4804110825061798,NTv3 650M (pre),2.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
 0.457105278968811,NTv3 650M (pre),2.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
 0.4594825804233551,NTv3 650M (pre),2.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
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-0.893308162689209,NTv3 650M (post),2.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
-0.8826373219490051,NTv3 650M (post),2.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
-0.8639559149742126,NTv3 650M (post),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291430,RNA-seq
-0.8841373324394226,NTv3 650M (post),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291431,RNA-seq
-0.8746727705001831,NTv3 650M (post),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291442,RNA-seq
-0.8546006083488464,NTv3 650M (post),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291445,RNA-seq
-0.9037920236587524,NTv3 650M (post),2.0,RNA_seq (DPA5_fruit),tomato,SRX29291441,RNA-seq
-0.9000611305236816,NTv3 650M (post),2.0,RNA_seq (DPA5_fruit),tomato,SRX29291443,RNA-seq
-0.8993349671363831,NTv3 650M (post),2.0,RNA_seq (DPA5_fruit),tomato,SRX29291444,RNA-seq
-0.4953060448169708,NTv3 650M (post),2.0,ATAC_seq (anthesis_fruit),tomato,SRX27799703,ATAC-seq
-0.8582074642181396,NTv3 650M (post),2.0,RNA_seq (anthesis_fruit),tomato,SRX29291438,RNA-seq
-0.8407872319221497,NTv3 650M (post),2.0,RNA_seq (anthesis_fruit),tomato,SRX29291439,RNA-seq
-0.843441903591156,NTv3 650M (post),2.0,RNA_seq (anthesis_fruit),tomato,SRX29291440,RNA-seq
-0.5302762985229492,NTv3 650M (post),2.0,ATAC_seq (daa10_fruit),tomato,SRX27799731,ATAC-seq
-0.4703091979026794,NTv3 650M (post),2.0,ATAC_seq (daa3_fruit),tomato,SRX27799719,ATAC-seq
-0.6039619445800781,NTv3 650M (post),2.0,ATAC_seq (daa5_fruit),tomato,SRX27799727,ATAC-seq
-0.4973532855510711,NTv3 650M (post),2.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
-0.4723750054836273,NTv3 650M (post),2.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
-0.48711958527565,NTv3 650M (post),2.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
+0.887213408946991,NTv3 650M (pos),2.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
+0.893308162689209,NTv3 650M (pos),2.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
+0.8826373219490051,NTv3 650M (pos),2.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
+0.8639559149742126,NTv3 650M (pos),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291430,RNA-seq
+0.8841373324394226,NTv3 650M (pos),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291431,RNA-seq
+0.8746727705001831,NTv3 650M (pos),2.0,RNA_seq (DPA15_fruit),tomato,SRX29291442,RNA-seq
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+0.9037920236587524,NTv3 650M (pos),2.0,RNA_seq (DPA5_fruit),tomato,SRX29291441,RNA-seq
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+0.8582074642181396,NTv3 650M (pos),2.0,RNA_seq (anthesis_fruit),tomato,SRX29291438,RNA-seq
+0.8407872319221497,NTv3 650M (pos),2.0,RNA_seq (anthesis_fruit),tomato,SRX29291439,RNA-seq
+0.843441903591156,NTv3 650M (pos),2.0,RNA_seq (anthesis_fruit),tomato,SRX29291440,RNA-seq
+0.5302762985229492,NTv3 650M (pos),2.0,ATAC_seq (daa10_fruit),tomato,SRX27799731,ATAC-seq
+0.4703091979026794,NTv3 650M (pos),2.0,ATAC_seq (daa3_fruit),tomato,SRX27799719,ATAC-seq
+0.6039619445800781,NTv3 650M (pos),2.0,ATAC_seq (daa5_fruit),tomato,SRX27799727,ATAC-seq
+0.4973532855510711,NTv3 650M (pos),2.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
+0.4723750054836273,NTv3 650M (pos),2.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
+0.48711958527565,NTv3 650M (pos),2.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
 0.5308845043182373,NTv2 500M,34.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
 0.528399646282196,NTv2 500M,34.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
 0.5361722707748413,NTv2 500M,34.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
@@ -2547,26 +2535,26 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.4587555229663849,NTv3 650M (pre),5.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
 0.4219962954521179,NTv3 650M (pre),5.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
 0.4382128417491913,NTv3 650M (pre),5.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
-0.894802451133728,NTv3 650M (post),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
-0.8989258408546448,NTv3 650M (post),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
-0.8930976390838623,NTv3 650M (post),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
-0.8766103982925415,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291430,RNA-seq
-0.8871738314628601,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291431,RNA-seq
-0.8847330808639526,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291442,RNA-seq
-0.8630269765853882,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291445,RNA-seq
-0.9082212448120116,NTv3 650M (post),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291441,RNA-seq
-0.9004700779914856,NTv3 650M (post),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291443,RNA-seq
-0.9024705290794371,NTv3 650M (post),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291444,RNA-seq
-0.409673273563385,NTv3 650M (post),5.0,ATAC_seq (anthesis_fruit),tomato,SRX27799703,ATAC-seq
-0.8662090301513672,NTv3 650M (post),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291438,RNA-seq
-0.8483365178108215,NTv3 650M (post),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291439,RNA-seq
-0.8528135418891907,NTv3 650M (post),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291440,RNA-seq
-0.5110035538673401,NTv3 650M (post),5.0,ATAC_seq (daa10_fruit),tomato,SRX27799731,ATAC-seq
-0.4125751256942749,NTv3 650M (post),5.0,ATAC_seq (daa3_fruit),tomato,SRX27799719,ATAC-seq
-0.6120463609695435,NTv3 650M (post),5.0,ATAC_seq (daa5_fruit),tomato,SRX27799727,ATAC-seq
-0.4395154118537903,NTv3 650M (post),5.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
-0.4006953835487366,NTv3 650M (post),5.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
-0.431672990322113,NTv3 650M (post),5.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
+0.894802451133728,NTv3 650M (pos),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
+0.8989258408546448,NTv3 650M (pos),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
+0.8930976390838623,NTv3 650M (pos),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
+0.8766103982925415,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291430,RNA-seq
+0.8871738314628601,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291431,RNA-seq
+0.8847330808639526,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291442,RNA-seq
+0.8630269765853882,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291445,RNA-seq
+0.9082212448120116,NTv3 650M (pos),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291441,RNA-seq
+0.9004700779914856,NTv3 650M (pos),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291443,RNA-seq
+0.9024705290794371,NTv3 650M (pos),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291444,RNA-seq
+0.409673273563385,NTv3 650M (pos),5.0,ATAC_seq (anthesis_fruit),tomato,SRX27799703,ATAC-seq
+0.8662090301513672,NTv3 650M (pos),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291438,RNA-seq
+0.8483365178108215,NTv3 650M (pos),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291439,RNA-seq
+0.8528135418891907,NTv3 650M (pos),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291440,RNA-seq
+0.5110035538673401,NTv3 650M (pos),5.0,ATAC_seq (daa10_fruit),tomato,SRX27799731,ATAC-seq
+0.4125751256942749,NTv3 650M (pos),5.0,ATAC_seq (daa3_fruit),tomato,SRX27799719,ATAC-seq
+0.6120463609695435,NTv3 650M (pos),5.0,ATAC_seq (daa5_fruit),tomato,SRX27799727,ATAC-seq
+0.4395154118537903,NTv3 650M (pos),5.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
+0.4006953835487366,NTv3 650M (pos),5.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
+0.431672990322113,NTv3 650M (pos),5.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
 0.5954752564430237,NTv2 500M,41.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
 0.5993300676345825,NTv2 500M,41.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
 0.6012799739837646,NTv2 500M,41.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
@@ -2707,23 +2695,23 @@ pearson correlation,model_name,running_time_hours,track_name_clean,species,datas
 0.4546709656715393,NTv3 650M (pre),4.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
 0.4230354428291321,NTv3 650M (pre),4.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
 0.433363676071167,NTv3 650M (pre),4.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
-0.8780694007873535,NTv3 650M (post),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
-0.8761381506919861,NTv3 650M (post),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
-0.8788752555847168,NTv3 650M (post),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
-0.8878394365310669,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291430,RNA-seq
-0.8868255615234375,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291431,RNA-seq
-0.8806089162826538,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291442,RNA-seq
-0.8647551536560059,NTv3 650M (post),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291445,RNA-seq
-0.881005048751831,NTv3 650M (post),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291441,RNA-seq
-0.8653808236122131,NTv3 650M (post),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291443,RNA-seq
-0.8692577481269836,NTv3 650M (post),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291444,RNA-seq
-0.4410182237625122,NTv3 650M (post),5.0,ATAC_seq (anthesis_fruit),tomato,SRX27799703,ATAC-seq
-0.8455159664154053,NTv3 650M (post),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291438,RNA-seq
-0.8328750133514404,NTv3 650M (post),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291439,RNA-seq
-0.8392651081085205,NTv3 650M (post),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291440,RNA-seq
-0.5192757248878479,NTv3 650M (post),5.0,ATAC_seq (daa10_fruit),tomato,SRX27799731,ATAC-seq
-0.4344106912612915,NTv3 650M (post),5.0,ATAC_seq (daa3_fruit),tomato,SRX27799719,ATAC-seq
-0.6097400188446045,NTv3 650M (post),5.0,ATAC_seq (daa5_fruit),tomato,SRX27799727,ATAC-seq
-0.4675922393798828,NTv3 650M (post),5.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
-0.4368469715118408,NTv3 650M (post),5.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
-0.464601069688797,NTv3 650M (post),5.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq
+0.8780694007873535,NTv3 650M (pos),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291446,RNA-seq
+0.8761381506919861,NTv3 650M (pos),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291447,RNA-seq
+0.8788752555847168,NTv3 650M (pos),5.0,RNA_seq (DPA10_fruit),tomato,SRX29291448,RNA-seq
+0.8878394365310669,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291430,RNA-seq
+0.8868255615234375,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291431,RNA-seq
+0.8806089162826538,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291442,RNA-seq
+0.8647551536560059,NTv3 650M (pos),5.0,RNA_seq (DPA15_fruit),tomato,SRX29291445,RNA-seq
+0.881005048751831,NTv3 650M (pos),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291441,RNA-seq
+0.8653808236122131,NTv3 650M (pos),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291443,RNA-seq
+0.8692577481269836,NTv3 650M (pos),5.0,RNA_seq (DPA5_fruit),tomato,SRX29291444,RNA-seq
+0.4410182237625122,NTv3 650M (pos),5.0,ATAC_seq (anthesis_fruit),tomato,SRX27799703,ATAC-seq
+0.8455159664154053,NTv3 650M (pos),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291438,RNA-seq
+0.8328750133514404,NTv3 650M (pos),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291439,RNA-seq
+0.8392651081085205,NTv3 650M (pos),5.0,RNA_seq (anthesis_fruit),tomato,SRX29291440,RNA-seq
+0.5192757248878479,NTv3 650M (pos),5.0,ATAC_seq (daa10_fruit),tomato,SRX27799731,ATAC-seq
+0.4344106912612915,NTv3 650M (pos),5.0,ATAC_seq (daa3_fruit),tomato,SRX27799719,ATAC-seq
+0.6097400188446045,NTv3 650M (pos),5.0,ATAC_seq (daa5_fruit),tomato,SRX27799727,ATAC-seq
+0.4675922393798828,NTv3 650M (pos),5.0,ATAC_seq (dba3_fruit),tomato,SRX27799722,ATAC-seq
+0.4368469715118408,NTv3 650M (pos),5.0,ATAC_seq (dba7_fruit),tomato,SRX27799718,ATAC-seq
+0.464601069688797,NTv3 650M (pos),5.0,ATAC_seq (leaf),tomato,SRX27799733,ATAC-seq

src/streamlit_app.py

@@ -56,8 +56,35 @@ COLORS = {
     'yellow_3': '#fff08c',   # Lightest yellow
 }
 
+
+ASSAY_TYPE_MAPPING = {
+    'ATAC-seq': 'Chromatin Accessibility',
+    'DNase-seq': 'Chromatin Accessibility',
+    'Histone ChIP-seq': 'Histone modifications',
+    'TF ChIP-seq': 'Chromatin Accessibility',
+    'PRO-cap': 'Transcription initiation',
+    'eCLIP': 'RNA binding sites',
+    'RNA-seq': 'Gene Expression',
+    'ribo-seq': 'mRNA translation',
+    'Annotation': 'Genome Annotation',
+}
+
+ASSAY_COLORS = {
+    'Chromatin Accessibility': '#004697',
+    'Histone modifications': '#cc0000',
+    'Transcription initiation': '#ff9900',
+    'RNA binding sites': '#9933cc',
+    'Gene Expression': '#009900',
+    'mRNA translation': '#ff6699',
+    'Genome Annotation': '#ffcc00',
+    "intron": '#004697',
+    "exon": '#cc0000',
+    "splice acceptor": '#ff9900',
+    "start codon": '#9933cc',
+}
+
 MODEL_COLORS = {
-    "NTv3 650M (post)": COLORS['blue_0'],
+    "NTv3 650M (pos)": COLORS['blue_0'],
     'NTv3 650M (pre)': COLORS['blue_1'],    # #3973fc (Darkest blue)
     'NTv3 100M (pre)': COLORS['blue_2'],    # #7ea4fc (Medium blue)
     'NTv3 8M (pre)': COLORS['blue_3'],      # #c3d5fc (Light blue)
@@ -70,7 +97,7 @@ MODEL_COLORS = {
 }
 
 MODEL_TRAINING_STATUS = {
-    "NTv3 650M (post)": "POST",
+    "NTv3 650M (pos)": "POS",
     "NTv3 650M (pre)": "PRE",
     "NTv3 100M (pre)": "PRE",
     "NTv3 8M (pre)": "PRE",
@@ -167,9 +194,9 @@ def load_expanded_data():
     pearson_df = _normalize_training_hours(pearson_df)
     mcc_df = _normalize_training_hours(mcc_df)
 
-    if "track_name_clean" in pearson_df.columns:
-        pearson_df = pearson_df.drop(columns=["datasets"], errors="ignore")
-        pearson_df = pearson_df.rename(columns={"track_name_clean": "datasets"})
+    #if "track_name_clean" in pearson_df.columns:
+    #    pearson_df = pearson_df.drop(columns=["datasets"], errors="ignore")
+    #    pearson_df = pearson_df.rename(columns={"track_name_clean": "datasets"})
 
     # --- Pearson correlations ---
     # Expect columns: species, assay_type, datasets, model_name, pearson correlation
@@ -180,6 +207,20 @@ def load_expanded_data():
         }
     )
 
+    # --- Keep track_name_clean available (for head-to-head only later) ---
+    pearson_track_map = None
+    if "track_name_clean" in pearson_df.columns:
+        map_keys = ["species", "datasets"]
+        if "assay_type" in pearson_df.columns:
+            map_keys.append("assay_type")
+
+        pearson_track_map = (
+            pearson_df[map_keys + ["track_name_clean"]]
+            .dropna(subset=["track_name_clean"])
+            .drop_duplicates()
+    )
+
+
     pearson_group_cols = ["species", "datasets", "Model"]
     if "assay_type" in pearson_df.columns:
         pearson_group_cols.append("assay_type")
@@ -188,12 +229,27 @@ def load_expanded_data():
     if "GPU hours" in pearson_df.columns:
         agg_cols["GPU hours"] = "mean"
 
+    # --- after aggregation ---
     pearson_df = (
         pearson_df
         .groupby(pearson_group_cols, as_index=False, dropna=False)
         .agg(agg_cols)
     )
 
+    # ✅ Merge track_name_clean back FIRST (assay_type still raw here)
+    if pearson_track_map is not None:
+        pearson_df = pearson_df.merge(pearson_track_map, on=map_keys, how="left")
+
+    # ✅ THEN map assay_type to your categories
+    if "assay_type" in pearson_df.columns:
+        pearson_df["assay_type"] = (
+            pearson_df["assay_type"]
+            .map(ASSAY_TYPE_MAPPING)
+            .fillna("Other")
+        )
+
+
+
     # --- MCC (bed tracks) ---
     # Expect columns: species, datasets, model_name, MCC
     mcc_df = mcc_df.rename(
@@ -506,11 +562,19 @@ def build_pairwise_scatter_df(
     Returns a per-track dataframe with columns:
       Track, Model A, Model B, (optional) species, (optional) assay_type, datasets
     Where each row corresponds to a specific track (datasets [+ assay_type]).
+
+    Special case:
+      If `track_name_clean` exists (typically for bigwig Functional Tracks),
+      we use it ONLY for the head-to-head "Track" label (and track identity),
+      while keeping the rest of the app using `datasets`.
     """
     cfg = _BENCHMARKS[benchmark_name]
 
-    # Filter using the same UI toggles, but ensure the chosen models are included
-    models_for_filter = list(set(selected_models + [model_a, model_b])) if selected_models else [model_a, model_b]
+    # Ensure chosen models are included even if toggles exclude them
+    models_for_filter = (
+        list(set(selected_models + [model_a, model_b]))
+        if selected_models else [model_a, model_b]
+    )
 
     df = filter_base_df(
         benchmark_name,
@@ -523,14 +587,17 @@ def build_pairwise_scatter_df(
     if df.empty:
         return pd.DataFrame()
 
+    # Prefer track_name_clean for BigWig head-to-head labeling ONLY
+    # (fallback to datasets if missing)
+    track_id_col = "track_name_clean" if "track_name_clean" in df.columns else "datasets"
+
     # Define what “a specific track” means
-    track_cols = ["datasets"]
+    track_cols = [track_id_col]
     if cfg.get("has_assay_type", False) and "assay_type" in df.columns:
-        track_cols = ["assay_type", "datasets"]
+        track_cols = ["assay_type", track_id_col]
 
-    # (Optional) keep species in hover if multiple are selected
+    # Keep species in hover if multiple are selected
     keep_species = "species" in df.columns and (selected_species is None or len(selected_species) != 1)
-
     id_cols = (["species"] if keep_species else []) + track_cols
 
     # Pivot into two model columns
@@ -540,21 +607,28 @@ def build_pairwise_scatter_df(
         .reset_index()
     )
 
-    # Require both values to exist for a dot
     if model_a not in wide.columns or model_b not in wide.columns:
         return pd.DataFrame()
 
     wide = wide.dropna(subset=[model_a, model_b])
 
-    # Nice “Track” label for display
+    # Create a nice "Track" label for display (uses track_name_clean if available)
     if "assay_type" in wide.columns:
-        wide["Track"] = wide["assay_type"].astype(str) + " / " + wide["datasets"].astype(str)
+        wide["Track"] = wide["assay_type"].astype(str) + " / " + wide[track_id_col].astype(str)
     else:
-        wide["Track"] = wide["datasets"].astype(str)
+        wide["Track"] = wide[track_id_col].astype(str)
 
     # Rename for plotting
     wide = wide.rename(columns={model_a: "Model A", model_b: "Model B"})
 
+    # If we used track_name_clean, keep datasets around too (if present) for hover/debug
+    # (nothing breaks if it's absent)
+    if track_id_col == "track_name_clean" and "datasets" in df.columns and "datasets" not in wide.columns:
+        # merge back datasets for hover only
+        merge_keys = id_cols.copy()
+        extra = df[merge_keys + ["datasets"]].drop_duplicates()
+        wide = wide.merge(extra, on=merge_keys, how="left")
+
     return wide
 
 
@@ -897,15 +971,22 @@ def main():
             axis_range = [min_v - pad, max_v + pad]
             tick_step = (axis_range[1] - axis_range[0]) / 5
 
-            hover_cols = ["Track"]
-            for c in ["species", "assay_type", "datasets"]:
-                if c in scatter_df.columns:
-                    hover_cols.append(c)
+            hover_cols = []
+
+            # Prefer track_name_clean; fall back to Track if not present
+            if "track_name_clean" in scatter_df.columns:
+                hover_cols.append("track_name_clean")
+            else:
+                hover_cols.append("datasets")
+
+            color_col = "assay_type" if "assay_type" in scatter_df.columns else "datasets"
 
             fig_scatter = px.scatter(
                 scatter_df,
                 x="Model B",
                 y="Model A",
+                color=color_col,
+                color_discrete_map=ASSAY_COLORS,
                 hover_name="Track",
                 hover_data=hover_cols,
             )
@@ -939,6 +1020,19 @@ def main():
                 paper_bgcolor="rgba(0,0,0,0)",
             )
 
+            fig_scatter.update_layout(
+                legend=dict(
+                    title="Assay type",
+                    x=0.98,
+                    y=0.1,
+                    xanchor="right",
+                    yanchor="bottom",
+                    bgcolor="rgba(255,255,255,0.2)",  # semi-transparent white
+                    bordercolor="rgba(0,0,0,0.2)",
+                    borderwidth=1,
+                )
+            )
+
             st.plotly_chart(fig_scatter, use_container_width=True)
 
     with right:
@@ -960,28 +1054,33 @@ def main():
                 x="GPU hours",
                 y="Performance",
                 text="Model",
+                color="Model",                       # 👈 color by model
+                color_discrete_map=MODEL_COLORS,     # 👈 your palette
                 hover_data=["Model", "GPU hours", "Performance"],
             )
+
             fig_conv.update_traces(textposition="top center")
             fig_conv.update_layout(
-                height=630,  # match left panel height
-                xaxis=dict(
-                    title="GPU hours",
-                    type="log",          # 👈 log scale
-                ),
-                yaxis=dict(
-                    title=cfg["metric_label"],
-                ),
+                height=630,
+                xaxis=dict(title="GPU hours", type="log"),
+                yaxis=dict(title=cfg["metric_label"]),
                 plot_bgcolor="rgba(0,0,0,0)",
                 paper_bgcolor="rgba(0,0,0,0)",
+                showlegend=False,
             )
+
             fig_conv.update_xaxes(
                 type="log",
                 range=[0, np.log10(conv_df["GPU hours"].max())],  # log10(1) = 0
                 title="GPU hours (log scale)",
             )
+
+            # optional: hide legend if labels already on points
+            # fig_conv.update_layout(showlegend=False)
+
             st.plotly_chart(fig_conv, use_container_width=True)
 
+
     # ------------------------------------------------------------------
     # Violin (full width, below)
     # ------------------------------------------------------------------