Update README.md

README.md

@@ -3,135 +3,137 @@ configs:
 - config_name: expression_HEK
   data_files:
   - split: train
-    path: "expression_level/HEK_10fold_cv_split.tsv"
+    path: expression_level/HEK_10fold_cv_split.tsv
 - config_name: expression_Muscle
   data_files:
   - split: train
-    path: "expression_level/Muscle_10fold_cv_split.tsv"
+    path: expression_level/Muscle_10fold_cv_split.tsv
 - config_name: expression_pc3
   data_files:
   - split: train
-    path: "expression_level/pc3_10fold_cv_split.tsv"
+    path: expression_level/pc3_10fold_cv_split.tsv
 - config_name: translation_efficiency_HEK
   data_files:
   - split: train
-    path: "translation_efficiency/HEK_10fold_cv_split.tsv"
+    path: translation_efficiency/HEK_10fold_cv_split.tsv
 - config_name: translation_efficiency_Muscle
   data_files:
   - split: train
-    path: "translation_efficiency/Muscle_10fold_cv_split.tsv"
+    path: translation_efficiency/Muscle_10fold_cv_split.tsv
 - config_name: translation_efficiency_pc3
   data_files:
   - split: train
-    path: "translation_efficiency/pc3_10fold_cv_split.tsv"
+    path: translation_efficiency/pc3_10fold_cv_split.tsv
 - config_name: modification_site
   data_files:
   - split: train
-    path: "modification_site_prediction/train.tsv"
+    path: modification_site_prediction/train.tsv
   - split: validation
-    path: "modification_site_prediction/valid.tsv"
+    path: modification_site_prediction/valid.tsv
   - split: test
-    path: "modification_site_prediction/test.tsv"
+    path: modification_site_prediction/test.tsv
 - config_name: ncrna_family_bnoise0
   data_files:
   - split: train
-    path: "ncrna_family_classification/bnoise0/train.tsv"
+    path: ncrna_family_classification/bnoise0/train.tsv
   - split: validation
-    path: "ncrna_family_classification/bnoise0/valid.tsv"
+    path: ncrna_family_classification/bnoise0/valid.tsv
   - split: test
-    path: "ncrna_family_classification/bnoise0/test.tsv"
+    path: ncrna_family_classification/bnoise0/test.tsv
 - config_name: ncrna_family_bnoise200
   data_files:
   - split: train
-    path: "ncrna_family_classification/bnoise200/train.tsv"
+    path: ncrna_family_classification/bnoise200/train.tsv
   - split: validation
-    path: "ncrna_family_classification/bnoise200/valid.tsv"
+    path: ncrna_family_classification/bnoise200/valid.tsv
   - split: test
-    path: "ncrna_family_classification/bnoise200/test.tsv"
+    path: ncrna_family_classification/bnoise200/test.tsv
 - config_name: protein_abundance_athaliana
   data_files:
   - split: train
-    path: "protein_abundance/athaliana_5fold_cv_split.tsv"
+    path: protein_abundance/athaliana_5fold_cv_split.tsv
 - config_name: protein_abundance_dmelanogaster
   data_files:
   - split: train
-    path: "protein_abundance/dmelanogaster_5fold_cv_split.tsv"
+    path: protein_abundance/dmelanogaster_5fold_cv_split.tsv
 - config_name: protein_abundance_ecoli
   data_files:
   - split: train
-    path: "protein_abundance/ecoli_5fold_cv_split.tsv"
+    path: protein_abundance/ecoli_5fold_cv_split.tsv
 - config_name: protein_abundance_hsapiens
   data_files:
   - split: train
-    path: "protein_abundance/hsapiens_5fold_cv_split.tsv"
+    path: protein_abundance/hsapiens_5fold_cv_split.tsv
 - config_name: protein_abundance_scerevisiae
   data_files:
   - split: train
-    path: "protein_abundance/scerevisiae_5fold_cv_split.tsv"
+    path: protein_abundance/scerevisiae_5fold_cv_split.tsv
 - config_name: splice_site_acceptor
   data_files:
   - split: train
-    path: "splice_site_prediction/acceptor/train.tsv"
+    path: splice_site_prediction/acceptor/train.tsv
   - split: validation
-    path: "splice_site_prediction/acceptor/valid.tsv"
+    path: splice_site_prediction/acceptor/valid.tsv
   - split: test_danio
-    path: "splice_site_prediction/acceptor/test_Danio.tsv"
+    path: splice_site_prediction/acceptor/test_Danio.tsv
   - split: test_fly
-    path: "splice_site_prediction/acceptor/test_Fly.tsv"
+    path: splice_site_prediction/acceptor/test_Fly.tsv
   - split: test_thaliana
-    path: "splice_site_prediction/acceptor/test_Thaliana.tsv"
+    path: splice_site_prediction/acceptor/test_Thaliana.tsv
   - split: test_worm
-    path: "splice_site_prediction/acceptor/test_Worm.tsv"
+    path: splice_site_prediction/acceptor/test_Worm.tsv
 - config_name: splice_site_donor
   data_files:
   - split: train
-    path: "splice_site_prediction/donor/train.tsv"
+    path: splice_site_prediction/donor/train.tsv
   - split: validation
-    path: "splice_site_prediction/donor/valid.tsv"
+    path: splice_site_prediction/donor/valid.tsv
   - split: test_danio
-    path: "splice_site_prediction/donor/test_Danio.tsv"
+    path: splice_site_prediction/donor/test_Danio.tsv
   - split: test_fly
-    path: "splice_site_prediction/donor/test_Fly.tsv"
+    path: splice_site_prediction/donor/test_Fly.tsv
   - split: test_thaliana
-    path: "splice_site_prediction/donor/test_Thaliana.tsv"
+    path: splice_site_prediction/donor/test_Thaliana.tsv
   - split: test_worm
-    path: "splice_site_prediction/donor/test_Worm.tsv"
+    path: splice_site_prediction/donor/test_Worm.tsv
 - config_name: transcript_abundance_athaliana
   data_files:
   - split: train
-    path: "transcript_abundance/athaliana_5fold_cv_split.tsv"
+    path: transcript_abundance/athaliana_5fold_cv_split.tsv
 - config_name: transcript_abundance_dmelanogaster
   data_files:
   - split: train
-    path: "transcript_abundance/dmelanogaster_5fold_cv_split.tsv"
+    path: transcript_abundance/dmelanogaster_5fold_cv_split.tsv
 - config_name: transcript_abundance_ecoli
   data_files:
   - split: train
-    path: "transcript_abundance/ecoli_5fold_cv_split.tsv"
+    path: transcript_abundance/ecoli_5fold_cv_split.tsv
 - config_name: transcript_abundance_hsapiens
   data_files:
   - split: train
-    path: "transcript_abundance/hsapiens_5fold_cv_split.tsv"
+    path: transcript_abundance/hsapiens_5fold_cv_split.tsv
 - config_name: transcript_abundance_hvolcanii
   data_files:
   - split: train
-    path: "transcript_abundance/hvolcanii_5fold_cv_split.tsv"
+    path: transcript_abundance/hvolcanii_5fold_cv_split.tsv
 - config_name: transcript_abundance_ppastoris
   data_files:
   - split: train
-    path: "transcript_abundance/ppastoris_5fold_cv_split.tsv"
+    path: transcript_abundance/ppastoris_5fold_cv_split.tsv
 - config_name: transcript_abundance_scerevisiae
   data_files:
   - split: train
-    path: "transcript_abundance/scerevisiae_5fold_cv_split.tsv"
+    path: transcript_abundance/scerevisiae_5fold_cv_split.tsv
 - config_name: mean_ribosome_load
   data_files:
   - split: train
-    path: "mean_ribosome_load/train.tsv"
+    path: mean_ribosome_load/train.tsv
   - split: validation
-    path: "mean_ribosome_load/validation_random7600.tsv"
+    path: mean_ribosome_load/validation_random7600.tsv
   - split: test
-    path: "mean_ribosome_load/test_human7600.tsv"
+    path: mean_ribosome_load/test_human7600.tsv
+tags:
+- biology
 ---
 
 # AIDO.RNA Benchmark Datasets
@@ -166,14 +168,14 @@ configs:
 
 ## RNA function prediction tasks
 The datasets listed below are collected following the setting in Wang et al. (2023) [4].
-* Cross-species splice site prediction
+* Cross-species splice site prediction [5]
   * 2 datasets: acceptor, donor
   * 4 test species: zebrafish, fruit fly, worm, and plant
   * input sequence: pre-mRNA fragment
-* ncRNA family classification
+* ncRNA family classification [6]
   * 2 datasets: boundary noise 0, boundary noise 200
   * input sequence: small noncoding RNA with different level of boundary noise
-* RNA modification site prediction
+* RNA modification site prediction [7]
   * 12 labels (modification sites): Am, Cm, Gm, Tm, m1A, m5C, m5U, m6A, m6Am, m7G, Φ, and I.
 
 
@@ -181,4 +183,7 @@ The datasets listed below are collected following the setting in Wang et al. (20
 1. Yanyi Chu, Dan Yu, Yupeng Li, Kaixuan Huang, Yue Shen, Le Cong, Jason Zhang, and Mengdi Wang. A 5 utr language model for decoding untranslated regions of mrna and function predictions. Nature Machine Intelligence, pages 1–12, 2024.
 2. Paul J Sample, Ban Wang, David W Reid, Vlad Presnyak, Iain J McFadyen, David R Morris, and Georg Seelig. Human 5 utr design and variant effect prediction from a massively parallel translation assay. Nature biotechnology, 37(7):803–809, 2019.
 3. Carlos Outeiral and Charlotte M Deane. Codon language embeddings provide strong signals for use in protein engineering. Nature Machine Intelligence, 6(2):170–179, 2024.
-4. Xi Wang, Ruichu Gu, Zhiyuan Chen, Yongge Li, Xiaohong Ji, Guolin Ke, and HanWen. Uni-rna: universal pre-trained models revolutionize rna research. bioRxiv, pages 2023–07, 2023.
+4. Xi Wang, Ruichu Gu, Zhiyuan Chen, Yongge Li, Xiaohong Ji, Guolin Ke, and HanWen. Uni-rna: universal pre-trained models revolutionize rna research. bioRxiv, pages 2023–07, 2023.
+5. Nicolas Scalzitti, Arnaud Kress, Romain Orhand, Thomas Weber, Luc Moulinier, Anne Jeannin-Girardon, Pierre Collet, Olivier Poch, and Julie D Thompson. Spliceator: Multi-species splice site prediction using convolutional neural networks. BMC bioinformatics, 22(1):1–26, 2021.
+6. Teresa Maria Rosaria Noviello, Francesco Ceccarelli, Michele Ceccarelli, and Luigi Cerulo. Deep learning predicts short non-coding rna functions from only raw sequence data. PLoS computational biology, 16(11):e1008415, 2020.
+7. Zitao Song, Daiyun Huang, Bowen Song, Kunqi Chen, Yiyou Song, Gang Liu, Jionglong Su, João Pedro de Magalhães, Daniel J Rigden, and Jia Meng. Attention-based multi-label neural networks for integrated prediction and interpretation of twelve widely occurring rna modifications. Nature communications, 12(1):4011, 2021.