UniProt: a worldwide hub of protein knowledge

UniProt: the Universal Protein knowledgebase

Apweiler, R. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh131 · Cited by 7,535 · see citing works

UniProt: the universal protein knowledgebase

The UniProt Consortium (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1099 · Cited by 4,436 · see citing works

A METTL3–METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation

Liu, J., Yue, Y., Han, D., Wang, X., Fu, Y., Zhang, L., Jia, G., Yu, M., Lu, Z., Deng, X., et al. (2014) · Nature Chemical Biology · doi:10.1038/nchembio.1432 · Cited by 3,433 · see citing works

Ensembl 2018

Zerbino, D. R., Achuthan, P., Akanni, W., Amode, M. R., Barrell, D., Bhai, J., Billis, K., Cummins, C., Gall, A., Girón, C. G., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1098 · Cited by 2,605 · see citing works

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

Suzek, B. E., Wang, Y., Huang, H., McGarvey, P. B., Wu, C. H., & the UniProt Consortium (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu739 · Cited by 1,928 · see citing works

Structural Basis for Cooperative Function of Mettl3 and Mettl14 Methyltransferases

Wang, P., Doxtader, K. A., & Nam, Y. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.05.041 · Cited by 1,256 · see citing works

Structural basis of N6-adenosine methylation by the METTL3–METTL14 complex

Wang, X., Feng, J. Q., Xue, Y. C., Guan, Z., Zhang, D., Liu, Z., Gong, Z., Wang, Q., Huang, J. B., Tang, C., et al. (2016) · Nature · doi:10.1038/nature18298 · Cited by 1,218 · see citing works

ChEBI in 2016: Improved services and an expanding collection of metabolites

Hastings, J., Owen, G., Dekker, A., Ennis, M., Kale, N., Muthukrishnan, V., Turner, S., Swainston, N., Mendes, P., & Steinbeck, C. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1031 · Cited by 1,083 · see citing works

VIRMA mediates preferential m6A mRNA methylation in 3′UTR and near stop codon and associates with alternative polyadenylation

Yue, Y., Liu, J., Cui, X., Cao, J., Luo, G., Zhang, Z., Cheng, T., Gao, M., Shu, X., Ma, H., et al. (2018) · Cell Discovery · doi:10.1038/s41421-018-0019-0 · Cited by 960 · see citing works

The Gene Ontology project in 2008

The Gene Ontology Consortium (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm883 · Cited by 776 · see citing works

WormBase ParaSite − a comprehensive resource for helminth genomics

Howe, K., Bolt, B. J., Shafie, M., Kersey, P. J., & Berriman, M. (2016) · Molecular and Biochemical Parasitology · doi:10.1016/j.molbiopara.2016.11.005 · Cited by 751 · see citing works

The International Nucleotide Sequence Database Collaboration

Karsch‐Mizrachi, I., Nakamura, Y., & Cochrane, G. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1006 · Cited by 717 · see citing works

ViPR: an open bioinformatics database and analysis resource for virology research

Pickett, B. E., Sadat, E. L., Zhang, Y., Noronha, J. M., Squires, R. B., Hunt, V., Liu, M., Kumar, S., Zaremba, S., Gu, Z., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr859 · Cited by 677 · see citing works

COMPARTMENTS: unification and visualization of protein subcellular localization evidence

Binder, J. X., Pletscher-Frankild, S., Tsafou, K., Stolte, C., O’Donoghue, S. I., Schneider, R., & Jensen, L. J. (2014) · Database · doi:10.1093/database/bau012 · Cited by 649 · see citing works

VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases

Giraldo-Calderón, G. I., Emrich, S., MacCallum, R. M., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1117 · Cited by 618 · see citing works

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium

Orchard, S. E., Kerrien, S., Abbani, S., Aranda, B., Bhate, J., Bidwell, S. L., Bridge, A. J., Briganti, L., Brinkman, F. S. L., Cesareni, G., et al. (2012) · Nature Methods · doi:10.1038/nmeth.1931 · Cited by 538 · see citing works

Structural insights into the molecular mechanism of the m6A writer complex

Sledz, P., & Jínek, M. (2016) · eLife · doi:10.7554/elife.18434 · Cited by 533 · see citing works

The Papillomavirus Episteme: a major update to the papillomavirus sequence database

Doorslaer, K. V., Li, Z., Xirasagar, S., Maes, P., Kaminsky, D., Liou, D., Sun, Q., Kaur, R., Huyen, Y., & McBride, A. A. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw879 · Cited by 424 · see citing works

Influenza Research Database: An integrated bioinformatics resource for influenza virus research

Zhang, Y., Aevermann, B. D., Anderson, T. K., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw857 · Cited by 346 · see citing works

Standardized benchmarking in the quest for orthologs

Quest for Orthologs consortium, Altenhoff, A. M., Boeckmann, B., Capella-Gutierrez, S., Dalquen, D. A., DeLuca, T., Forslund, K., Huerta-Cepas, J., Linard, B., Pereira, C., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3830 · Cited by 214 · see citing works

HBVdb: a knowledge database for Hepatitis B Virus

Hayer, J., Jadeau, F., Deléage, G., Kay, A., Zoulim, F., & Combet, C. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1022 · Cited by 212 · see citing works

EBI Metagenomics in 2017: enriching the analysis of microbial communities, from sequence reads to assemblies

Mitchell, A., Scheremetjew, M., Denise, H., Potter, S., Tarkowska, A., Qureshi, M., Salazar, G. A., Pesseat, S., Boland, M. A., Hunter, F. M. I., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx967 · Cited by 208 · see citing works

The international nucleotide sequence database collaboration

Karsch-Mizrachi, I., Takagi, T., Cochrane, G., & on behalf of the International Nucleotide Sequence Database Collaboration (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1097 · Cited by 190 · see citing works

On expert curation and scalability: UniProtKB/Swiss-Prot as a case study

Poux, S., Arighi, C. N., Magrane, M., Bateman, A., Wei, C.-H., Lu, Z., Boutet, E., Bye-A-Jee, H., Famiglietti, M. L., Roechert, B., et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx439 · Cited by 135 · see citing works

The complex portal - an encyclopaedia of macromolecular complexes

Meldal, B., Forner, O., Costanzo, M. C., Dana, J. M., Demeter, J., Dumousseau, M., Dwight, S. S., Gaulton, A., Licata, L., Melidoni, A. N., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku975 · Cited by 114 · see citing works

Representative Proteomes: A Stable, Scalable and Unbiased Proteome Set for Sequence Analysis and Functional Annotation

Chen, C., Natale, D. A., Finn, R. D., Huang, H., Zhang, J., Wu, C. H., & Mazumder, R. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018910 · Cited by 101 · see citing works

The Proteins API: accessing key integrated protein and genome information

Nightingale, A., Antunes, R., Alpi, E., Bursteinas, B., Gonzales, L. J. D. C., Liu, W., Luo, J., Qi, G., Turner, E., & Martin, M. J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx237 · Cited by 97 · see citing works

tmVar 2.0: integrating genomic variant information from literature with dbSNP and ClinVar for precision medicine

Wei, C.-H., Phan, L. D., Feltz, J., et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx541 · Cited by 97 · see citing works

Uniform resolution of compact identifiers for biomedical data

Wimalaratne, S., Juty, N., Kunze, J., Janée, G., McMurry, J. A., Beard, N., Jiménez, R. C., Grethe, J. S., Hermjakob, H., Martone, M. E., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.29 · Cited by 61 · see citing works

UniProt-DAAC: domain architecture alignment and classification, a new method for automatic functional annotation in UniProtKB

Doğan, T., MacDougall, A., Saidi, R., Poggioli, D., Bateman, A. G., O’Donovan, C., & Martin, M. J. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw114 · Cited by 48 · see citing works

Construction of protein phosphorylation networks by data mining, text mining and ontology integration: analysis of the spindle checkpoint

ROSS, K. E., Arighi, C. N., Ren, J. D., et al. (2013) · Database · doi:10.1093/database/bat038 · Cited by 22 · see citing works

eGenPub, a text mining system for extending computationally mapped bibliography for UniProt Knowledgebase by capturing centrality

Ding, R., Boutet, E., Lieberherr, D., Schneider, M., Tognolli, M., Wu, C. H., Vijay‐Shanker, K., & Arighi, C. N. (2017) · Database · doi:10.1093/database/bax081 · Cited by 8 · see citing works

Computational clustering for viral reference proteomes

Chen, C., Huang, H., Mazumder, R., et al. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw110 · Cited by 4 · see citing works

ColabFold - Making protein folding accessible to all

Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2021) · doi:10.1101/2021.08.15.456425 · Cited by 9,391 · see citing works

The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

Szklarczyk, D., Gable, A. L., Nastou, K. C., Lyon, D., Kirsch, R., Pyysalo, S., Doncheva, N. T., Legeay, M., Fang, T., Bork, P., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1074 · Cited by 8,056 · see citing works

UniProt: the universal protein knowledgebase in 2021

The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1100 · Cited by 6,372 · see citing works

g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

Raudvere, U., Kolberg, L., Kuzmin, I., Arak, T., Adler, P., Peterson, H., & Vilo, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz369 · Cited by 5,045 · see citing works

PubChem in 2021: new data content and improved web interfaces

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa971 · Cited by 3,953 · see citing works

Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3

Beghini, F., McIver, L. J., Blanco-Míguez, A., Dubois, L., Asnicar, F., Maharjan, S., Mailyan, A., Manghi, P., Scholz, M., Thomas, A. M., et al. (2021) · eLife · doi:10.7554/elife.65088 · Cited by 2,303 · see citing works

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Elnaggar, A., Heinzinger, M., Dallago, C., Rehawi, G., Wang, Y., Jones, L., Gibbs, T., Feher, T., Angerer, C., Steinegger, M., et al. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3095381 · Cited by 2,329 · see citing works

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences

Burley, S. K., Bhikadiya, C., Bi, C., Bittrich, S., Chen, L., Crichlow, G. V., Christie, C. H., Dalenberg, K., Di Costanzo, L., Duarte, J. M., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1038 · Cited by 1,581 · see citing works

GENCODE 2021

Frankish, A., Diekhans, M., Jungreis, I., Lagarde, J., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J., Barnes, I., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1087 · Cited by 1,334 · see citing works

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse

Koopmans, F., van Nierop, P., Andres-Alonso, M., Byrnes, A., Cijsouw, T., Coba, M. P., Cornelisse, L. N., Farrell, R. J., Goldschmidt, H. L., Howrigan, D. P., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.05.002 · Cited by 938 · see citing works

Using machine learning approaches for multi-omics data analysis: A review

Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903 · see citing works

BRENDA, the ELIXIR core data resource in 2021: new developments and updates

Chang, A., Jeske, L., Ulbrich, S., Hofmann, J., Koblitz, J., Schomburg, I., Neumann-Schaal, M., Jahn, D., & Schomburg, D. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1025 · Cited by 789 · see citing works

Protein Sequence Analysis Using the MPI Bioinformatics Toolkit

Gabler, F., Nam, S., Till, S., Mirdita, M., Steinegger, M., Söding, J., Lupas, A. N., & Alva, V. (2020) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.108 · Cited by 831 · see citing works

Disease variant prediction with deep generative models of evolutionary data

Frazer, J., Notin, P., Dias, M., Gomez, A., Min, J. K., Brock, K., Gal, Y., & Marks, D. S. (2021) · Nature · doi:10.1038/s41586-021-04043-8 · Cited by 791 · see citing works

Evaluating Protein Transfer Learning with TAPE

Rao, R., Bhattacharya, N., Thomas, N., Duan, Y., Chen, X., Canny, J., Abbeel, P., & Song, Y. S. (2019) · doi:10.1101/676825 · Cited by 719 · see citing works

Rethinking Attention with Performers

Choromanski, K., Likhosherstov, V., Dohan, D., Song, X., Gane, A., Sarlos, T., Hawkins, P., Davis, J., Mohiuddin, A., Kaiser, L., et al. (2020) · arXiv · doi:10.48550/arxiv.2009.14794 · Cited by 695 · see citing works

Isolation of an archaeon at the prokaryote–eukaryote interface

Imachi, H., Nobu, M. K., Nakahara, N., Morono, Y., Ogawara, M., Takaki, Y., Takano, Y., Uematsu, K., Ikuta, T., Ito, M., et al. (2020) · Nature · doi:10.1038/s41586-019-1916-6 · Cited by 624 · see citing works

NAD+ homeostasis in health and disease

Katsyuba, E., Romani, M., Hofer, D., & Auwerx, J. (2020) · Nature Metabolism · doi:10.1038/s42255-019-0161-5 · Cited by 627 · see citing works

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection

Messner, C. B., Demichev, V., Wendisch, D., Michalick, L., White, M., Freiwald, A., Textoris-Taube, K., Vernardis, S. I., Egger, A.-S., Kreidl, M., et al. (2020) · Cell Systems · doi:10.1016/j.cels.2020.05.012 · Cited by 561 · see citing works

Proteogenomic Characterization of Endometrial Carcinoma

Dou, Y., Kawaler, E. A., Cui Zhou, D., Gritsenko, M. A., Huang, C., Blumenberg, L., Karpova, A., Petyuk, V. A., Savage, S. R., Satpathy, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.01.026 · Cited by 485 · see citing works

CATH: increased structural coverage of functional space

Sillitoe, I., Bordin, N., Dawson, N., Waman, V. P., Ashford, P., Scholes, H. M., Pang, C. S. M., Woodridge, L., Rauer, C., Sen, N., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1079 · Cited by 509 · see citing works

Autism genes converge on asynchronous development of shared neuron classes

Paulsen, B., Velasco, S., Kedaigle, A. J., Pigoni, M., Quadrato, G., Deo, A. J., Adiconis, X., Uzquiano, A., Sartore, R., Yang, S. M., et al. (2022) · Nature · doi:10.1038/s41586-021-04358-6 · Cited by 439 · see citing works

Learning the protein language: Evolution, structure, and function

Bepler, T., & Berger, B. (2021) · Cell Systems · doi:10.1016/j.cels.2021.05.017 · Cited by 483 · see citing works

ProGen2: Exploring the boundaries of protein language models

Nijkamp, E., Ruffolo, J. A., Weinstein, E. N., Naik, N., & Madani, A. (2023) · Cell Systems · doi:10.1016/j.cels.2023.10.002 · Cited by 480 · see citing works

Identification of bacteria-derived HLA-bound peptides in melanoma

Kalaora, S., Nagler, A., Nejman, D., Alon, M., Barbolin, C., Barnea, E., Ketelaars, S. L. C., Cheng, K., Vervier, K., Shental, N., et al. (2021) · Nature · doi:10.1038/s41586-021-03368-8 · Cited by 457 · see citing works

Protein posttranslational modifications in health and diseases: Functions, regulatory mechanisms, and therapeutic implications

Zhong, Q., Xiao, X., Qiu, Y., Xu, Z., Chen, C., Chong, B., Zhao, X., Hai, S., Li, S., An, Z., et al. (2023) · MedComm · doi:10.1002/mco2.261 · Cited by 442 · see citing works

Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration

Moiseeva, V., Cisneros, A., Sica, V., Deryagin, O., Lai, Y., Jung, S., Andrés, E., An, J., Segalés, J., Ortet, L., et al. (2023) · Nature · doi:10.1038/s41586-022-05535-x · Cited by 423 · see citing works

Expanding functional protein sequence spaces using generative adversarial networks

Repecka, D., Jauniskis, V., Karpus, L., Rembeza, E., Rokaitis, I., Zrimec, J., Poviloniene, S., Laurynenas, A., Viknander, S., Abuajwa, W., et al. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00310-5 · Cited by 388 · see citing works

Plasma Proteomics Identify Biomarkers and Pathogenesis of COVID-19

Shu, T., Ning, W., Wu, D., Xu, J., Han, Q., Huang, M., Zou, X., Yang, Q., Yuan, Y., Bie, Y., et al. (2020) · Immunity · doi:10.1016/j.immuni.2020.10.008 · Cited by 337 · see citing works

An Activity-Guided Map of Electrophile-Cysteine Interactions in Primary Human T Cells

Vinogradova, E. V., Zhang, X., Remillard, D., Lazar, D. C., Suciu, R. M., Wang, Y., Bianco, G., Yamashita, Y., Crowley, V. M., Schafroth, M. A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.07.001 · Cited by 351 · see citing works

GPCRdb in 2021: integrating GPCR sequence, structure and function

Kooistra, A. J., Mordalski, S., Pándy-Szekeres, G., Esguerra, M., Mamyrbekov, A., Munk, C., Keserű, G. M., & Gloriam, D. E. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1080 · Cited by 351 · see citing works

Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders

Yang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290 · see citing works

The PROTACtable genome

Schneider, M., Radoux, C. J., Hercules, A., Ochoa, D., Dunham, I., Zalmas, L.-P., Hessler, G., Ruf, S., Shanmugasundaram, V., Hann, M. M., et al. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00245-x · Cited by 273 · see citing works

AF2Complex predicts direct physical interactions in multimeric proteins with deep learning

Gao, M., Nakajima An, D., Parks, J. M., & Skolnick, J. (2022) · Nature Communications · doi:10.1038/s41467-022-29394-2 · Cited by 252 · see citing works

Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank

Steinegger, M., & Salzberg, S. L. (2020) · Genome Biology · doi:10.1186/s13059-020-02023-1 · Cited by 246 · see citing works

Toward better drug discovery with knowledge graph

Zeng, X., Tu, X., Liu, Y., Fu, X., & Su, Y. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2021.09.003 · Cited by 229 · see citing works

Accelerating antibiotic discovery through artificial intelligence

Melo, M. C. R., Maasch, J. R. M. A., & de la Fuente-Nunez, C. (2021) · Communications Biology · doi:10.1038/s42003-021-02586-0 · Cited by 234 · see citing works

Deep Learning in Protein Structural Modeling and Design

Gao, W., Mahajan, S. P., Sulam, J., & Gray, J. J. (2020) · Patterns · doi:10.1016/j.patter.2020.100142 · Cited by 227 · see citing works

MetaNetX/MNXref: unified namespace for metabolites and biochemical reactions in the context of metabolic models

Moretti, S., Tran, V. D. T., Mehl, F., Ibberson, M., & Pagni, M. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa992 · Cited by 177 · see citing works

Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning

Kroll, A., Rousset, Y., Hu, X.-P., Liebrand, N. A., & Lercher, M. J. (2023) · Nature Communications · doi:10.1038/s41467-023-39840-4 · Cited by 186 · see citing works

DrugCentral 2021 supports drug discovery and repositioning

Avram, S., Bologa, C. G., Holmes, J., Bocci, G., Wilson, T. B., Nguyen, D.-T., Curpan, R., Halip, L., Bora, A., Yang, J. J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa997 · Cited by 189 · see citing works

SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning

Hanson, J., Paliwal, K. K., Litfin, T., & Zhou, Y. (2019) · Genomics, Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.01.004 · Cited by 165 · see citing works

Machine learning: a powerful tool for gene function prediction in plants

Mahood, E. H., Kruse, L. H., & Moghe, G. D. (2020) · Applications in Plant Sciences · doi:10.1002/aps3.11376 · Cited by 153 · see citing works

Systematic review and analysis of human proteomics aging studies unveils a novel proteomic aging clock and identifies key processes that change with age

Johnson, A. A., Shokhirev, M. N., Wyss-Coray, T., & Lehallier, B. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101070 · Cited by 166 · see citing works

TCRD and pharos 2021: mining the human proteome for disease biology

Sheils, T. K., Mathias, S. L., Kelleher, K. J., Siramshetty, V. B., Nguyen, D.-T., Bologa, C. G., Jensen, L. J., Vidović, D., Koleti, A., Schürer, S. C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa993 · Cited by 160 · see citing works

Leveraging Uncertainty in Machine Learning Accelerates Biological Discovery and Design

Hie, B., Bryson, B. D., & Berger, B. (2020) · Cell Systems · doi:10.1016/j.cels.2020.09.007 · Cited by 154 · see citing works

The IUPHAR/BPS guide to PHARMACOLOGY in 2022: curating pharmacology for COVID-19, malaria and antibacterials

Harding, S. D., Armstrong, J. F., Faccenda, E., Southan, C., Alexander, S. P. H., Davenport, A. P., Pawson, A. J., Spedding, M., Davies, J. A., & NC-IUPHAR (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1010 · Cited by 149 · see citing works

GeneCaRNA: A Comprehensive Gene-centric Database of Human Non-coding RNAs in the GeneCards Suite.

Barshir, R., Fishilevich, S., Iny-Stein, T., Zelig, O., Mazor, Y., Guan-Golan, Y., Safran, M., & Lancet, D. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.166913 · Cited by 134 · see citing works

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins

Lazar, T., Martínez-Pérez, E., Quaglia, F., Hatos, A., Chemes, L. B., Iserte, J. A., Méndez, N. A., Garrone, N. A., Saldaño, T. E., Marchetti, J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1021 · Cited by 142 · see citing works

Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery

Chiou, S.-H., Tseng, D., Reuben, A., Mallajosyula, V., Molina, I. S., Conley, S., Wilhelmy, J., McSween, A. M., Yang, X., Nishimiya, D., et al. (2021) · Immunity · doi:10.1016/j.immuni.2021.02.014 · Cited by 133 · see citing works

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis

Kim, H., Park, S., Jeong, I. G., Song, S. H., Jeong, Y., Kim, C.-S., & Lee, K. H. (2021) · ACS Nano · doi:10.1021/acsnano.0c06946 · Cited by 130 · see citing works

Reproducibility in systems biology modelling

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