Recent advances in predicting protein–protein interactions with the aid of artificial intelligence algorithms

Highly accurate protein structure prediction with AlphaFold

Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works

The Protein Data Bank

Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196 · see citing works

STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1131 · Cited by 17,749 · 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

Accurate prediction of protein structures and interactions using a 3-track network

Baek, M., DiMaio, F., Anishchenko, I., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., et al. (2021) · doi:10.1101/2021.06.14.448402 · Cited by 5,542 · see citing works

Protein complex prediction with AlphaFold-Multimer

Evans, R., O’Neill, M., Pritzel, A., Antropova, N., Senior, A., Green, T., Žídek, A., Bates, R., Blackwell, S., Yim, J., et al. (2021) · doi:10.1101/2021.10.04.463034 · Cited by 3,808 · see citing works

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Krogan, N. J., Cagney, G., Yu, H., Zhong, G., Guo, X., Ignatchenko, A., Li, J., Pu, S., Datta, N., Tikuisis, A., et al. (2006) · Nature · doi:10.1038/nature04670 · Cited by 2,915 · see citing works

Towards a proteome-scale map of the human protein–protein interaction network

Rual, J.-F. M., Venkatesan, K., Hao, T., Hirozane-Kishikawa, T., Dricot, A., Li, N., Berriz, G. F., Gibbons, F. D., Dreze, M., Ayivi-Guedehoussou, N., et al. (2005) · Nature · doi:10.1038/nature04209 · Cited by 2,904 · see citing works

STRING 8--a global view on proteins and their functional interactions in 630 organisms

Jensen, L. J., Kuhn, M., Stark, M., Chaffron, S., Creevey, C. J., Muller, J., Doerks, T., Julien, P., Roth, A. C., Simonovic, M., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn760 · Cited by 2,475 · see citing works

The reactome pathway knowledgebase 2022

Gillespie, M. E., Jassal, B., Stephan, R., Orlic-Milacic, M., Rothfels, K., Senff‐Ribeiro, A., Griss, J., Sevilla, C., Matthews, L. R., Gong, C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab1028 · Cited by 2,355 · see citing works

The Database of Interacting Proteins: 2004 update

Salwinski, L. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh086 · Cited by 2,271 · see citing works

The <scp>BioGRID</scp> database: A comprehensive biomedical resource of curated protein, genetic, and chemical interactions

Oughtred, R., Rust, J., Chang, C., Breitkreutz, B., Stark, C., Willems, A., Boucher, L., Leung, G., Kolas, N., Zhang, F., et al. (2021) · Protein Science · doi:10.1002/pro.3978 · Cited by 1,858 · see citing works

The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases

Orchard, S. E., Ammari, M. G., Aranda, B., Breuza, L., Briganti, L., Broackes-Carter, F. C., Campbell, N. H., Chavali, G. B., Chen, C. C. L., del‐Toro, N., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1115 · Cited by 1,835 · see citing works

ZDOCK server: interactive docking prediction of protein–protein complexes and symmetric multimers

Pierce, B. G., Wiehe, K. J., Hwang, H., Kim, B., Vreven, T., & Weng, Z. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu097 · Cited by 1,767 · see citing works

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

(2016) · doi:10.1109/cvpr33180.2016 · Cited by 1,569 · see citing works

PATRIC, the bacterial bioinformatics database and analysis resource

Wattam, A. R., Abraham, D., Dalay, O., Disz, T. L., Driscoll, T., Gabbard, J. L., Gillespie, J. J., Gough, R., Hix, D., Kenyon, R. W., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1099 · Cited by 1,245 · see citing works

InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curation

Breuer, K., Foroushani, A. B. K., Laird, M. R., Chen, C. C. L., Sribnaia, A., Lo, R., Winsor, G. L., Hancock, R. E. W., Brinkman, F. S. L., & Lynn, D. J. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1147 · Cited by 1,224 · see citing works

Harnessing protein folding neural networks for peptide–protein docking

Tsaban, T., Varga, J. K., Avraham, O., Ben-Aharon, Z., Khramushin, A., & Schueler-Furman, O. (2022) · Nature Communications · doi:10.1038/s41467-021-27838-9 · Cited by 1,205 · see citing works

MINT, the molecular interaction database: 2012 update

Licata, L., Briganti, L., Peluso, D., Perfetto, L., Iannuccelli, M., Galeota, E., Sacco, F., Palma, A., Nardozza, A. P., Santonico, E., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr930 · Cited by 1,062 · see citing works

Predicting protein–protein interactions based only on sequences information

Shen, J., Zhang, J., Luo, X., Zhu, W., Yu, K., Chen, K., Li, Y., & Jiang, H. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0607879104 · Cited by 996 · see citing works

The PDBbind database: methodologies and updates

Wang, R., Fang, X., Lu, Y., Yang, C.-Y., & Wang, S. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm048957q · Cited by 933 · see citing works

An empirical framework for binary interactome mapping

Venkatesan, K., Rual, J.-F. M., Vázquez, A., Stelzl, U., Lemmens, I. H., Hirozane-Kishikawa, T., Hao, T., Zenkner, M., Xin, X., Goh, K. I., et al. (2008) · Nature Methods · doi:10.1038/nmeth.1280 · Cited by 907 · see citing works

Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials

Lu, H., Zhou, Q., He, J., Jiang, Z., Peng, C., Tong, R., & Shi, J. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00315-3 · Cited by 891 · see citing works

Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain

Sun, L., Hui, A.-M., Su, Q., Vortmeyer, A. O., Kotliarov, Y., Pastorino, S., Passaniti, A., Menon, J., Walling, J., Bailey, R., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.03.003 · Cited by 878 · see citing works

Estimating the size of the human interactome

Stumpf, M. P. H., Thorne, T., de Silva, E., Stewart, R., An, H. J., Lappé, M., & Wiuf, C. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0708078105 · Cited by 827 · see citing works

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

Gaínza, P., Sverrisson, F., Monti, F., Rodolà, E., Boscaini, D., Bronstein, M. M., & Correia, B. E. (2019) · Nature Methods · doi:10.1038/s41592-019-0666-6 · Cited by 811 · see citing works

Atomic-resolution protein structure determination by cryo-EM

Yip, K. M., Fischer, N., Paknia, E., Chari, A., & Stark, H. (2020) · Nature · doi:10.1038/s41586-020-2833-4 · Cited by 750 · see citing works

Structure-based prediction of protein–protein interactions on a genome-wide scale

Zhang, Q. C., Petrey, D., Deng, L., Qiang, L., Shi, Y., Thu, C. A., Bisikirska, B., Lefebvre, C., Accili, D., Hunter, T., et al. (2012) · Nature · doi:10.1038/nature11503 · Cited by 723 · see citing works

MicroScale Thermophoresis: Interaction analysis and beyond

Jerabek‐Willemsen, M., André, T., Wanner, R., Roth, H. M., Duhr, S., Baaske, P., & Breitsprecher, D. (2014) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2014.03.009 · Cited by 717 · see citing works

Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences

Guo, Y., Yu, L., Wen, Z., & Li, M. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn159 · Cited by 690 · see citing works

Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks

Rivas, J. D. L., & Fontanillo, C. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000807 · Cited by 650 · see citing works

Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information

Ovchinnikov, S., Kamisetty, H., & Baker, D. (2014) · eLife · doi:10.7554/elife.02030 · Cited by 629 · see citing works

Yeast Two-Hybrid, a Powerful Tool for Systems Biology

Brückner, A., Polge, C., Lentze, N., Auerbach, D., & Schlattner, U. (2009) · International Journal of Molecular Sciences · doi:10.3390/ijms10062763 · Cited by 618 · see citing works

Human protein reference database as a discovery resource for proteomics

Peri, S. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh070 · Cited by 606 · see citing works

Protein structure determination from NMR chemical shifts

Cavalli, A., Salvatella, X., Dobson, C. M., & Vendruscolo, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610313104 · Cited by 557 · see citing works

PQS: a protein quaternary structure file server

Henrick, K. (1998) · Trends in Biochemical Sciences · doi:10.1016/s0968-0004(98)01253-5 · Cited by 540 · see citing works

HIPPIE v2.0: enhancing meaningfulness and reliability of protein–protein interaction networks

Alanis‐Lobato, G., Andrade-Navarro, M. A., & Schaefer, M. H. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw985 · Cited by 520 · see citing works

Sequence co-evolution gives 3D contacts and structures of protein complexes

Hopf, T. A., Schärfe, C. P. I., Rodrigues, J. P. G. L. M., Green, A. G., Kohlbacher, O., Sander, C., Bonvin, A. M. J. J., & Marks, D. S. (2014) · eLife · doi:10.7554/elife.03430 · Cited by 515 · see citing works

Phage display: Concept, innovations, applications and future

Pande, J., Szewczyk, M. M., & Grover, A. K. (2010) · Biotechnology Advances · doi:10.1016/j.biotechadv.2010.07.004 · Cited by 492 · see citing works

Protein–protein docking benchmark version 4.0

Hwang, H., Vreven, T., Janin, J., & Weng, Z. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22830 · Cited by 476 · see citing works

SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations

Hooper, C. M., Castleden, I. R., Tanz, S. K., Aryamanesh, N., & Millar, A. H. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1041 · Cited by 435 · see citing works

Updates to the integrated protein-protein interaction benchmarks: docking benchmark version 5 and affinity benchmark version 2

Vreven, T., Moal, I. H., Vangone, A., Pierce, B. G., Kastritis, P. L., Torchala, M., Chaleil, R., Jiménez-García, B., Bates, P. A., Fernandez-Recio, J., et al. (2015) · Journal of Molecular Biology · doi:10.1016/j.jmb.2015.07.016 · Cited by 424 · see citing works

RADIAL BASIS PROBABILISTIC NEURAL NETWORKS: MODEL AND APPLICATION

Huang, D.-S. (1999) · International Journal of Pattern Recognition and Artificial Intelligence · doi:10.1142/s0218001499000604 · Cited by 424 · see citing works

ASEdb: a database of alanine mutations and their effects on the free energy of binding in protein interactions

Thorn, K. S., & Bogan, A. A. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.3.284 · Cited by 403 · see citing works

Correlated sequence-signatures as markers of protein-protein interaction

Sprinzak, E., & Margalit, H. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.4920 · Cited by 401 · see citing works

Predicting protein–protein interactions using signature products

Martin, S., Roe, D. C., & Faulon, J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth483 · Cited by 391 · see citing works

SKEMPI 2.0: an updated benchmark of changes in protein–protein binding energy, kinetics and thermodynamics upon mutation

Jankauskaitė, J., Jiménez-García, B., Dapkūnas, J., Fernández-Recio, J., & Moal, I. H. (2019) · Bioinformatics · doi:10.1093/bioinformatics/bty635 · Cited by 389 · see citing works

Prediction of protein–protein interactions using random decision forest framework

Chen, X., & Liu, M. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti721 · Cited by 386 · see citing works

Sequence-based prediction of protein protein interaction using a deep-learning algorithm

Sun, T., Zhou, B., Lai, L., & Pei, J. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1700-2 · Cited by 376 · see citing works

Multifaceted protein–protein interaction prediction based on Siamese residual RCNN

Chen, M., Ju, C. J. ‐., Zhou, G., Chen, X., Zhang, T., Chang, K.-W., Zaniolo, C., & Wang, W. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz328 · Cited by 375 · see citing works

Predicting protein–protein interactions through sequence-based deep learning

Hashemifar, S. S., Neyshabur, B., Khan, A. A., & Xu, J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty573 · Cited by 370 · see citing works

Prediction of Protein Subcellular Locations by Incorporating Quasi-Sequence-Order Effect

Chou, K. (2000) · Biochemical and Biophysical Research Communications · doi:10.1006/bbrc.2000.3815 · Cited by 361 · see citing works

mentha: a resource for browsing integrated protein-interaction networks

Calderone, A., Castagnoli, L., & Cesareni, G. (2013) · Nature Methods · doi:10.1038/nmeth.2561 · Cited by 349 · see citing works

Are protein–protein interfaces more conserved in sequence than the rest of the protein surface?

Caffrey, D. R., Somaroo, S. S., Hughes, J. D., Mintseris, J., & Huang, E. S. (2003) · Protein Science · doi:10.1110/ps.03323604 · Cited by 339 · see citing works

3D Complex: A Structural Classification of Protein Complexes

Levy, E. D., Pereira‐Leal, J. B., Chothia, C., & Teichmann, S. A. (2006) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020155 · Cited by 337 · see citing works

2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

(2017) · doi:10.1109/bibm41494.2017 · Cited by 327 · see citing works

ModBase, a database of annotated comparative protein structure models and associated resources

Pieper, U., Webb, B., Dong, G. Q., Schneidman‐Duhovny, D., Fan, H., Kim, S. J., Khuri, N., Spill, Y. G., Weinkam, P., Hammel, M., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1144 · Cited by 323 · see citing works

Functional Proteomics Mapping of a Human Signaling PathwayPreprint

Colland, F., Jacq, X., Trouplin, V., Mougin, C., Groizeleau, C., Hamburger, A., Meil, A., Wojcik, J., Legrain, P., & Gauthier, J. (2004) · Genome Research · doi:10.1101/gr.2334104 · Cited by 316 · see citing works

ESLpred: SVM-based method for subcellular localization of eukaryotic proteins using dipeptide composition and PSI-BLAST

Bhasin, M., & Raghava, G. P. S. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh350 · Cited by 310 · see citing works

3did: a catalog of domain-based interactions of known three-dimensional structure

Mosca, R., Ceol, A. G. M., Stein, A., Olivella, R., & Aloy, P. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt887 · Cited by 307 · see citing works

Applying the Naïve Bayes classifier with kernel density estimation to the prediction of protein–protein interaction sites

Murakami, Y., & Mizuguchi, K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq302 · Cited by 304 · see citing works

2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

(2016) · doi:10.1109/bibm39014.2016 · Cited by 299 · see citing works

Protein–protein interaction site prediction through combining local and global features with deep neural networks

Zeng, M., Zhang, F., Wu, F., Li, Y., Wang, J., & Li, M. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz699 · Cited by 281 · see citing works

HPIDB 2.0: a curated database for host–pathogen interactions

Ammari, M., Gresham, C. R., McCarthy, F., & Nanduri, B. (2016) · Database J. Biol. Databases Curation · doi:10.1093/database/baw103 · Cited by 270 · see citing works

Protein–protein docking benchmark version 3.0

Hwang, H., Pierce, B. G., Mintseris, J., Janin, J., & Weng, Z. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22106 · Cited by 256 · see citing works

VirHostNet 2.0: surfing on the web of virus/host molecular interactions data

Guirimand, T., Delmotte, S., & Navratil, V. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1121 · Cited by 237 · see citing works

Bon-EV: an improved multiple testing procedure for controlling false discovery rates

Li, D., Xie, Z., Zand, M. S., Fogg, T. T., & Dye, T. (2017) · BMC Bioinformatics · doi:10.1186/s12859-016-1414-x · Cited by 231 · see citing works

Large-Scale Prediction of Human Protein−Protein Interactions from Amino Acid Sequence Based on Latent Topic Features

Pan, X., Zhang, Y., & Shen, H. (2010) · Journal of Proteome Research · doi:10.1021/pr100618t · Cited by 216 · see citing works

Flaws in evaluation schemes for pair-input computational predictions

Park, Y., & Marcotte, E. M. (2012) · Nature Methods · doi:10.1038/nmeth.2259 · Cited by 213 · see citing works

PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs

Pitre, S., Dehne, F., Chan, A., Cheetham, J., Duong, A., Emili, A., Gebbia, M., Greenblatt, J. F., Jessulat, M. G., Krogan, N. J., et al. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-365 · Cited by 213 · see citing works

Surface Plasmon Resonance: An Introduction to a Surface Spectroscopy Technique

Tang, Y., Zeng, X., & Liang, J. (2010) · Journal of Chemical Education · doi:10.1021/ed100186y · Cited by 210 · see citing works

D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions

Sledzieski, S., Singh, R., Cowen, L., & Berger, B. (2021) · Cell Systems · doi:10.1016/j.cels.2021.08.010 · Cited by 208 · see citing works

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks

Juan, D., Pazos, F., & Valencia, A. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709671105 · Cited by 193 · see citing works

IID 2018 update: context-specific physical protein–protein interactions in human, model organisms and domesticated species

Kotlyar, M., Pastrello, C., Malik, Z., & Jurišica, I. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1037 · Cited by 193 · see citing works

Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein structure analysis

Blohm, P., Frishman, G., Smialowski, P., Goebels, F., Wachinger, B., Ruepp, A., & Frishman, D. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1079 · Cited by 192 · see citing works

ProtorP: a protein–protein interaction analysis server

Reynolds, C. R., Damerell, D., & Jones, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn584 · Cited by 185 · see citing works

Chapter 26 Affinity Chromatography

Urh, M., Simpson, D., & Zhao, K. Q. (2009) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(09)63026-3 · Cited by 177 · see citing works

PHISTO: pathogen-host interaction search tool

Tekir, S. D., Çakır, T., Ardiç, E., Sayilirbas, A. S., Konuk, G., Konuk, M., Sariyer, H., Ugurlu, A., Karadeniz, I., Özgür, A., et al. (2013) · Bioinform. · doi:10.1093/bioinformatics/btt137 · Cited by 175 · see citing works

Protein-Protein Complex Structure Predictions by Multimeric Threading and Template Recombination

Mukherjee, S., & Zhang, Y. (2011) · Structure · doi:10.1016/j.str.2011.04.006 · Cited by 174 · see citing works

The binding interface database (BID): a compilation of amino acid hot spots in protein interfaces

Fischer, T. B., Arunachalam, K. V., Bailey, D., Mangual, V., Bakhru, S., Russo, R., Huang, D. S., Paczkowski, M., Lalchandani, V., Ramachandra, C., et al. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg163 · Cited by 164 · see citing works

DELPHI: accurate deep ensemble model for protein interaction sites prediction

Li, Y., Golding, G. B., & Ilie, L. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa750 · Cited by 164 · see citing works

Prediction of human-virus protein-protein interactions through a sequence embedding-based machine learning method

Yang, X., Yang, S., Li, Q., Wuchty, S., & Zhang, Z. (2019) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2019.12.005 · Cited by 163 · see citing works

VirusMentha: a new resource for virus-host protein interactions

Alberto, C., Licata, L., & Cesareni, G. (2014) · Nucleic Acids Res. · doi:10.1093/nar/gku830 · Cited by 161 · see citing works

SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences

Zhang, J., & Kurgan, L. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz324 · Cited by 156 · see citing works

Current Experimental Methods for Characterizing Protein–Protein Interactions

Zhou, M., Li, Q., & Wang, R. (2016) · ChemMedChem · doi:10.1002/cmdc.201500495 · Cited by 144 · see citing works

Predicting protein-protein interactions via multivariate mutual information of protein sequences

Ding, Y., Tang, J., & Guo, F. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1253-9 · Cited by 143 · see citing works

Whole-proteome interaction mining

Bock, J. R., & Gough, D. A. (2002) · Bioinformatics · doi:10.1093/bioinformatics/19.1.125 · Cited by 138 · see citing works

Automated Yeast Two-hybrid Screening for Nuclear Receptor-interacting Proteins

Albers, M., Kranz, H. D., Kober, I., Kaiser, C., Klink, M., SUCKOW, J. M., Kern, R., & Koegl, M. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400169-mcp200 · Cited by 129 · see citing works

LSTM-PHV: prediction of human-virus protein–protein interactions by LSTM with word2vec

Tsukiyama, S., Hasan, M. M., Fujii, S., et al. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab228 · Cited by 127 · see citing works

DeepRank: a deep learning framework for data mining 3D protein-protein interfaces

Renaud, N., Geng, C., Georgievska, S., Ambrosetti, F., Ridder, L., Marzella, D. F., Réau, M. F., Bonvin, A. M. J. J., & Xue, L. C. (2021) · Nature Communications · doi:10.1038/s41467-021-27396-0 · Cited by 125 · see citing works

Blind prediction of homo- and hetero-protein complexes: the CASP13-CAPRI experiment

Lensink, M. F., Brysbaert, G., Nadzirin, N., Velankar, S., Chaleil, R. A. G., Gerguri, T., Bates, P. A., Laine, E., Carbone, A., Grudinin, S., et al. (2019) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25838 · Cited by 122 · see citing works

The advantages and limitations of protein crystal structures

Acharya, K. R., & Lloyd, M. D. (2004) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2004.10.011 · Cited by 120 · see citing works

Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence

Huang, Y., You, Z., Gao, X., Wong, L., & Wang, L. (2015) · BioMed Research International · doi:10.1155/2015/902198 · Cited by 119 · see citing works

APID interactomes: providing proteome-based interactomes with controlled quality for multiple species and derived networks

Alonso‐López, D., Gutiérrez, M. A., Lopes, K. D. P., Prieto, C. A. V., Santamaría, R., & Rivas, J. D. L. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw363 · Cited by 119 · see citing works

A Human Protein Interaction Network Shows Conservation of Aging Processes between Human and Invertebrate Species

Bell, R. N., Hubbard, A., Chettier, R., Chen, D., Miller, J. P., Kapahi, P., Tarnopolsky, M. A., Sahasrabuhde, S., Melov, S., & Hughes, R. E. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000414 · Cited by 116 · see citing works

Fluorescence Polarization: Past, Present and Future

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