Guilt-by-association goes global

A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae

Uetz, P., Giot, L., Cagney, G., Mansfield, T. A., Judson, R. S., Knight, J. R., Lockshon, D., Narayan, V., Srinivasan, M., Pochart, P., et al. (2000) · Nature · doi:10.1038/35001009 · Cited by 4,706

Life with 6000 Genes

Goffeau, A., Barrell, B. G., Bussey, H., Davis, R. W., Dujon, B., Feldmann, H., Galibert, F., Hoheisel, J. D., Jacq, C., Johnston, M., et al. (1996) · Science · doi:10.1126/science.274.5287.546 · Cited by 4,423

Direct analysis of protein complexes using mass spectrometry

Link, A. J., Eng, J. K., Schieltz, D. M., Carmack, E., Mize, G. J., Morris, D. R., Garvik, B. M., & Yates, J. R. (1999) · Nature Biotechnology · doi:10.1038/10890 · Cited by 2,218

Linking genome and proteome by mass spectrometry: Large-scale identification of yeast proteins from two dimensional gels

Shevchenko, A., Jensen, O. N., Podtelejnikov, A. V., Sagliocco, F. A., Wilm, M. S., Vorm, O., Mortensen, P. M., Shevchenko, A., Boucherie, H., & Mann, M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.25.14440 · Cited by 1,429

Systematic functional analysis of the yeast genome

Oliver, S. G. (1998) · Trends in biotechnology · doi:10.1016/s0167-7799(98)01214-1 · Cited by 1,374

Characterization of the Yeast Transcriptome

Velculescu, V. E., Zhang, L., Zhou, W., Vogelstein, R. J., Basrai, M. A., Bassett, D. E., Hieter, P., Vogelstein, B., & Kinzler, K. W. (1997) · Cell · doi:10.1016/s0092-8674(00)81845-0 · Cited by 973

Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens

Fromont‐Racine, M., Rain, J., & Legrain, P. (1997) · Nature Genetics · doi:10.1038/ng0797-277 · Cited by 930

Characterization of Sm‐like proteins in yeast and their association with U6 snRNA

Mayes, A. E., Verdone, L., Legrain, P., & Beggs, J. D. (1999) · The EMBO Journal · doi:10.1093/emboj/18.15.4321 · Cited by 239

A protein–protein interaction map of yeast RNA polymerase III

Flores, A., Briand, J.-F., Gadal, O., Andrau, J., Rubbi, L., Mullem, V. V., Boschiero, C., Goussot, M., Marck, C., Carles, C., et al. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.14.7815 · Cited by 142

Oligomer-chip technology

Hoheisel, J. D. (1997) · Trends in biotechnology · doi:10.1016/s0167-7799(97)01123-2 · Cited by 70

Perfil de expressão gênica de célula monocítica humana infectada por Leishmania (Leishmania) infantum

Ozaki, C. Y. (2019) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.99.2019.tde-25032019-151512

On function homophily of microbial Protein-Protein Interaction Networks.Preprint

Apollonio, N., Franciosa, P. G., & Santoni, D. (2021) · arXiv (Cornell University)

Identification of antineoplastic agents for oral squamous cell carcinoma: an integrated bioinformatics approach using differential gene expression and network biologyPreprint

Usman, A., & Khan, F. F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.14.464376

From Petri Plates to Petri Nets, a revolution in yeast biology

Oliver, S. G. (2022) · FEMS Yeast Research · doi:10.1093/femsyr/foac008

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Pan-cancer Analyses reveal functional similarities of three lncRNAs across multiple tumorsPreprint

Khazaal, A., Zandavi, S. M., Smolnikov, A., Fatima, S., & Vafaee, F. (2022) · medRxiv · doi:10.1101/2022.03.14.22272396

Identification of a novel subnetwork involved in eye size variation between Drosophila melanogaster and D. mauritiana

Lu, T.-H. (2022) · doi:10.53846/goediss-9111

A reliability measure of protein–protein interactions and a reliability measure-based search engine

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Conclusion

Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064660

EMBnet.journal 18 Suppl. A

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Mining Protein Interactome Networks to Measure Interaction Reliability and Select Hub Proteins

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The Proteomics Market

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Preface

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Faculty Opinions recommendation of A Pan-plant Protein Complex Map Reveals Deep Conservation and Novel Assemblies.

Leister, D., & Rühle, T. (2021) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.737582077.793586591

RNA degradation heavily impacts mRNA co-expressionPreprint

García‐Blay, Ó., Verhagen, P. G. A., Martin, B., & Hansen, M. M. K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.09.21.508820

Multi-layer guilt-by-association-based drug repurposing by integrating clinical knowledge on biological heterogeneous networksPreprint

Bang, D., Lim, S., Lee, S., & Kim, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.22.517225

Genome-wide association reveals novel insights into the molecular mechanisms regulating stem volume in Pinus taedaPreprint

Aono, A. H., Bajay, S. K., Francisco, F. R., & de Souza, A. P. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.06.519371

Clustering Analysis Indicates Genes Involved in Progesterone-Induced Oxidative Stress in Pancreatic Beta Cells: Insights to Understanding Gestational Diabetes

dos Santos, L. M. D., Oliveira, P. R., & Azevedo‐Martins, A. K. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-21175-1_8

Análise de agrupamento de dados de expressão gênica e sua aplicação para o entendimento da relação entre progesterona e diabetes gestacional

dos Santos, L. M. D. (2022) · doi:10.11606/d.100.2022.tde-20122022-113123

The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticusPreprint

Carter, E. W., Guerra‐Peraza, O., & Wang, N. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.10.548374

Identificação de contaminantes e análises multiômicas aplicadas no melhoramento molecular de forrageiras tropicais poliploides

Martins, F. B. (2022) · doi:10.47749/t/unicamp.2022.1265990

Additional file 2 of Inferring SARS-CoV-2 functional genomics from viral transcriptome with identification of potential antiviral drugs and therapeutic targets

Pan, X., Li, X., Ning, S., & Zhi, H. (2021) · Figshare · doi:10.6084/m9.figshare.16590741

Discovery of Novel Plant Lignocellulose Conversion Associated Fungal Transcription Factors Using a Network-Based ApproachPreprint

Peng, M., Müller, A., Kowalczyk, J. E., Kun, R. S., & de Vries, R. P. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4808935

Bioinformatics-based pan-cancer analysis of UBE2CPreprint

Zhang, Y., Hu, M.-G., Yang, C., Peng, J., Wei, H., Wang, Y.-B., Li-ning, S., & Wu, X. (2024) · Research Square · doi:10.21203/rs.3.rs-4352245/v1

Protein Function Prediction Based on the Pretrained Language Model ESM2 and Graph Convolutional Networks

Hou, L., Qin, H., Zhang, X., & Zhang, Y. (2024) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa63168.2024.00242

Two Decades of Biological Pathway Databases: Results and Challenges

Rahmati, S., Pastrello, C., Rossos, A. E. M., & Jurišica, I. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-95502-7.00367-5

DeepGO-ESM: Improving the Protein Function Prediction of DeepGraphGO via the Evolutionary Scale Modeling Framework

Zhao, J., & Shao, J. (2025) · Lecture notes in computer science · doi:10.1007/978-981-95-0030-7_35

An Adaptive Multi-view Feature Fusion Framework Based on Multiple Graphs for Predicting Drug-Drug Interactions

Wang, F., Cheng, Z., Lei, X., Wu, F., Zheng, C.-H., & Su, Y. (2025) · Lecture notes in computer science · doi:10.1007/978-981-95-0030-7_32

circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data

Ryšavý, P., Anuarbekov, A., Merkerová, M. D., & Kléma, J. (2025) · BioData Mining · doi:10.1186/s13040-025-00468-3

Identification of antimicrobial resistance genes in Escherichia coli through network diffusion

Mansouri, A., Durazzi, F., Ihsan, M. N., Griffin, S., Manfreda, G., Valdramidis, V., Pasquali, F., & Remondini, D. (2025) · Journal of Antimicrobial Chemotherapy · doi:10.1093/jac/dkaf404

VIP-OT: Dissecting Single-Cell Biochemical State Dynamics under Perturbation via Vibrational Painting and Optimal TransportPreprint

Li, X., Stark, S. G., Liu, X., Wei, M., Zhao, Z., Qi, J., Chen, X., Dang, T. N. S., Wu, Y., Zhang, K., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.09.693255

An integrative approach to studying protein-protein interactions within the genome of Mycobacterium tuberculosis

Opap, K. (2011) · Open University of Cape Town (University of Cape Town)

Additional file 1 of Inferring SARS-CoV-2 functional genomics from viral transcriptome with identification of potential antiviral drugs and therapeutic targets

Pan, X., Li, X., Ning, S., & Zhi, H. (2021) · Figshare · doi:10.6084/m9.figshare.16590735

Additional file 3 of Finding functional associations between prokaryotic virus orthologous groups: a proof of concept

Pappas, N., & Dutilh, B. E. (2021) · Figshare · doi:10.6084/m9.figshare.16625594

Additional file 1 of Peripheral whole blood microRNA expression in relation to vascular function: a population-based study

Talevi, V., Melas, K., Pehlivan, G., Imtiaz, M. A., Krueger, D. M., Centeno, T. P., Aziz, N. A., Fischer, A., & Breteler, M. M. B. (2024) · Figshare · doi:10.6084/m9.figshare.26339936

Additional file 1 of Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets

Poudel, S., Cope, A. L., O’Dell, K. B., Guss, A. M., Seo, H., Trinh, C. T., & Hettich, R. L. (2021) · Figshare · doi:10.6084/m9.figshare.14570014

Additional file 3 of Peripheral whole blood microRNA expression in relation to vascular function: a population-based study

Talevi, V., Melas, K., Pehlivan, G., Imtiaz, M. A., Krueger, D. M., Centeno, T. P., Aziz, N. A., Fischer, A., & Breteler, M. M. B. (2024) · Figshare · doi:10.6084/m9.figshare.26751706

Additional file 4 of Finding functional associations between prokaryotic virus orthologous groups: a proof of concept

Pappas, N., & Dutilh, B. E. (2021) · Figshare · doi:10.6084/m9.figshare.16625597

Additional file 1 of GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Yuan, Y., & Bar‐Joseph, Z. (2020) · Figshare · doi:10.6084/m9.figshare.13364592

Additional file 2 of Finding functional associations between prokaryotic virus orthologous groups: a proof of concept

Pappas, N., & Dutilh, B. E. (2021) · Figshare · doi:10.6084/m9.figshare.16625591

Additional file 2 of Peripheral whole blood microRNA expression in relation to vascular function: a population-based study

Talevi, V., Melas, K., Pehlivan, G., Imtiaz, M. A., Krueger, D. M., Centeno, T. P., Aziz, N. A., Fischer, A., & Breteler, M. M. B. (2024) · Figshare · doi:10.6084/m9.figshare.26340148

Additional file 2 of GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data

Yuan, Y., & Bar‐Joseph, Z. (2020) · Figshare · doi:10.6084/m9.figshare.13364595

Additional file 5 of Finding functional associations between prokaryotic virus orthologous groups: a proof of concept

Pappas, N., & Dutilh, B. E. (2021) · Figshare · doi:10.6084/m9.figshare.16625600

Additional file 1 of KinOrtho: a method for mapping human kinase orthologs across the tree of life and illuminating understudied kinases

Huang, L., Taujale, R., Gravel, N., Venkat, A., Yeung, W., Byrne, D. P., Eyers, P. A., & Kannan, N. (2021) · Figshare · doi:10.6084/m9.figshare.16640874

Additional file 9 of Identification and characterization of proteins of unknown function (PUFs) in Clostridium thermocellum DSM 1313 strains as potential genetic engineering targets

Poudel, S., Cope, A. L., O’Dell, K. B., Guss, A. M., Seo, H., Trinh, C. T., & Hettich, R. L. (2021) · Figshare · doi:10.6084/m9.figshare.14570038

UNITe: exploiting conserved links between oncogenesis and homeostasis to identify novel cancer drivers

Agrawal, P., Timon, A., Gopalan, V., Singh, A., & Hannenhalli, S. S. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1711517

Learning block structures in covariance matrices under heteroskedasticity

Wu, J., & Zhang, W. (2026) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2026.108371

Evaluating network-based algorithms for protein function prediction using plant protein-protein interaction networks

Piyatissa, M. A. S. U., Weeraman, J., Sridaran, A., Silva, M. R. P. D., Tirimanne, T. L. S., & Fernando, P. (2026) · BMC Plant Biology · doi:10.1186/s12870-026-08608-5

TCM formula optimization for treating diabetic peripheral neuropathy: Network pharmacology, machine learning, and experimental verification

Du, Y., Peng, J., Zhang, F., Yu, Q., Zho, X., Yang, K., & Ren, J. (2026) · Science of Traditional Chinese Medicine · doi:10.1097/st9.0000000000000108

Méthodes de classification de réseaux d'intéractions protéine-protéine et évaluations pour l'étude de la fonction

Robisson, B. (2013) · theses.fr (ABES) · doi:10.70675/ffe73fb2ze1c4z41a4z8ae7z86cd4efe56ad

Application de la biologie des systèmes pour l'identification de marqueurs moléculaires des maladies rénales dans les fluides biologiques

Boizard, F. (2019) · theses.fr (ABES) · doi:10.70675/adf3a0d1z519cz4083z96e7zfed423c6e572

Melatonin promotes notoginsenosides accumulation via a PnHSP17/PnJAZ5-PnWRKY11–PnSE regulatory module in Panax notoginseng

Li, L., Luo, H., Li, J., Hou, J., Ai, M., Pu, R., Liu, T., Li, R., Zhang, W., Liu, Y., et al. (2026) · Industrial Crops and Products · doi:10.1016/j.indcrop.2026.123697

Network-based machine learning to identify biomarkers for systemic lupus erythematosus

Park, M., Kim, D., Lee, J., Noh, J., Kim, C. J., Oh, Y., Suh, C. S., Kim, J.-W., Im, S., Kim, S., et al. (2026) · BMC Biology · doi:10.1186/s12915-026-02681-w

FaNAC29 : a novel gene positively regulating strawberry powdery mildew resistance

He, R., Chen, L., Wang, D., Xiao, Q., Zhang, G., Liu, J., & Li, H. (2026) · New Phytologist · doi:10.1111/nph.71517

Graph-based representations in modern protein science

Matthews, D. S., Pulsford, S. B., Brancewicz, A., Chen, J. Z., Gall, B., Sandhu, M., Spence, M. A., & Jackson, C. J. (2026) · Biochemical Journal · doi:10.1042/bcj20260179

Metabolism and Metabolomics in Sjӧgren’s Disease

Scofield, R. H., & Ice, J. A. (2026) · Rheumatic Disease Clinics of North America · doi:10.1016/j.rdc.2026.09.001

SubtilNet2, a functional interaction model for the validation of potential therapeutic targets

Hawes, C. (2010) · OpenGrey (Institut de l'Information Scientifique et Technique)

Guilt by Association: A Tutorial on Protein Function Inference

Wong, L. (2007)

A combined algorithm for genome-wide prediction of protein function

Marcotte, E. M., Pellegrini, M. A., Thompson, M. J., Yeates, T. O., & Eisenberg, D. S. (1999) · Nature · doi:10.1038/47048 · Cited by 901

Brewing Up Something Special in Yeast

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A network of protein–protein interactions in yeast

Schwikowski, B., Uetz, P., & Fields, S. (2000) · Nature Biotechnology · doi:10.1038/82360 · Cited by 1,364

Detecting protein function and protein-protein interactions from genome sequences. Science 285:751–753

Marcotte, E. M., Pellegrini, M. A., Ng, H.-L., Rice, D. W., Yeates, T. O., & Eisenberg, D. S. (1999)