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Normalized L3-based link prediction in protein–protein interaction networks

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Improved Protein–Protein Interaction Assay FlimPIA by the Entrapment of Luciferase Conformation

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Homology-Based Prediction of Potential Protein-Protein Interactions between Human Erythrocytes and Plasmodium falciparum

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Review of Recent Protein-Protein Interaction Techniques

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Protein–Protein Interface and Disease: Perspective from Biomolecular Networks

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Leveraging Stacked Denoising Autoencoder in Prediction of Pathogen-Host Protein-Protein Interactions

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NMI Functions as Immuno-regulatory Molecule in Sepsis by Regulating Multiple Signaling Pathways

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Exploring the role of EBV in multiple sclerosis pathogenesis through EBV interactome

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Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl–like molecules binding

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Learning from real imbalanced data of 14-3-3 proteins binding specificity

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A framework towards data analytics on host–pathogen protein–protein interactions

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Predicting Protein–Protein Interactions Using Symmetric Logistic Matrix Factorization

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TTC39B destabilizes retinoblastoma protein promoting hepatic lipogenesis in a sex-specific fashion

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Protein-protein interaction prediction from primary sequences using supervised machine learning algorithm

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Prediction of Biomolecular Complexes

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Proteome-level assessment of origin, prevalence and function of leucine-aspartic acid (LD) motifs

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Target identification for small-molecule discovery in the FOXO3a tumor-suppressor pathway using a biodiverse peptide library

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From local structure to a global framework: recognition of protein folds

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ZEPPI: Proteome-scale sequence-based evaluation of protein–protein interaction models

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In silico prediction method for plant Nucleotide‐binding leucine‐rich repeat‐ and pathogen effector interactions

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Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

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SDADB: a functional annotation database of protein structural domains

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Global Vectors Representation of Protein Sequences and Its Application for Predicting Self-Interacting Proteins with Multi-Grained Cascade Forest Model

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A Conserved Mammalian Protein Interaction Network

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A Protein–Protein Interaction Assay Based on the Functional Complementation of Mutant Firefly Luciferases

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MatrixDB 2024: an increased coverage of extracellular matrix interactions, a new Network Explorer and a new web interface

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Negative sampling strategies impact the prediction of scale-free biomolecular network interactions with machine learning

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Cross-attention PHV: Prediction of human and virus protein-protein interactions using cross-attention–based neural networks

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From workstations to workbenches: Towards predicting physicochemically viable protein–protein interactions across a host and a pathogen

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New Compound Classes: Protein–Protein Interactions

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Towards Data Analytics of Pathogen-Host Protein-Protein Interaction: A Survey

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Molecular comparison of Neanderthal and Modern Human adenylosuccinate lyase

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De Novo and Supervised Endophenotyping Using Network-Guided Ensemble Learning

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Non-photoreceptor Expression of Tulp1 May Contribute to Extensive Retinal Degeneration in Tulp1-/- Mice

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Subtype-selective prenylated isoflavonoids disrupt regulatory drivers of MYCN-amplified cancers

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Growing ecosystem of deep learning methods for modeling protein–protein interactions

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RNA-seq data analysis at the gene and CDS levels provides a comprehensive view of transcriptome responses induced by 4-hydroxynonenal

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INSEL: an in silico method for optimizing and exploring biorecognition assays

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A Systems Approach to Drug Discovery in Alzheimer's Disease

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Protein-Protein Interaction Assays Using Split-NanoLuc

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Dockground Tool for Development and Benchmarking of Protein Docking Procedures

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Protein–Protein Interaction Prediction Based on Spectral Radius and General Regression Neural Network

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Advances in the elucidation of nuclear proteins in the model plant Arabidopsis thaliana: based on protein interactions and bioinformatics analysis

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Characterizing Genes with Distinct Methylation Patterns in the Context of Protein-Protein Interaction Network: Application to Human Brain Tissues

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Comparison of Leptospira interrogans and Leptospira biflexa genomes: analysis of potential leptospiral–host interactions

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A New Family of Similarity Measures for Scoring Confidence of Protein Interactions Using Gene Ontology

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Decomposing the space of protein quaternary structures with the interface fragment pair library

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Complementary omics strategies to dissect p53 signaling networks under nutrient stress

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Deep learning based CETSA feature prediction cross multiple cell lines with latent space representation

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Regulation of Nuclear Receptor Interacting Protein 1 (NRIP1) Gene Expression in Response to Weight Loss and Exercise in Humans

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Molecular dynamics simulation analysis of conessine against multi drug resistant Serratia marcescens

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Analyses of p73 Protein Oligomerization and p73–MDM2 Interaction in Single Living Cells Using In Situ Single Molecule Spectroscopy

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Getting to know each other: PPIMem, a novel approach for predicting transmembrane protein-protein complexes

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Evolutionary Pressure on the Topology of Protein Interface Interaction Networks

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Predicting protein complexes in protein interaction networks using Mapper and graph convolution networks

Daou, L., & Hanna, E. M. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.10.009 · Cited by 8

Accurate Identification of Protein Binding Sites for All Drug Modalities Using ALLSites

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Protein-protein interaction prediction based on multiple kernels and partial network with linear programming

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DCUN1D3 activates SCFSKP2 ubiquitin E3 ligase activity and cell cycle progression under UV damage

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Pathogen and Host-Pathogen Protein Interactions Provide a Key to Identify Novel Drug Targets

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Advances in the Application of Protein Language Modeling for Nucleic Acid Protein Binding Site Prediction

Wang, B., & Li, W. (2024) · Genes · doi:10.3390/genes15081090 · Cited by 7

Self-similarity of human protein interaction networks: a novel strategy of distinguishing proteins

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Perturbation of the Monomer–Monomer Interfaces of the Benzoylformate Decarboxylase Tetramer

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An integrative approach for the large-scale identification of human genome kinases regulating cancer metastasis

Zhang, H., Wu, P.-Y., Ma, M., Ye, Y., Yang, H., Yang, J., Yin, S., Sun, C., Phan, J. H., Wang, M. D., et al. (2013) · Nanomedicine Nanotechnology Biology and Medicine · doi:10.1016/j.nano.2013.05.015 · Cited by 7

In silico analysis and experimental validation of active compounds from fructus Schisandrae chinensis in protection from hepatic injury

Wang, S., Fu, L., Zhang, S. Y., Tian, M., Zhang, L., Zheng, Y., Wang, J., Huang, J. M., & Ouyang, L. (2014) · Cell Proliferation · doi:10.1111/cpr.12157 · Cited by 7

Using the concept of transient complex for affinity predictions in CAPRI rounds 20–27 and beyond

Qin, S., & Zhou, H. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24366 · Cited by 7

Structure‐based protein‐protein interaction networks and drug design

Naveed, H., & Han, J. J. (2013) · Quantitative Biology · doi:10.1007/s40484-013-0018-y · Cited by 8

Systems Pharmacology: An Overview

Birtwistle, M. R., Hansen, J., Gallo, J. M., Muppirisetty, S., Ung, P. M. U., Iyengar, R., & Schlessinger, A. (2016) · AAPS advances in the pharmaceutical sciences series · doi:10.1007/978-3-319-44534-2_4 · Cited by 8

Prediction of Protein-Protein Interaction Based on Deep Learning Feature Representation and Random Forest

Ma, W., Bao, W., Cao, Y., Yang, B., & Chen, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-84532-2_59 · Cited by 7

Assessing Structural Predictions of Protein–Protein Recognition: The CAPRI Experiment

Janin, J., Wodak, S. J., Lensink, M. F., & Velankar, S. S. (2015) · Reviews in computational chemistry · doi:10.1002/9781118889886.ch4 · Cited by 7

Druggability of protein–protein interactions

Hamon, V., & Morelli, X. (2013) · doi:10.4155/ebo.13.193 · Cited by 7

Molecular Glue Degraders: From Serendipity to Hunting and Design

Nieto‐Barrado, L., Domostegui, A., & Mayor‐Ruiz, C. (2022) · Wiley eBooks · doi:10.1002/9783527836208.ch6 · Cited by 7

Computational Analyses of the Interactome between TNF and TNFR Superfamilies

Dhusia, K., Su, Z., & Wu, Y. (2022) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2023.107823 · Cited by 6

A review of carbon recovery in sewage treatment and analysis of product options for a typical water recycling plant

Mohseni, A., Fan, L., Gao, L., Segal, J., & Roddick, F. (2024) · Environmental Science Water Research & Technology · doi:10.1039/d4ew00160e · Cited by 6

Learning protein language contrastive models with multi-knowledge representation

Xu, W., Xia, Y., Sun, B., Zhao, Z., Tang, L., Zhou, X., Wang, Q., & Gu, L. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.107580 · Cited by 6

From Traditional Methods to Deep Learning Approaches: Advances in Protein–Protein Docking

Jiang, L., Zhang, K., Zhu, K., Zhang, H., Shen, C., & Hou, T. (2025) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.70016 · Cited by 6

Predicting protein-protein interaction with interpretable bilinear attention network

Han, Y. K., Zhang, S., Shi, M., Zhang, Q., Li, Y., & Cui, X. (2025) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2025.108756 · Cited by 6

Protein–Protein Interactions Efficiently Modeled by Residue Cluster Classes

Velez, A. H. P., Fontove, F., & del Rio, G. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21134787 · Cited by 6

Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter

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Fluorescence resonance energy transfer in revealing protein-protein interactions in living cells.

Bhaumik, S. R. (2021) · Emerging Topics in Life Sciences · doi:10.1042/etls20200337 · Cited by 4

RF_phage virion: Classification of phage virion proteins with a random forest model

Zhang, Y., & Li, Z. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2022.1103783 · Cited by 6

Sequence-based prediction of protein–protein interaction using auto-feature engineering of RNN-based model

Mewara, B., & Lalwani, S. (2023) · Research on Biomedical Engineering · doi:10.1007/s42600-023-00273-z · Cited by 6

Protein-protein interaction network inference from multiple kernels with optimization based on random walk by linear programming

Huang, L., Liao, L., & Wu, C. H. (2015) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2015.7359681 · Cited by 6

Predicting physiologically relevant SH3 domain mediated protein–protein interactions in yeast

Jain, S., & Bader, G. D. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw045 · Cited by 6

A System-Level Investigation into the Mechanisms of Apigenin Against Inflammation

Xie, Y., Liang, D., Wu, Q., Chen, X., Buabeid, M. A., & Wang, Y. (2019) · Natural Product Communications · doi:10.1177/1934578x19878600 · Cited by 6

Protein structure–based gene expression signatures

Rahman, R., Zatorski, N., Hansen, J., Xiong, Y., van Hasselt, J. G. C., Sobie, E. A., Birtwistle, M. R., Azeloglu, E. U., Iyengar, R., & Schlessinger, A. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2014866118 · Cited by 6

Comprehensive comparison of two protein family of P-ATPases (13A1 and 13A3) in insects

Seddigh, S. (2017) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2017.04.006 · Cited by 6

Molecular Modeling Method Applications: Probing the Mechanism of Endocrine Disruptor Action

Yang, X., Liu, H., & Kusko, R. L. (2019) · Challenges and advances in computational chemistry and physics · doi:10.1007/978-3-030-16443-0_16 · Cited by 6

Protein–Protein Interaction Databases

Kotlyar, M., Pastrello, C., Rossos, A. E. M., & Jurišica, I. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.20495-0 · Cited by 6

MESM: integrating multi-source data for high-accuracy protein-protein interactions prediction through multimodal language models

Wang, F., Chu, J., Shen, L., & Chang, S. (2025) · BMC Biology · doi:10.1186/s12915-025-02356-y · Cited by 5

180 Integrating structural and systems biology: structure-based prediction of protein–protein interactions on a genome-wide scale

Zhang, Q. C., Petrey, D. S., & Honig, B. H. (2013) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2013.786422

A PrePPI way to make predictions

Montoya, M. (2012) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2445 · Cited by 4

Structure-based Prediction of Protein-protein Interaction Networks across Proteomes

Maheshwari, S. (2017) · doi:10.31390/gradschool_dissertations.4361

Predicting PPIs

Doerr, A. J. (2012) · Nature Methods · doi:10.1038/nmeth.2272 · Cited by 2

Computational Methods for the Prediction of Protein-Protein Interactions

Xia, J., Wang, S., & Lei, Y. (2010) · Protein and Peptide Letters · doi:10.2174/092986610791760405 · Cited by 26