The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks. - Kevin Y. Yip; Haiyuan Yu; Philip M. Kim; Martin H. Schultz; Mark Gerstein (Bioinform., 2007)

The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics. - Haiyuan Yu; Philip M. Kim; Emmett Sprecher; Valery Trifonov; Mark Gerstein (PLoS Comput. Biol., 2007)

An integrated system for studying residue coevolution in proteins. - Kevin Y. Yip; Prianka Patel; Philip M. Kim; Donald M. Engelman; Drew McDermott; Mark Gerstein (Bioinform., 2008)

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels. - Kevin Y. Yip; Philip M. Kim; Drew McDermott; Mark Gerstein (BMC Bioinform., 2009)

MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains. - Hugo Y. K. Lam; Philip M. Kim; Janine Mok; Raffi Tonikian; Sachdev S. Sidhu; Benjamin E. Turk; Michael Snyder 001; Mark B. Gerstein (BMC Bioinform., 2010)

Measuring the Evolutionary Rewiring of Biological Networks. - Chong Shou; Nitin Bhardwaj; Hugo Y. K. Lam; Koon-Kiu Yan; Philip M. Kim; Michael Snyder 001; Mark B. Gerstein (PLoS Comput. Biol., 2011)

Network Evolution: Rewiring and Signatures of Conservation in Signaling. - Mark G. F. Sun; Martin Sikora; Michael Costanzo; Charles Boone; Philip M. Kim (PLoS Comput. Biol., 2012)

Distinct Types of Disorder in the Human Proteome: Functional Implications for Alternative Splicing. - Recep Colak; TaeHyung Kim; Magali Michaut; Mark G. F. Sun; Manuel Irimia; Jeremy Bellay; Chad L. Myers; Benjamin J. Blencowe; Philip M. Kim (PLoS Comput. Biol., 2013)

JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis. - Recep Colak; TaeHyung Kim; Hilal Kazan; Yoomi Oh; Miguel Cruz; Adan Valladares-Salgado; Jesus Peralta; Jorge Escobedo; Esteban J. Parra; Philip M. Kim; Anna Goldenberg (Bioinform., 2016)

ELASPIC web-server: proteome-wide structure-based prediction of mutation effects on protein stability and binding affinity. - Daniel K. Witvliet; Alexey Strokach; Andrés Felipe Giraldo-Forero; Joan Teyra; Recep Colak; Philip M. Kim (Bioinform., 2016)

PAT: predictor for structured units and its application for the optimization of target molecules for the generation of synthetic antibodies. - Jouhyun Jeon; Roland Arnold; Fateh Singh; Joan Teyra; Tatjana Braun; Philip M. Kim (BMC Bioinform., 2016)

Data driven flexible backbone protein design. - Mark G. F. Sun; Philip M. Kim (PLoS Comput. Biol., 2017)

Deep Generative Modeling for Protein Design. - Alexey Strokach; Philip M. Kim (CoRR, 2021)

Rapid protein model refinement by deep learning. - Osama Abdin; Philip M. Kim (Nat. Comput. Sci., 2021)

Targeting the Receptor-Binding Motif of SARS-CoV-2 with D-Peptides Mimicking the ACE2 Binding Helix: Lessons for Inhibiting Omicron and Future Variants of Concern. - Pedro A. Valiente; Satra Nim; Jinah Lee; Seungtaek Kim; Philip M. Kim (J. Chem. Inf. Model., 2022)

Score-based generative modeling for de novo protein design. - Jin Sub Lee; Jisun Kim; Philip M. Kim (Nat. Comput. Sci., 2023)

Gate-based quantum computing for protein design. - Mohammad Hassan Khatami; Udson C. Mendes; Nathan Wiebe; Philip M. Kim (PLoS Comput. Biol., 2023)

HelixGAN a deep-learning methodology for conditional de novo design of α-helix structures. - Xuezhi Xie; Pedro A. Valiente; Philip M. Kim (Bioinform., 2023)

Antibody-SGM, a Score-Based Generative Model for Antibody Heavy-Chain Design. - Xuezhi Xie; Pedro A. Valiente; Jin Sub Lee; Jisun Kim; Philip M. Kim (J. Chem. Inf. Model., 2024)

Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion. - Osama Abdin; Philip M. Kim (Nat. Mac. Intell., 2024)