Philip M. Kim

According to our database, Philip M. Kim authored at least 20 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion.

Osama Abdin, Philip M. Kim

Nat. Mac. Intell., 2024

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

2023

HelixGAN a deep-learning methodology for conditional <i>de novo</i> design of α-helix structures.

Xuezhi Xie, Pedro A. Valiente, Philip M. Kim

Bioinform., January, 2023

Gate-based quantum computing for protein design.

Mohammad Hassan Khatami, Udson C. Mendes, Nathan Wiebe, Philip M. Kim

PLoS Comput. Biol., 2023

Score-based generative modeling for de novo protein design.

Jin Sub Lee, Jisun Kim, Philip M. Kim

Nat. Comput. Sci., 2023

2022

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

2021

Rapid protein model refinement by deep learning.

Osama Abdin, Philip M. Kim

Nat. Comput. Sci., 2021

Deep Generative Modeling for Protein Design.

Alexey Strokach, Philip M. Kim

CoRR, 2021

2017

Data driven flexible backbone protein design.

Mark G. F. Sun, Philip M. Kim

PLoS Comput. Biol., 2017

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

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

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

2013

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

2012

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

2011

Measuring the Evolutionary Rewiring of Biological Networks.

Chong Shou, Nitin Bhardwaj, Hugo Y. K. Lam, Koon-Kiu Yan, Philip M. Kim, Michael Snyder, Mark B. Gerstein

PLoS Comput. Biol., 2011

2010

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, Mark B. Gerstein

BMC Bioinform., 2010

2009

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

2008

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

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

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