Philip M. Kim

发表

Measuring the Evolutionary Rewiring of Biological Networks

Mark Gerstein, Michael Snyder, Nitin Bhardwaj, 2011, PLoS Comput. Biol..

The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks

Mark Gerstein, Martin H. Schultz, Kevin Y. Yip, 2006, Bioinform..

A multi-reporter bacterial 2-hybrid assay for the fast, simple, and dynamic assay of PDZ domain – peptide interactions

Marcus B. Noyes, Philip M. Kim, David M. Ichikawa, 2019, bioRxiv.

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

Mark Gerstein, Drew McDermott, Kevin Y. Yip, 2009, BMC Bioinformatics.

JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis

TaeHyung Kim, Anna Goldenberg, Adan Valladares-Salgado, 2015, Bioinform..

Data driven flexible backbone protein design

Philip M. Kim, Mark G. F. Sun, Mark G. F. Sun, 2017, PLoS Comput. Biol..

Open Access Methodology Article Motips: Automated Motif Analysis for Predicting Targets of Modular Protein Domains

Mark Gerstein, Michael Snyder, Sachdev S. Sidhu, 2022 .

The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics

Mark Gerstein, Valery Trifonov, Haiyuan Yu, 2007, PLoS Comput. Biol..

An integrated system for studying residue coevolution in proteins

Mark Gerstein, Drew McDermott, Kevin Y. Yip, 2008, Bioinform..

A physics-based energy function allows the computational redesign of a PDZ domain

Philip M. Kim, Nicolas Panel, David M. Ichikawa, 2019, Scientific Reports.

Designing real novel proteins using deep graph neural networks

David Becerra, Albert Perez-Riba, Philip M. Kim, 2019 .

Network Evolution: Rewiring and Signatures of Conservation in Signaling

Michael Costanzo, Martin Sikora, Charles Boone, 2012, PLoS Comput. Biol..

ELASPIC web-server: proteome-wide structure-based prediction of mutation effects on protein stability and binding affinity

Joan Teyra, Philip M. Kim, Recep Colak, 2016, Bioinform..

Distinct Types of Disorder in the Human Proteome: Functional Implications for Alternative Splicing

TaeHyung Kim, Chad L. Myers, Philip M. Kim, 2013, PLoS Comput. Biol..

The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks

Mark Gerstein, Martin H. Schultz, Kevin Y. Yip, 2006, Bioinform..

Fast and flexible design of novel proteins using graph neural networks

Albert Perez-Riba, Philip M. Kim, Carles Corbi-Verge, 2019, bioRxiv.

PAT: predictor for structured units and its application for the optimization of target molecules for the generation of synthetic antibodies

Roland Arnold, Jouhyun Jeon, Joan Teyra, 2016, BMC Bioinformatics.

Deep Generative Modeling for Protein Design

Philip M. Kim, Alexey Strokach, Alexey Strokach, 2021, Current opinion in structural biology.

Rapid protein model refinement by deep learning

Philip M. Kim, Osama Abdin, 2021, Nature Computational Science.

Subsystem identification through dimensionality reduction of large-scale gene expression data.

Philip M. Kim, B. Tidor, 2003, Genome research.

Paired-End Mapping Reveals Extensive Structural Variation in the Human Genome

Philip M. Kim, M. Gerstein, N. Carter, 2007, Science.

Analysis of copy number variants and segmental duplications in the human genome: Evidence for a change in the process of formation in recent evolutionary history.

Hugo Y. K. Lam, Philip M. Kim, M. Gerstein, 2008, Genome research.

Relating Three-Dimensional Structures to Protein Networks Provides Evolutionary Insights

Philip M. Kim, M. Gerstein, Yu Xia, 2006, Science.

The Genetic Landscape of a Cell

Gary D Bader, Philip M. Kim, Eric D. Spear, 2010, Science.

The role of disorder in interaction networks: a structural analysis

Philip M. Kim, M. Gerstein, A. Sboner, 2008, Molecular systems biology.

Nucleotide-resolution analysis of structural variants using BreakSeq and a breakpoint library

Hugo Y. K. Lam, Philip M. Kim, M. Gerstein, 2010, Nature Biotechnology.

Quantitative Genome-Wide Genetic Interaction Screens Reveal Global Epistatic Relationships of Protein Complexes in Escherichia coli

Philip M. Kim, A. Emili, James Vlasblom, 2014, PLoS genetics.

Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

Philip M. Kim, Niklas Berliner, J. Teyra, 2014, PloS one.

Evolution of biological interaction networks: from models to real data

Philip M. Kim, Philip M Kim, Mark G. F. Sun, 2011, Genome Biology.

Motif mediated protein-protein interactions as drug targets

Philip M. Kim, Carles Corbi-Verge, Carles Corbi-Verge, 2016, Cell Communication and Signaling.

The Chemical Fluctuation Theorem governing gene expression

Gil-Suk Yang, Sanggeun Song, Jaeyoung Sung, 2018, Nature Communications.

Computational structural analysis of protein interactions and networks

Philip M. Kim, Philip M Kim, Y. Hooda, 2012, Proteomics.

Deciphering Protein Kinase Specificity through Large-scale Analysis of Materials Supplemental Deciphering Protein Kinase Specificity through Large-scale Analysis of Yeast Phosphorylation Site Motifs

Bruce Stillman, Hugo Y. K. Lam, Philip M. Kim, 2010 .

Tissue-specific alternative splicing remodels protein-protein interaction networks.

Xinchen Wang, Philip M. Kim, Philip M Kim, 2012, Molecular cell.

The geometric influence on the Cys2His2 zinc finger domain and functional plasticity

Philip M. Kim, David M. Ichikawa, M. Noyes, 2020, Nucleic acids research.

The Evolutionary Landscape of Alternative Splicing in Vertebrate Species

Michael D. Wilson, Philip M. Kim, B. Frey, 2012, Science.

A systematic approach to identify novel cancer drug targets using machine learning, inhibitor design and high-throughput screening

Philip M. Kim, J. Moffat, J. Wrana, 2014, Genome Medicine.

Classification of Intrinsically Disordered Regions and Proteins

Christopher J. Oldfield, Philip M. Kim, Robert J. Weatheritt, 2014, Chemical reviews.

The current excitement about copy-number variation: how it relates to gene duplications and protein families.

Philip M. Kim, M. Gerstein, J. Korbel, 2008, Current opinion in structural biology.

MUSI: an integrated system for identifying multiple specificity from very large peptide or nucleic acid data sets

Gary D. Bader, Gary D Bader, TaeHyung Kim, 2011, Nucleic acids research.

Large-scale interaction profiling of PDZ domains through proteomic peptide-phage display using human and viral phage peptidomes

Tony Pawson, Roland Arnold, Rakesh Joshi, 2014, Proceedings of the National Academy of Sciences.

Positive selection at the protein network periphery: Evaluation in terms of structural constraints and cellular context

Jan O. Korbel, Mark B. Gerstein, Philip M. Kim, 2007, Proceedings of the National Academy of Sciences.

Coevolution of PDZ domain-ligand interactions analyzed by high-throughput phage display and deep sequencing.

Gary D. Bader, Gary D Bader, Somasekar Seshagiri, 2010, Molecular bioSystems.

Strategies to Develop Inhibitors of Motif-Mediated Protein-Protein Interactions as Drug Leads.

Philip M. Kim, Michael Garton, Carles Corbi-Verge, 2017, Annual review of pharmacology and toxicology.

High-Resolution Copy-Number Variation Map Reflects Human Olfactory Receptor Diversity and Evolution

Yehudit Hasin, Tsviya Olender, Miriam Khen, 2008, PLoS genetics.

Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins

Gary D. Bader, Gary D Bader, Somasekar Seshagiri, 2009, PLoS biology.

Rewiring of Transcriptional Regulatory Networks: Hierarchy, Rather Than Connectivity, Better Reflects the Importance of Regulators

Nitin Bhardwaj, Philip M. Kim, Philip M Kim, 2010, Science Signaling.

An omics perspective of protein disorder.

Philip M. Kim, C. Myers, J. Bellay, 2012, Molecular bioSystems.

Identification of specificity determining residues in peptide recognition domains using an information theoretic approach applied to large-scale binding maps

Kevin Y. Yip, Philip M. Kim, M. Gerstein, 2011, BMC Biology.

Method to generate highly stable D-amino acid analogs of bioactive helical peptides using a mirror image of the entire PDB

Philip M. Kim, C. Deber, Michael Garton, 2018, Proceedings of the National Academy of Sciences.

Predicting changes in protein stability caused by mutation using sequence‐and structure‐based methods in a CAGI5 blind challenge

Philip M. Kim, Carles Corbi-Verge, Alexey Strokach, 2019, Human mutation.

Predicting the Effect of Mutations on Protein Folding and Protein-Protein Interactions.

Philip M. Kim, J. Teyra, Carles Corbi-Verge, 2018, Methods in molecular biology.

Discovery of short linear motif‐mediated interactions through phage display of intrinsically disordered regions of the human proteome

Norman E. Davey, Philip M. Kim, N. Davey, 2017, The FEBS journal.

Rapid and accurate structure‐based therapeutic peptide design using GPU accelerated thermodynamic integration

Philip M. Kim, Michael Garton, N. Tarasova, 2019, Proteins.

Non-base-contacting residues enable kaleidoscopic evolution of metazoan C2H2 zinc finger DNA binding

Philip M. Kim, H. Najafabadi, T. Hughes, 2017, Genome Biology.

A computational approach for designing D-proteins with non-canonical amino acid optimised binding affinity

Philip M. Kim, Michael Garton, M. Sayadi, 2017, PloS one.

Large‐scale survey and database of high affinity ligands for peptide recognition modules

Gary D Bader, Philip M. Kim, J. Min, 2020, Molecular systems biology.

The present and the future of motif-mediated protein-protein interactions.

Philip M. Kim, M. Seo, 2018, Current opinion in structural biology.

PepNN: a deep attention model for the identification of peptide binding sites

Philip M. Kim, Satra Nim, H. Wen, 2022, Communications biology.

Pooled screening for anti-proliferative inhibitors of protein-protein interactions

Philip M. Kim, J. Moffat, Jouhyun Jeon, 2016, Nature chemical biology.

A PxL motif promotes timely cell cycle substrate dephosphorylation by the Cdc14 phosphatase

Philip M. Kim, Carles Corbi-Verge, F. Uhlmann, 2018, Nature Structural & Molecular Biology.

Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins Graphical

Philip M. Kim, B. Kuster, A. Ignatchenko, 2016 .

Allosteric Modu Specificity by A of Protein Cores

Philip M. Kim, Julia M. Shifman, J. Shifman, 2019 .

Allosteric Modulation of Binding Specificity by Alternative Packing of Protein Cores.

Philip M. Kim, Julia M. Shifman, J. Shifman, 2019, Journal of molecular biology.

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

Philip M. Kim, P. A. Valiente, Satra Nim, 2022, J. Chem. Inf. Model..

A structural approach reveals how neighbouring C2H2 zinc ﬁngers inﬂuence DNA binding speciﬁcity

Philip M. Kim, H. Najafabadi, Michael Garton, 2015 .

Identification of a Major Determinant for Serine-Threonine Kinase Phosphoacceptor Specificity

Kevin Y. Yip, Philip M. Kim, M. Gerstein, 2014, Molecular cell.

Information for : “ C 2 H 2 zinc finger proteins greatly expand the human regulatory lexicon ”

Philip M. Kim, B. Frey, H. Najafabadi, 2014 .

Conjugating Ligands to an Equilibrated Nanoparticle Protein Corona Enables Cell Targeting in Serum

Philip M. Kim, Zahra Sepahi, Yuwei Zhang, 2022, Chemistry of Materials.

Gate-based quantum computing for protein design

Philip M. Kim, N. Wiebe, U. C. Mendes, 2022, PLoS Comput. Biol..

GDockScore: a graph-based protein-protein docking scoring function

Philip M. Kim, Matthew McFee, 2022, bioRxiv.

Antibodies as drugs—a Keystone Symposia report

Philip M. Kim, B. Keyt, A. Hayday, 2022, Annals of the New York Academy of Sciences.

Understanding Modularity in Molecular Networks Requires Dynamics

Thierry Emonet, Philip M. Kim, Philip M Kim, 2009, Science Signaling.

ELASPIC2 (EL2): Combining contextualized language models and graph neural networks to predict effects of mutations.

Philip M. Kim, Alexey Strokach, Tianchi Lu, 2021, Journal of molecular biology.

Protein engineering by highly parallel screening of computationally designed variants

Philip M. Kim, Carles Corbi-Verge, Philip M Kim, 2016, Science Advances.

Non-base-contacting residues enable kaleidoscopic evolution of metazoan C2H2 zinc finger DNA binding

Philip M. Kim, H. Najafabadi, T. Hughes, 2017, Genome Biology.

The Evolutionary Landscape of Alternative Splicing in Vertebrate Species

Michael D. Wilson, Philip M. Kim, B. Frey, 2013 .

C2H2 zinc finger proteins greatly expand the human regulatory lexicon

Mihai Albu, Philip M. Kim, Philip M Kim, 2015, Nature Biotechnology.

formation in recent evolutionary history the human genome : Evidence for a change in the process of Analysis of copy number variants and segmental duplications in

Hugo Y. K. Lam, Philip M. Kim, M. Gerstein, 2008 .

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

Roland Arnold, Laurence Pelletier, Andrew Emili, 2013, Molecular systems biology.

Understanding Subsystems in Biology through Dimensionality Reduction, Graph Partitioning and Analytical Modeling

Philip M. Kim, Philip Mjong-Hyon Shin Kim, 2003 .

Comparing classical pathways and modern networks: towards the development of an edge ontology.

Kevin Y Yip, Yuanpeng J Huang, Gaetano T Montelione, 2007, Trends in biochemical sciences.

A high-throughput pipeline for the production of synthetic antibodies for analysis of ribonucleoprotein complexes

Philip M. Kim, J. Laver, Jouhyun Jeon, 2016, RNA.

Characterizing WW Domain Interactions of Tumor Suppressor WWOX Reveals Its Association with Multiprotein Networks*

Philip M. Kim, R. Aqeilan, M. Sudol, 2014, The Journal of Biological Chemistry.

A structural approach reveals how neighbouring C2H2 zinc fingers influence DNA binding specificity

Philip M. Kim, H. Najafabadi, T. Hughes, 2015, Nucleic acids research.

Diverse protein kinase interactions identified by protein microarrays reveal novel connections between cellular processes.

Mark Gerstein, Haiyuan Yu, Philip M. Kim, 2011, Genes & development.

A method to calculate the relative binding free energy differences of α-helical stapled peptides.

Philip M. Kim, P. A. Valiente, David Becerra, 2020, The Journal of organic chemistry.

A Multireporter Bacterial 2-Hybrid Assay for the High-Throughput and Dynamic Assay of PDZ Domain-Peptide Interactions.

Philip M. Kim, David M. Ichikawa, Michael J. Shen, 2019, ACS synthetic biology.

The multiple-specificity landscape of modular peptide recognition domains.

Gary D Bader, Sachdev S Sidhu, Erik Verschueren, 2011 .

Comprehensive Analysis of the Human SH3 Domain Family Reveals a Wide Variety of Non-canonical Specificities.

Gary D Bader, Philip M. Kim, J. Min, 2017, Structure.

Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge

Philip M. Kim, S. Brenner, E. Capriotti, 2019, Human mutation.

Fast and Flexible Protein Design Using Deep Graph Neural Networks.

Albert Perez-Riba, Philip M. Kim, Carles Corbi-Verge, 2020, Cell systems.

ProteinSGM: Score-based generative modeling for de novo protein design

Philip M. Kim, Jisun Kim, Jin Sub Lee, 2023, bioRxiv.

Bringing order to protein disorder through comparative genomics and genetic interactions

Gary D Bader, TaeHyung Kim, Sangjo Han, 2011, Genome Biology.

Large-Scale Interaction Profiling of Protein Domains Through Proteomic Peptide-Phage Display Using Custom Peptidomes.

Philip M. Kim, Jouhyun Jeon, Satra Nim, 2017, Methods in molecular biology.

Putting genetic interactions in context through a global modular decomposition.

Gowtham Atluri, Sangjo Han, Gaurav Pandey, 2011, Genome research.

GDockScore: a graph-based protein–protein docking scoring function

Philip M. Kim, Matthew McFee, 2022, bioRxiv.

Computational and artificial intelligence-based methods for antibody development.

Philip M. Kim, Qiao Fang, Jisun Kim, 2023, Trends in pharmacological sciences.

Methods Identifying Protein Domains and Their Boundaries

Philip M. Kim, T. Braun, Jouhyun Jeon, 2022 .

A universal deep-learning model for zinc finger design enables transcription factor reprogramming

Philip M. Kim, David M. Ichikawa, T. Hughes, 2023, Nature Biotechnology.

Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Mathias Wilhelm, Joan Teyra, Bernhard Kuster, 2015, Cell reports.

Computational analysis of interactomes: Current and future perspectives for bioinformatics approaches to model the host–pathogen interaction space

Roland Arnold, Kurt Boonen, Philip M. Kim, 2012, Methods.

PepNN: a deep attention model for the identification of peptide binding sites

Philip M. Kim, Satra Nim, H. Wen, 2021, Communications Biology.

Elucidation of the binding preferences of peptide recognition modules: SH3 and PDZ domains

Joan Teyra, Sachdev S Sidhu, Philip M. Kim, 2012, FEBS letters.

Computational Design of Potent D-Peptide Inhibitors of SARS-CoV-2

Philip M. Kim, Y. P. Paudel, Albert Perez-Riba, 2021, Journal of medicinal chemistry.

Motif mediated protein-protein interactions as drug targets

Philip M. Kim, Carles Corbi-Verge, 2016, Cell Communication and Signaling.

Cell cycle regulation of mitochondrial protein import revealed by genome-scale pooled bimolecular fluorescence complementation screening

Philip M. Kim, C. Misquitta, J. Moffat, 2019, bioRxiv.

Proteomic peptide phage display uncovers novel interactions of the PDZ1‐2 supramodule of syntenin

Philip M. Kim, Roland Arnold, S. Sidhu, 2016, FEBS letters.

Phage display identification of nanomolar ligands for human NEDD4-WW3: Energetic and dynamic implications for the development of broad-spectrum antivirals.

Philip M. Kim, Jose C. Martínez, Ziying Han, 2022, International journal of biological macromolecules.

Computational generation of proteins with predetermined three-dimensional shapes using ProteinSolver

Philip M. Kim, Albert Perez-Riba, Carles Corbi-Verge, 2021, STAR protocols.

Interpreting protein networks with three-dimensional structures

Philip M. Kim, J. Teyra, 2013, Nature Methods.

PAT: predictor for structured units and its application for the optimization of target molecules for the generation of synthetic antibodies

Philip M. Kim, T. Braun, Jouhyun Jeon, 2016, BMC Bioinformatics.

The Chemical Fluctuation Theorem governing gene expression

Philip M. Kim, S. Park, Sanggeun Song, 2018, Nature Communications.

PepFlow: direct conformational sampling from peptide energy landscapes through hypernetwork-conditioned diffusion

Philip M. Kim, Osama Abdin, 2023, bioRxiv.

Disrupting the α-synuclein-ESCRT interaction with a peptide inhibitor mitigates neurodegeneration in preclinical models of Parkinson’s disease

Philip M. Kim, Suneil K. Kalia, L. Kay, 2023, Nature communications.

formation in recent evolutionary history the human genome: Evidence for a change in the process of Analysis of copy number variants and segmental duplications in

Hugo Y. K. Lam, Philip M. Kim, A. Urban, 2008 .

MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains

Hugo Y. K. Lam, Philip M. Kim, M. Gerstein, 2010, BMC Bioinformatics.

The multiple-specificity landscape of modular peptide recognition domains

Gary D Bader, Philip M. Kim, Luis Serrano, 2011, Molecular systems biology.

Limitations of quantitative gene regulation models: a case study.

Bruce Tidor, Philip M. Kim, Philip M Kim, 2003, Genome research.

HelixGAN a deep-learning methodology for conditional de novo design of α-helix structures

Philip M. Kim, P. A. Valiente, Xuezhi Xie, 2023, Bioinform..

Deciphering Protein Kinase Specificity Through Large-Scale Analysis of Yeast Phosphorylation Site Motifs

Hugo Y. K. Lam, Philip M. Kim, M. Gerstein, 2010, Science Signaling.

Computational Design of Potent and Selective d-Peptide Agonists of the Glucagon-like Peptide-2 Receptor.

Philip M. Kim, P. A. Valiente, Satra Nim, 2023, Journal of medicinal chemistry.

The Evolutionary Landscape of Alternative Splicing in Vertebrate Species

Philip M. Kim, B. Frey, Leo J. Lee, 2012, Science.

Semi-supervised Learning Predicts Approximately One Third of the Alternative Splicing Isoforms as Functional Proteins.

Philip M. Kim, B. Kuster, A. Ignatchenko, 2015, Cell reports.

Rewiring of Transcriptional Regulatory Networks: Hierarchy, Rather Than Connectivity, Better Reflects the Importance of Regulators

Philip M. Kim, M. Gerstein, N. Bhardwaj, 2010, Science Signaling.

Score-based generative modeling for de novo protein design

Philip M. Kim, Jisun Kim, Jin Sub Lee, 2023, Nature Computational Science.

The role of disorder in interaction networks: a structural analysis

Philip M. Kim, M. Gerstein, A. Sboner, 2008, Molecular systems biology.

Chaperonin activity modulates codon adaptation

Philip M. Kim, Sangjo Han, 2010, Molecular systems biology.

Molecular Systems Biology Peer Review Process File the Multiple Specificity Landscape of Modular Peptide Recognition Domains Transaction Report

Gary D Bader, Philip M. Kim, Luis Serrano, 2022 .

Designing real novel proteins using deep graph neural networks

Philip M. Kim, David Becerra, Alexey Strokach, 2019 .

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

Philip M. Kim, Frederick S. Vizeacoumar, Glauber C. Brito, 2013, Molecular systems biology.