Philip M. Kim

Orcid: 0000-0003-3683-152X

According to our database1, Philip M. Kim authored at least 18 papers between 2007 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2023
HelixGAN a deep-learning methodology for conditional <i>de novo</i> design of α-helix structures.
Bioinform., January, 2023

Gate-based quantum computing for protein design.
PLoS Comput. Biol., 2023

Score-based generative modeling for de novo protein design.
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.
J. Chem. Inf. Model., 2022

2021
Rapid protein model refinement by deep learning.
Nat. Comput. Sci., 2021

Deep Generative Modeling for Protein Design.
CoRR, 2021

2017
Data driven flexible backbone protein design.
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.
BMC Bioinform., 2016

ELASPIC web-server: proteome-wide structure-based prediction of mutation effects on protein stability and binding affinity.
Bioinform., 2016

JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis.
Bioinform., 2016

2013
Distinct Types of Disorder in the Human Proteome: Functional Implications for Alternative Splicing.
PLoS Comput. Biol., 2013

2012
Network Evolution: Rewiring and Signatures of Conservation in Signaling.
PLoS Comput. Biol., 2012

2011
Measuring the Evolutionary Rewiring of Biological Networks.
PLoS Comput. Biol., 2011

2010
MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains.
BMC Bioinform., 2010

2009
Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels.
BMC Bioinform., 2009

2008
An integrated system for studying residue coevolution in proteins.
Bioinform., 2008

2007
The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics.
PLoS Comput. Biol., 2007

The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks.
Bioinform., 2007


  Loading...