Article

Time Evolving Undirected Graphical Model for Protein-Protein Interaction Networks

2017-06-26

Abstract excerpt

Proteins are the workhorses of the cell that perform biological functions by interacting with other proteins. Many statistical methods for protein-protein interaction (PPI) have been studied without considering time-dependent changes in networks and the functionalities. I introduced a novel method that models PPI networks as being dynamic in nature and evolving time-varying multivariate distribution with Condition...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c694486c-9e18-5c38-9d7b-1073276247c6
DOI: 10.20944/preprints201706.0114.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 8 closest

Time Evolving Undirected Graphical Model for Protein-Protein Interaction NetworksDOI 10.20944/preprints201706.0114.v1Read

LRTM: Left-Right Transition Matrices for Molecular Interaction PredictionSemantic proximity Read

Unsupervised Inductive node representation learning for dynamic graphsSemantic proximity Read

Directed Shortest Walk on Temporal GraphsSemantic proximity Read

A novel approach of dynamic cross correlation analysis on molecular dynamics simulations and its application to Ets1 dimer-DNA complex.Semantic proximity Read

A sparse Ising model with covariates.Semantic proximity Read

Detecting protein atom correlations using correlation of probability of recurrence.Semantic proximity Read

Multiple Gaussian network modes alignment reveals dynamically variable regions: the hemoglobin case.Semantic proximity Read

Hom-Complex-Based Machine Learning (HCML) for the Prediction of Protein-Protein Binding Affinity Changes upon Mutation.Semantic proximity Read