Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein-protein Interfaces

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Rethinking bioinformatics expertise in the era of artificial intelligence.

NPJ digital medicine·2026

Same author

Large Language Models and Their Applications in Mental Health: Scoping Review.

JMIR mental health·2026

Same author

Blood plasma proteomic biomarkers for forecasting transition to psychosis in an Asian cohort.

Translational psychiatry·2026

Same author

The 2025 Westlake Autumn Symposium for Al Proteomics and Virtual Cell.

Genomics, proteomics & bioinformatics·2026

Same author

Enhancing protein structure prediction: evaluating the role of amino acid physicochemical features in homology search.

Briefings in bioinformatics·2026

Same author

Predicting Ultra-High Risk Outcomes Using Linguistic and Acoustic Measures From High-Risk Social Challenge Recordings: mHealth Longitudinal Cohort Exploratory Study.

JMIR formative research·2025

Search research articles

Related Experiment Video

Updated: Feb 27, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

NetProt: Complex-based Feature Selection.

Wilson Wen Bin Goh^1,2,3, Limsoon Wong^3,4

¹School of Pharmaceutical Science and Technology, Tianjin University , 92 Weijin Road, Tianjin 300072, China.

Journal of Proteome Research

|July 1, 2017

Summary

This summary is machine-generated.

NetProt is a new R package that makes protein complex-based feature selection (PCBFS) methods accessible for proteomics data analysis. It offers implementations of key methods and tools for benchmarking, improving reproducibility and phenotypic relevance.

Keywords:

bioinformatics feature-selection networks proteomics

More Related Videos

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Related Experiment Videos

Last Updated: Feb 27, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Pharmacophore Modeling for Targets with Extensive Ligand Libraries: A Case Study on SARS-CoV-2 Mpro

Published on: September 26, 2025

Area of Science:

Bioinformatics
Computational Biology
Proteomics

Background:

Protein complex-based feature selection (PCBFS) offers high reproducibility and phenotypic relevance in proteomics.
Existing PCBFS methods are not universally implemented or accessible to general users.
There is a need for accessible tools to leverage advanced feature selection techniques in proteomics.

Purpose of the Study:

To develop an R package, NetProt, providing accessible implementations of representative PCBFS methods.
To facilitate the application of PCBFS techniques for proteomics data analysis.
To offer tools for simulating data and benchmarking complex-based methods.

Main Methods:

Development of the NetProt R package.
Implementation of representative protein complex-based feature selection algorithms.
Inclusion of functions for generating simulated differential proteomics data.
Development of methods for creating pseudocomplexes for performance evaluation.

Main Results:

NetProt package provides accessible implementations of key PCBFS methods.
The package includes utilities for data simulation and performance benchmarking.
NetProt enhances the usability of advanced feature selection techniques in proteomics.

Conclusions:

NetProt democratizes the use of advanced PCBFS methods in proteomics research.
The package improves the reproducibility and phenotypic relevance of feature selection.
NetProt serves as a valuable resource for computational biologists and bioinformaticians.