alexa Prediction of lipid-interacting amino acid residues from sequence features.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Glycomics & Lipidomics

Author(s): Wang L, Irausquin SJ, Yang JY

Abstract Share this page

Abstract Proteins and lipids are integral components of cell membranes, and play important roles in cell signalling. Alterations of normal protein-lipid recognition may cause various diseases. However, molecular mechanisms underlying protein-lipid recognition are still poorly understood. In this study, we have developed a support vector machine-based approach for predicting lipid-interacting residues from amino acid sequence features. To the best of our knowledge, this is the first study that applies machine learning to sequence-based prediction of lipid-interacting residues in proteins. Our study provides useful information for understanding protein-lipid interactions, and may lead to advances in drug discovery.
This article was published in Int J Comput Biol Drug Des and referenced in Journal of Glycomics & Lipidomics

Relevant Expert PPTs

Relevant Speaker PPTs

Recommended Conferences

Relevant Topics

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords