PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

Author:

Niu Yulong123,Liu Chengcheng4,Moghimyfiroozabad Shayan5,Yang Yi2,Alavian Kambiz N.135

Affiliation:

1. Department of Medicine, Division of Brain Sciences, Imperial College London, London, United Kingdom

2. Key Lab of Bio-resources and Eco-environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China

3. School of Medicine, Department of Internal Medicine, Endocrinology, Yale University, New Haven, CT, United States of America

4. Department of Periodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China

5. Department of Biology, The Bahá’í Institute for Higher Education (BIHE), Tehran, Iran

Abstract

Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/.

Funder

China Scholarship Council

Imperial College London, Department of Medicine, Division of Brain Sciences

Division of Brain Sciences

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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