Logo image
Back
A Novel Approach Based on Bi-Random Walk to Predict Microbe-Disease Associations
Book chapter   Peer reviewed

A Novel Approach Based on Bi-Random Walk to Predict Microbe-Disease Associations

Xianjun Shen, Huan Zhu, Xingpeng Jiang, Xiaohua Hu and Jincai Yang
Intelligent Computing Methodologies, pp 746-752
06 Jul 2018
DOI: https://doi.org/10.1007/978-3-319-95957-3_78
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Bi-Random Walk Computational prediction model Microbe-disease associations
An increasing number of clinical observations have confirmed that the microbes inhabiting in human body have critical impacts on the progression of human disease, which provides promising insights into understanding the mechanism of diseases. However, the known microbe-disease associations remain limited. So, we proposed Bi-Random Walk based on Multiple Path (BiRWMP) to predict microbe-disease associations. Leave-one-out cross-validation (LOOCV) and 5-fold cross-validation were adopted to demonstrate the capability of proposed method. BiRWMP performed better than other methods. Finally, we listed 2 common disease and potential microbes ranked at top 10, and we demonstrated its reasonableness through looking up literatures.

Metrics

11 Record Views
15 citations in Web of Science
18 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Logo image