Classification methods for the analysis of LH–PCR data associated with inflammatory bowel disease patients. (1st January 2015)

• Record Type: Journal Article
• Authors: Wisittipanit, Nuttachat; Rangwala, Huzefa; Sikaroodi, Masoumeh; Keshavarzian, Ali; Mutlu, Ece A.; Gillevet, Patrick
• Is Part Of: International journal of bioinformatics research and applications. Volume 11:Number 2(2015)
• Page Start: 111
• Page End: 129
• Publication Date: 2015-01-01
• Subjects: human microbiome -- inflammatory bowel disease -- IBD -- microbial abundance profile -- machine learning -- support vector machine -- SVM -- K–nearest neighbour -- kNN -- classification -- length heterogeneity PCR -- LH–PCR fingerprinting -- polymerase chain reaction -- bioinformatics -- human gut; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1504/IJBRA.2015.068087
• Languages: English
• ISSNs: 1744-5485

Abstract

The human gut is one of the most densely populated microbial communities in the world. The interaction of microbes with human host cells is responsible for several disease conditions and of criticality to human health. It is imperative to understand the relationships between these microbial communities within the human gut and their roles in disease. In this study we analyse the microbial communities within the human gut and their role in Inflammatory Bowel Disease (IBD). The bacterial communities were interrogated using Length Heterogeneity PCR (LH–PCR) fingerprinting of mucosal and luminal associated microbial communities for a class of healthy and diseases patients.