分类方法分析与炎症性肠病患者相关的LH-PCR数据。

Q4 Health Professions International Journal of Bioinformatics Research and Applications Pub Date : 2015-01-01 DOI:10.1504/IJBRA.2015.068087

Nuttachat Wisittipanit, Huzefa Rangwala, Masoumeh Sikaroodi, Ali Keshavarzian, Ece A Mutlu, Patrick Gillevet

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引用次数: 8

摘要

人类肠道是世界上最密集的微生物群落之一。微生物与人类宿主细胞的相互作用是几种疾病的原因，对人类健康至关重要。必须了解人类肠道内这些微生物群落之间的关系及其在疾病中的作用。在这项研究中，我们分析了人类肠道内的微生物群落及其在炎症性肠病(IBD)中的作用。利用长度异质性PCR (LH-PCR)指纹图谱对一类健康和疾病患者的粘膜和肠道相关微生物群落进行了研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Classification methods for the analysis of LH-PCR data associated with inflammatory bowel disease patients.

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.

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来源期刊

International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management

CiteScore

0.60

自引率

0.00%

发文量

期刊介绍： Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.