Bioinformatics Methods and Biological Interpretation for Next-Generation Sequencing Data.

Guohua Wang,Dongxiao Zhu,Weixing Feng,Yunlong Liu,Gunnar W Klau

doi:10.1155/2015/690873

Abstract

Bioinformatics Methods and Biological Interpretation for Next-Generation Sequencing Data.

Highlights

In “mmnet: An R Package for Metagenomics Systems Biology Analysis,” the authors developed R package, mmnet, to implement community-level metabolic network reconstruction and implement a set of functions for automatic analysis pipeline construction
The plethora of information that emerges from large-scale next-generation sequencing experiments has triggered the development of bioinformatics tools and method for efficient analysis, interpretation, and visualization of Next-generation sequencing (NGS) data
Such methods and tools will substantially promote the life-science community to better and efficiently help understand the underlying biological principles and mechanisms. This special issue mainly focuses on the original research articles as well as review articles that develop new bioinformatics approaches, present novel platforms and systems, and describe concise models well explaining the biological context and application in relation to genetics, metagenomics, and clinical study from NGS data

Summary

Introduction

In “mmnet: An R Package for Metagenomics Systems Biology Analysis,” the authors developed R package, mmnet, to implement community-level metabolic network reconstruction and implement a set of functions for automatic analysis pipeline construction. Editorial Bioinformatics Methods and Biological Interpretation for Next-Generation Sequencing Data Guohua Wang,1 Yunlong Liu,2 Dongxiao Zhu,3 Gunnar W.

Results

Conclusion