Literature DB >> 23978768

Community-analyzer: a platform for visualizing and comparing microbial community structure across microbiomes.

Bhusan K Kuntal1, Tarini Shankar Ghosh, Sharmila S Mande.   

Abstract

A key goal in comparative metagenomics is to identify microbial group(s) which are responsible for conferring specific characteristics to a given environment. These characteristics are the result of the inter-microbial interactions between the resident microbial groups. We present a new GUI-based comparative metagenomic analysis application called Community-Analyzer which implements a correlation-based graph layout algorithm that not only facilitates a quick visualization of the differences in the analyzed microbial communities (in terms of their taxonomic composition), but also provides insights into the inherent inter-microbial interactions occurring therein. Notably, this layout algorithm also enables grouping of the metagenomes based on the probable inter-microbial interaction patterns rather than simply comparing abundance values of various taxonomic groups. In addition, the tool implements several interactive GUI-based functionalities that enable users to perform standard comparative analyses across microbiomes. For academic and non-profit users, the Community-Analyzer is currently available for download from: http://metagenomics.atc.tcs.com/Community_Analyzer/.
© 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Algorithms; Metagenomics; Microbial interactions; Software

Mesh:

Year:  2013        PMID: 23978768     DOI: 10.1016/j.ygeno.2013.08.004

Source DB:  PubMed          Journal:  Genomics        ISSN: 0888-7543            Impact factor:   5.736


  7 in total

1.  'NetShift': a methodology for understanding 'driver microbes' from healthy and disease microbiome datasets.

Authors:  Bhusan K Kuntal; Pranjal Chandrakar; Sudipta Sadhu; Sharmila S Mande
Journal:  ISME J       Date:  2018-10-04       Impact factor: 10.302

2.  Global investigation of composition and interaction networks in gut microbiomes of individuals belonging to diverse geographies and age-groups.

Authors:  Deepak Yadav; Tarini Shankar Ghosh; Sharmila S Mande
Journal:  Gut Pathog       Date:  2016-05-06       Impact factor: 4.181

3.  "EviMass": A Literature Evidence-Based Miner for Human Microbial Associations.

Authors:  Divyanshu Srivastava; Krishanu D Baksi; Bhusan K Kuntal; Sharmila S Mande
Journal:  Front Genet       Date:  2019-09-13       Impact factor: 4.599

4.  Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

Authors:  Disha Tandon; Mohammed Monzoorul Haque; Sharmila S Mande
Journal:  PLoS One       Date:  2016-04-28       Impact factor: 3.240

5.  CompNet: a GUI based tool for comparison of multiple biological interaction networks.

Authors:  Bhusan K Kuntal; Anirban Dutta; Sharmila S Mande
Journal:  BMC Bioinformatics       Date:  2016-04-26       Impact factor: 3.169

6.  'TIME': A Web Application for Obtaining Insights into Microbial Ecology Using Longitudinal Microbiome Data.

Authors:  Krishanu D Baksi; Bhusan K Kuntal; Sharmila S Mande
Journal:  Front Microbiol       Date:  2018-01-24       Impact factor: 5.640

7.  BURRITO: An Interactive Multi-Omic Tool for Visualizing Taxa-Function Relationships in Microbiome Data.

Authors:  Colin P McNally; Alexander Eng; Cecilia Noecker; William C Gagne-Maynard; Elhanan Borenstein
Journal:  Front Microbiol       Date:  2018-03-01       Impact factor: 5.640

  7 in total

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