Literature DB >> 31719228

Visual exploration of microbiome data.

Bhusan K Kuntal1, Sharmila S Mande.   

Abstract

A dramatic increase in large-scale cross-sectional and temporal-level metagenomic experiments has led to an improved understanding of the microbiome and its role in human well-being. Consequently, a plethora of analytical methods has been developed to decipher microbial biomarkers for various diseases, cluster different ecosystems based on microbial content, and infer functional potential of the microbiome as well as analyze its temporal behavior. Development of user-friendly visualization methods and frameworks is necessary to analyze this data and infer taxonomic and functional patterns corresponding to a phenotype. Thus, new methods as well as application of pre-existing ones has gained importance in recent times pertaining to the huge volume of the generated microbiome data. In this review, we present a brief overview of some useful visualization techniques that have significantly enriched microbiome data analytics.

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Year:  2019        PMID: 31719228

Source DB:  PubMed          Journal:  J Biosci        ISSN: 0250-5991            Impact factor:   1.826


  3 in total

1.  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Authors:  Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  Web-igloo: a web based platform for multivariate data visualization.

Authors:  Bhusan K Kuntal; Sharmila S Mande
Journal:  Bioinformatics       Date:  2017-02-15       Impact factor: 6.937

3.  Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

Authors:  Martha Zakrzewski; Carla Proietti; Jonathan J Ellis; Shihab Hasan; Marie-Jo Brion; Bernard Berger; Lutz Krause
Journal:  Bioinformatics       Date:  2017-03-01       Impact factor: 6.937

  3 in total
  1 in total

1.  MetagenoNets: comprehensive inference and meta-insights for microbial correlation networks.

Authors:  Sunil Nagpal; Rashmi Singh; Deepak Yadav; Sharmila S Mande
Journal:  Nucleic Acids Res       Date:  2020-07-02       Impact factor: 16.971

  1 in total

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