SHARMILA S MANDE
Articles written in Journal of Biosciences
Volume 41 Issue 3 September 2016 pp 475-485
VARUN MEHRA TARINI SHANKAR GHOSH SHARMILA S MANDE
Horizontal Gene Transfer (HGT) events, initially thought to be rare in
Volume 44 Issue 5 October 2019 Article ID 0118 Review
MOHAMMED MONZOORUL HAQUE SHARMILA S MANDE MANDE
Recent studies have highlighted the potential of ‘translational’ microbiome research in addressing real-world challengespertaining to human health, nutrition and disease. Additionally, outcomes of microbiome research have also positivelyimpacted various aspects pertaining to agricultural productivity, fuel or energy requirements, and stability/preservation ofvarious ecological habitats. Microbiome data is multi-dimensional with various types of data comprising nucleic andprotein sequences, metabolites as well as various metadata related to host and or environment. This poses a major challengefor computational analysis and interpretation of data to reach meaningful, reproducible (and replicable) biological conclusions.In this review, we first describe various aspects of microbiomes that make them an attractive tool/target fordeveloping various translational applications. The challenge of deciphering signatures from an information-rich resourcelike the microbiome is also discussed. Subsequently, we present three case-studies that exemplify the potential of microbiome-based solutions in solving real-world problems. The final part of the review attempts to familiarize readers with theimportance of a robust study design and the diligence required during every stage of analysis for achieving solutions withpotential translational value.
Volume 44 Issue 5 October 2019 Article ID 0119 Review
Visual exploration of microbiome data
BHUSAN K KUNTAL SHARMILA S MANDE
A dramatic increase in large-scale cross-sectional and temporal-level metagenomic experiments has led to an improvedunderstanding of the microbiome and its role in human well-being. Consequently, a plethora of analytical methods has beendeveloped 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-friendlyvisualization methods and frameworks is necessary to analyze this data and infer taxonomic and functional patternscorresponding to a phenotype. Thus, new methods as well as application of pre-existing ones has gained importance inrecent times pertaining to the huge volume of the generated microbiome data. In this review, we present a brief overview ofsome useful visualization techniques that have significantly enriched microbiome data analytics.
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