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S. Chandrasegaran

dblp:305/6506 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 70% Computational science and engineering · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene regulation
gene regulatory network		 0.512021
TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis · Bioinform. 2021
Bioinformatics and computational biology › gene regulation › microRNA regulation
miRNA-mRNA interaction		 0.512021
TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis · Bioinform. 2021
Computational science and engineering
time series analysis		 0.512021
TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis · Bioinform. 2021
Bioinformatics and computational biology › bioinformatics infrastructure
r/bioconductor package		 0.112021
TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis · Bioinform. 2021
YearPublicationVenuePosition
2021 TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis
abstract
MOTIVATION: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. RESULTS: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction. AVAILABILITY AND IMPLEMENTATION: TimiRGeN is available for download on Bioconductor (https://bioconductor.org/packages/TimiRGeN) and requires R v4.0.2 or newer and BiocManager v3.12 or newer. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Krutik Patel, S. Chandrasegaran, I M. Clark, Carole J. Proctor, D. A. Young, Daryl P. Shanley
 Bioinform.2