Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Sourabh Samaddar

dblp:291/0601 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-0746-3924ORCID · reported

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 · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
microbial genomics
0.512021
Network approach to mutagenesis sheds insight on phage resistance in mycobacteria · Bioinform. 2021
Bioinformatics and computational biology › network bioinformatics › biological network analysis
network comparison
0.512021
Network approach to mutagenesis sheds insight on phage resistance in mycobacteria · Bioinform. 2021
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction network
0.512021
Network approach to mutagenesis sheds insight on phage resistance in mycobacteria · Bioinform. 2021
Bioinformatics and computational biology
systems biology
0.512021
Network approach to mutagenesis sheds insight on phage resistance in mycobacteria · Bioinform. 2021

Methods — techniques the papers use, named apart from their topics

shortest path analysis · 0.5differential network analysis · 0.5
YearPublicationVenuePosition
2021 Network approach to mutagenesis sheds insight on phage resistance in mycobacteria
abstract
MOTIVATION: A rigorous yet general mathematical approach to mutagenesis, especially one capable of delivering systems-level perspectives would be invaluable. Such systems-level understanding of phage resistance is also highly desirable for phage-bacteria interactions and phage therapy research. Independently, the ability to distinguish between two graphs with a set of common or identical nodes and identify the implications thereof, is important in network science. RESULTS: Herein, we propose a measure called shortest path alteration fraction (SPAF) to compare any two networks by shortest paths, using sets. When SPAF is one, it can identify node pairs connected by at least one shortest path, which are present in either network but not both. Similarly, SPAF equalling zero identifies identical shortest paths, which are simultaneously present between a node pair in both networks. We study the utility of our measure theoretically in five diverse microbial species, to capture reported effects of well-studied mutations and predict new ones. We also scrutinize the effectiveness of our procedure through theoretical and experimental tests on Mycobacterium smegmatis mc2155 and by generating a mutant of mc2155, which is resistant to mycobacteriophage D29. This mutant of mc2155, which is resistant to D29 exhibits significant phenotypic alterations. Whole-genome sequencing identifies mutations, which cannot readily explain the observed phenotypes. Exhaustive analyses of protein-protein interaction network of the mutant and wild-type, using the machinery of topological metrics and differential networks does not yield a clear picture. However, SPAF coherently identifies pairs of proteins at the end of a subset of shortest paths, from amongst hundreds of thousands of viable shortest paths in the networks. The altered functions associated with the protein pairs are strongly correlated with the observed phenotypes. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Saptarshi Sinha, Sourabh Samaddar, Sujoy K. Das Gupta, Soumen Roy
Bioinform.2