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Nishita Mandal

dblp:312/8013 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-9114-0281ORCID · 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 · 67% Computational science and engineering · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural bioinformatics
ligand transport analysis
0.612022
TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through them · Bioinform. 2022
Computational science and engineering › computational chemistry › molecular simulation › molecular dynamics
molecular dynamics analysis
0.612022
TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through them · Bioinform. 2022
Bioinformatics and computational biology
structural bioinformatics
0.612022
TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through them · Bioinform. 2022

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

trajectory analysis · 0.6molecular dynamics simulation · 0.6
YearPublicationVenuePosition
2022 TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through them
abstract
SUMMARY: Information regarding pathways through voids in biomolecules and their roles in ligand transport is critical to our understanding of the function of many biomolecules. Recently, the advent of high-throughput molecular dynamics simulations has enabled the study of these pathways, and of rare transport events. However, the scale and intricacy of the data produced requires dedicated tools in order to conduct analyses efficiently and without excessive demand on users. To fill this gap, we developed the TransportTools, which allows the investigation of pathways and their utilization across large, simulated datasets. TransportTools also facilitates the development of custom-made analyses. AVAILABILITY AND IMPLEMENTATION: TransportTools is implemented in Python3 and distributed as pip and conda packages. The source code is available at https://github.com/labbit-eu/transport_tools. Data are available in a repository and can be accessed via a link: https://doi.org/10.5281/zenodo.5642954. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Jan Brezovsky, Aravind Selvaram Thirunavukarasu, Bartlomiej Surpeta, Carlos Eduardo Sequeiros-Borja, Nishita Mandal, Dheeraj Kumar Sarkar, Cedrix Jurgal Dongmo Foumthuim, Nikhil Agrawal
Bioinform.5