Demo Data from EDBT 2026 / reviewers in the wild / expert
Nishita Mandal
dblp:312/8013
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › structural bioinformatics
ligand transport analysis |
0.6 | 1 | 2022 | 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 |
0.6 | 1 | 2022 | 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 |
0.6 | 1 | 2022 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through themabstractSUMMARY: 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 |