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Jan Beránek

dblp:393/6304 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0002-5347-3966ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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
Computational science and engineering · 100%

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

TopicWeightPapersLastEvidence papers
Computational science and engineering › computational chemistry › molecular simulation
molecular dynamics
0.812024
Analysis of metadynamics simulations by metadynminer.py · Bioinform. 2024
Computational science and engineering › computational chemistry › molecular simulation › molecular dynamics
trajectory analysis
0.812024
Analysis of metadynamics simulations by metadynminer.py · Bioinform. 2024
Computational science and engineering › computational chemistry › molecular simulation › molecular dynamics
enhanced sampling
0.212024
Analysis of metadynamics simulations by metadynminer.py · Bioinform. 2024
YearPublicationVenuePosition
2024 Analysis of metadynamics simulations by metadynminer.py
abstract
MOTIVATION: Molecular dynamics simulation is very useful but computationally demanding method of studying dynamics of biomolecular systems. Many enhanced sampling methods were developed in order to obtain the desired results in available computational time. Metadynamics and its variants are common enhanced sampling methods used for this purpose. Metadynamics simulations allow the user to gather large amounts of data, which have to be analyzed to elucidate the properties of the studied system. RESULTS: Here, we present metadynminer.py, a Python package that allows easy and user-friendly analysis and visualization of the results obtained from metadynamics simulations. The built-in functions automate frequent tasks and make the package easy to use for new users, while its many customization options and object-oriented nature allow for integration into specialized data analysis workflows by more advanced users. AVAILABILITY AND IMPLEMENTATION: The "metadynminer.py" Python package is available under the GPL-3.0 license via PyPi and Conda. The development version is available on GitHub along with issue support (https://github.com/Jan8be/metadynminer.py). Documentation, tutorial and Jupyter Notebook (provided through the public mybinder.org service) are available at https://metadynreporter.cz.
Jan Beránek, Ales Krenek, Vojtech Spiwok
Bioinform.1