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Vitor Bernardes Pinheiro

dblp:403/6208 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0003-2491-0028ORCID · 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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
protein structure analysis
0.812024
Melodia: a Python library for protein structure analysis · Bioinform. 2024
Bioinformatics and computational biology
shape descriptor
0.812024
Melodia: a Python library for protein structure analysis · Bioinform. 2024
Bioinformatics and computational biology
structural bioinformatics
0.812024
Melodia: a Python library for protein structure analysis · Bioinform. 2024

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

knot theory · 0.8differential geometry of 3d curves · 0.8RMSD · 0.8
YearPublicationVenuePosition
2024 Melodia: a Python library for protein structure analysis
abstract
SUMMARY: Analysing protein structure similarities is an important step in protein engineering and drug discovery. Methodologies that are more advanced than simple RMSD are available but often require extensive mathematical or computational knowledge for implementation. Grouping and optimizing such tools in an efficient open-source library increases accessibility and encourages the adoption of more advanced metrics. Melodia is a Python library with a complete set of components devised for describing, comparing and analysing the shape of protein structures using differential geometry of 3D curves and knot theory. It can generate robust geometric descriptors for thousands of shapes in just a few minutes. Those descriptors are more sensitive to structural feature variation than RMSD deviation. Melodia also incorporates sequence structural annotation and 3D visualizations. AVAILABILITY AND IMPLEMENTATION: Melodia is an open-source Python library freely available on https://github.com/rwmontalvao/Melodia_py, along with interactive Jupyter Notebook tutorials.
Rinaldo W. Montalvão, William R. Pitt, Vitor Bernardes Pinheiro, Tom L. Blundell
Bioinform.3