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Biotite: new tools for a versatile Python bioinformatics library
BACKGROUND: Biotite is a program library for sequence and structural bioinformatics written for the Python programming language. It implements widely used computational methods into a consistent and accessible package. This allows for easy combination of various data analysis, modeling and simulatio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243083/ https://www.ncbi.nlm.nih.gov/pubmed/37277726 http://dx.doi.org/10.1186/s12859-023-05345-6 |
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author | Kunzmann, Patrick Müller, Tom David Greil, Maximilian Krumbach, Jan Hendrik Anter, Jacob Marcel Bauer, Daniel Islam, Faisal Hamacher, Kay |
author_facet | Kunzmann, Patrick Müller, Tom David Greil, Maximilian Krumbach, Jan Hendrik Anter, Jacob Marcel Bauer, Daniel Islam, Faisal Hamacher, Kay |
author_sort | Kunzmann, Patrick |
collection | PubMed |
description | BACKGROUND: Biotite is a program library for sequence and structural bioinformatics written for the Python programming language. It implements widely used computational methods into a consistent and accessible package. This allows for easy combination of various data analysis, modeling and simulation methods. RESULTS: This article presents major functionalities introduced into Biotite since its original publication. The fields of application are shown using concrete examples. We show that the computational performance of Biotite for bioinformatics tasks is comparable to individual, special purpose software systems specifically developed for the respective single task. CONCLUSIONS: The results show that Biotite can be used as program library to either answer specific bioinformatics questions and simultaneously allow the user to write entire, self-contained software applications with sufficient performance for general application. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05345-6. |
format | Online Article Text |
id | pubmed-10243083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102430832023-06-07 Biotite: new tools for a versatile Python bioinformatics library Kunzmann, Patrick Müller, Tom David Greil, Maximilian Krumbach, Jan Hendrik Anter, Jacob Marcel Bauer, Daniel Islam, Faisal Hamacher, Kay BMC Bioinformatics Software BACKGROUND: Biotite is a program library for sequence and structural bioinformatics written for the Python programming language. It implements widely used computational methods into a consistent and accessible package. This allows for easy combination of various data analysis, modeling and simulation methods. RESULTS: This article presents major functionalities introduced into Biotite since its original publication. The fields of application are shown using concrete examples. We show that the computational performance of Biotite for bioinformatics tasks is comparable to individual, special purpose software systems specifically developed for the respective single task. CONCLUSIONS: The results show that Biotite can be used as program library to either answer specific bioinformatics questions and simultaneously allow the user to write entire, self-contained software applications with sufficient performance for general application. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05345-6. BioMed Central 2023-06-05 /pmc/articles/PMC10243083/ /pubmed/37277726 http://dx.doi.org/10.1186/s12859-023-05345-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Kunzmann, Patrick Müller, Tom David Greil, Maximilian Krumbach, Jan Hendrik Anter, Jacob Marcel Bauer, Daniel Islam, Faisal Hamacher, Kay Biotite: new tools for a versatile Python bioinformatics library |
title | Biotite: new tools for a versatile Python bioinformatics library |
title_full | Biotite: new tools for a versatile Python bioinformatics library |
title_fullStr | Biotite: new tools for a versatile Python bioinformatics library |
title_full_unstemmed | Biotite: new tools for a versatile Python bioinformatics library |
title_short | Biotite: new tools for a versatile Python bioinformatics library |
title_sort | biotite: new tools for a versatile python bioinformatics library |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243083/ https://www.ncbi.nlm.nih.gov/pubmed/37277726 http://dx.doi.org/10.1186/s12859-023-05345-6 |
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