Biopython

Biopython: freely available Python tools for computational molecular biology and bioinformatics. Biopython is a set of freely available tools for biological computation written in Python by an international team of developers. It is a distributed collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics. The source code is made available under the Biopython License, which is extremely liberal and compatible with almost every license in the world. We work along with the Open Bioinformatics Foundation, who generously host our website, bug tracker, and mailing lists.


References in zbMATH (referenced in 20 articles , 1 standard article )

Showing results 1 to 20 of 20.
Sorted by year (citations)

  1. Berenice Talamantes-Becerra, Jason Carling, Arthur Georges: omicR: A tool to facilitate BLASTn alignments for sequence data (2021) not zbMATH
  2. Vincent Mallet, Carlos Oliver, Jonathan Broadbent, William L. Hamilton, Jérôme Waldispühl: RNAglib: A Python Package for RNA 2.5D Graphs (2021) arXiv
  3. Nicolas Renaud; Cunliang Geng: The pdb2sql Python Package: Parsing, Manipulation and Analysis of PDB Files Using SQL Queries (2020) not zbMATH
  4. N. Moshiri: TreeSwift: A massively scalable Python tree package (2020) not zbMATH
  5. Yuan, Ye; Bar-Joseph, Ziv: Deep learning for inferring gene relationships from single-cell expression data (2019)
  6. Zamudio, Gabriel S.; Prosdocimi, Francisco; Torres de Farias, Sávio; José, Marco V.: A neutral evolution test derived from a theoretical amino acid substitution model (2019)
  7. Benjamin D. Lee: Python Implementation of Codon Adaptation Index (2018) not zbMATH
  8. Russell Y. Neches; Camille Scott: SuchTree: Fast, thread-safe computations with phylogenetic trees (2018) not zbMATH
  9. Keith, Jonathan M. (ed.): Bioinformatics. Volume I. Data, sequence analysis, and evolution (2017)
  10. Berk Ekmekci, Charles E. McAnany, Cameron Mura: An Introduction to Programming for Bioscientists: A Python-based Primer (2016) arXiv
  11. Carugo, Oliviero (ed.); Eisenhaber, Frank (ed.): Data mining techniques for the life sciences (2016)
  12. Kasabov, Nikola (ed.): Springer handbook of bio-/neuro-informatics (2014)
  13. List, Johann-Mattis: SCA: phonetic alignment based on sound classes (2012) ioport
  14. Elloumi, Mourad (ed.); Zomaya, Albert Y. (ed.): Algorithms in computational molecular biology. Techniques approaches and applications. (2011)
  15. Giraud, Mathieu; Varré, Jean-Stéphane: Parallel position weight matrices algorithms (2011) ioport
  16. Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni: ETE: a python environment for tree exploration (2010) ioport
  17. Burkowski, Forbes J.: Structural bioinformatics. An algorithmic approach (2009)
  18. Cock, Peter J. A.; Antao, Tiago; Chang, Jeffrey T.; Chapman, Brad A.; Cox, Cymon J.; Dalke, Andrew; Friedberg, Iddo; Hamelryck, Thomas; Kauff, Frank; Wilczynski, Bartek; De Hoon, Michiel J. L.: Biopython: freely available python tools for computational molecular biology and bioinformatics (2009) ioport
  19. Han, Mira V.; Zmasek, Christian M.: Phyloxml: XML for evolutionary biology and comparative genomics (2009) ioport
  20. Jankun-Kelly, T. J.; Lindeman, Andrew D.; Bridges, Susan M.: Exploratory visual analysis of conserved domains on multiple sequence alignments (2009) ioport