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      Is Open Access

      Biopython: freely available Python tools for computational molecular biology and bioinformatics

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Summary: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning.

          Availability: Biopython is freely available, with documentation and source code at www.biopython.org under the Biopython license.

          Contact: All queries should be directed to the Biopython mailing lists, see www.biopython.org/wiki/_Mailing_lists peter.cock@ 123456scri.ac.uk .

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          Most cited references17

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          The Pfam protein families database.

          A. Bateman, Lachlan Coin (2004)
          Pfam is a large collection of protein families and domains. Over the past 2 years the number of families in Pfam has doubled and now stands at 6190 (version 10.0). Methodology improvements for searching the Pfam collection locally as well as via the web are described. Other recent innovations include modelling of discontinuous domains allowing Pfam domain definitions to be closer to those found in structure databases. Pfam is available on the web in the UK (http://www.sanger.ac.uk/Software/Pfam/), the USA (http://pfam.wustl.edu/), France (http://pfam.jouy.inra.fr/) and Sweden (http://Pfam.cgb.ki.se/).
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            Python for Scientific Computing

            Travis E. Oliphant (2007)
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              Improved tools for biological sequence comparison.

              W R Pearson, D J Lipman (1988)
              We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence similarity. The FASTA program is a more sensitive derivative of the FASTP program, which can be used to search protein or DNA sequence data bases and can compare a protein sequence to a DNA sequence data base by translating the DNA data base as it is searched. FASTA includes an additional step in the calculation of the initial pairwise similarity score that allows multiple regions of similarity to be joined to increase the score of related sequences. The RDF2 program can be used to evaluate the significance of similarity scores using a shuffling method that preserves local sequence composition. The LFASTA program can display all the regions of local similarity between two sequences with scores greater than a threshold, using the same scoring parameters and a similar alignment algorithm; these local similarities can be displayed as a "graphic matrix" plot or as individual alignments. In addition, these programs have been generalized to allow comparison of DNA or protein sequences based on a variety of alternative scoring matrices.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Journal ID (hwp): bioinfo
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1460-2059
                Publication date (Print): 1 June 2009
                Publication date (Electronic): 20 March 2009
                Publication date PMC-release: 20 March 2009
                Volume: 25
                Issue: 11
                Pages: 1422-1423
                Affiliations
                1Plant Pathology, SCRI, Invergowrie, Dundee, DD2 5DA, 2Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK, 3Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, NC, 4Department of Molecular Biology, Simches Research Center, Massachusetts General Hospital, Boston, MA 02114, USA, 5Centro de Ciências do Mar, Universidade do Algarve, Faro, Portugal, 6Andrew Dalke Scientific, AB, Gothenburg, Sweden, 7California Institute for Telecommunications and Information Technology, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093-0446, USA, 8Bioinformatics Center, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark, 9Molecular Phylogenetics, Department of Biology, TU Kaiserslautern, 67653 Kaiserslautern, UK, 10EMBL Heidelberg, Meyerhofstraβe 1, 69117 Heidelberg, Germany, 11Institute of Informatics, University of Warsaw, Poland and 12RIKEN Omics Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama-shi, Kanagawa-ken, 230-0045, Japan
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Dmitrij Frishman

                Article
                Publisher ID: btp163
                DOI: 10.1093/bioinformatics/btp163
                PMC ID: 2682512
                PubMed ID: 19304878
                SO-VID: 8662dfe4-3441-469f-9467-547c19ddc51e
                Copyright © © 2009 The Author(s)
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 11 March 2009
                Date accepted : 16 March 2009
                Categories
                Subject: Applications Note
                Subject: Sequence Analysis

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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