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BIOINFORMATICS APPLICATIONS NOTE Vol. 25 no. 11 2009, pages 1422–1423doi:10.1093/bioinformatics/btp163
Sequence analysis
Biopython: freely available Python tools for computational
molecular biology and bioinformatics
Peter J. A. Cock1,∗, Tiago Antao2, Jeffrey T. Chang3, Brad A. Chapman4, Cymon J. Cox5,
Andrew Dalke6, Iddo Friedberg7, Thomas Hamelryck8, Frank Kauff9,
Bartek Wilczynski10,11 and Michiel J. L. de Hoon12
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, Meyerhofstraße 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
Received and revised on March 11, 2009; accepted on March 16, 2009
Advance Access publication March 20, 2009
Associate Editor: Dmitrij Frishman
ABSTRACT
Summary: The Biopython project is a mature open source inter-
national 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@scri.ac.uk.
1 INTRODUCTION
Python (www.python.org) and Biopython are freely available open
source tools, available for all the major operating systems. Python is
a very high-level programming language, in widespread commercial
and academic use. It features an easy to learn syntax, object-
oriented programming capabilities and a wide array of libraries.
Python can interface to optimized code written in C, C++ or even
FORTRAN, and together with the Numerical Python project numpy
(Oliphant, 2006), makes a good choice for scientific programming
(Oliphant, 2007). Python has even been used in the numerically
demanding field of molecular dynamics (Hinsen, 2000). There
are also high-quality plotting libraries such as matplotlib
(matplotlib.sourceforge.net) available.
∗To whom correspondence should be addressed.
Since its founding in 1999 (Chapman and Chang, 2000),
Biopython has grown into a large collection of modules, described
briefly below, intended for computational biology or bioinformatics
programmers to use in scripts or incorporate into their own software.
Our web site lists over 100 publications using or citing Biopython.
The Open Bioinformatics Foundation (OBF, www.open-bio.org)
hosts our web site, source code repository, bug tracking database
and email mailing lists, and also supports the related BioPerl
(Stajich et al., 2002), BioJava (Holland et al., 2008), BioRuby
(www.bioruby.org) and BioSQL (www.biosql.org) projects.
2 BIOPYTHON FEATURES
The Seq object is Biopython’s core sequence representation. It
behaves very much like a Python string but with the addition of
an alphabet (allowing explicit declaration of a protein sequence for
example) and some key biologically relevant methods. For example,
>>> from Bio.Seq import Seq
>>> from Bio.Alphabet import generic_dna
>>> gene = Seq("ATGAAAGCAATTTTCGTACTG"
... "AAAGGTTGGTGGCGCACTTGA",
... generic_dna)
>>> print gene.transcribe()
AUGAAAGCAAUUUUCGUACUGAAAGGUUGGUGGCGCACUUGA
>>> print gene.translate(table=11)
MKAIFVLKGWWRT*
Sequence annotation is represented using SeqRecord objects
which augment a Seq object with properties such as the record
name, identifier and description and space for additional key/value
terms. The SeqRecord can also hold a list of SeqFeature
© 2009 The Author(s)
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.

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Biopython
Table 1. Selected Bio.SeqIO or Bio.AlignIO file formats
Format R/W Name and reference
fasta R+W FASTA (Pearson and Lipman, 1988)
genbank R+W GenBank (Benson et al., 2007)
embl R EMBL (Kulikova et al., 2006)
swiss R Swiss-Prot/TrEMBL or UniProtKB
(The UniProt Consortium, 2007)
clustal R+W Clustal W (Thompson et al., 1994)
phylip R+W PHYLIP (Felsenstein, 1989)
stockholm R+W Stockholm or Pfam (Bateman et al., 2004)
nexus R+W NEXUS (Maddison et al., 1997)
Where possible, our format names (column ‘Format’) match BioPerl and EMBOSS
(Rice et al., 2000). Column ‘R/W’ denotes support for reading (R) and writing (W).
objects which describe sub-features of the sequence with their
location and their own annotation.
The Bio.SeqIO module provides a simple interface for
reading and writing biological sequence files in various formats
(Table 1), where regardless of the file format, the information
is held as SeqRecord objects. Bio.SeqIO interprets multiple
sequence alignment file formats as collections of equal length
(gapped) sequences. Alternatively, Bio.AlignIO works directly
with alignments, including files holding more than one alignment
(e.g. re-sampled alignments for bootstrapping, or multiple pairwise
alignments). Related module Bio.Nexus, developed for Kauff
et al. (2007), supports phylogenetic tools using the NEXUS interface
(Maddison et al., 1997) or the Newick standard tree format.
Modules for a number of online databases are included, such as
the NCBI Entrez Utilities, ExPASy, InterPro, KEGG and SCOP.
Bio.Blast can call the NCBI’s online Blast server or a local
standalone installation, and includes a parser for their XML output.
Biopython has wrapper code for other command line tools too, such
as ClustalW and EMBOSS. The Bio.PDB module provides a PDB
file parser, and functionality related to macromolecular structure
(Hamelryck and Manderick, 2003). Module Bio.Motif provides
support for sequence motif analysis (searching, comparing and
de novo learning). Biopython’s graphical output capabilities were
recently significantly extended by the inclusion of GenomeDiagram
(Pritchard et al., 2006).
Biopython contains modules for supervised statistical learning,
such as Bayesian methods and Markov models, as well as unsu-
pervised learning, such as clustering (De Hoon et al., 2004).
The population genetics module provides wrappers for GENEPOP
(Rousset, 2007), coalescent simulation via SIMCOAL2 (Laval and
Excoffier, 2004) and selection detection based on a well-evaluated
Fst-outlier detection method (Beaumont and Nichols, 1996).
BioSQL (www.biosql.org) is another OBF supported initiative,
a joint collaboration between BioPerl, Biopython, BioJava and
BioRuby to support loading and retrieving annotated sequences to
and from an SQL database using a standard schema. Each project
provides an object-relational mapping (ORM) between the shared
schema and its own object model (a SeqRecord in Biopython).
As an example, xBASE (Chaudhuri and Pallen, 2006) uses BioSQL
with both BioPerl and Biopython.
3 CONCLUSIONS
Biopython is a large open-source application programming interface
(API) used in both bioinformatics software development and
in everyday scripts for common bioinformatics tasks. The
homepage www.biopython.org provides access to the source code,
documentation and mailing lists. The features described herein are
only a subset; potential users should refer to the tutorial and API
documentation for further information.
ACKNOWLEDGEMENTS
The OBF hosts and supports the project. The many Biopython
contributors over the years are warmly thanked, a list too long to be
reproduced here.
Funding: Fundacao para a Ciencia e Tecnologia (Portugal) (grant
SFRH/BD/30834/2006 to T.A.).
Conflict of Interest: none declared.
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