The Bioperl toolkit: Perl modules for the life sciences.

By Jason E. Stajich, David Block, K. Boulez, Steven E. Brenner, S. Chervitz, Chris Dagdigian, Georg Fuellen, James G. R. Gilbert, Ian Korf, H. Lapp and 11 more. 2002

1,736 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology

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Citations in the corpus

Biopython: freely available Python tools for computational molecular biology and bioinformatics (2009, background): “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.”
Population Genomics: Whole-Genome Analysis of Polymorphism and Divergence in Drosophila simulans (2007, methodology): “PAML was run in batch mode using a BioPerl wrapper [132].”
RBPDB: a database of RNA-binding specificities (2010, methodology): “When only the identity of bound genes or transcripts is reported, we compiled the transcript or gene sequence retrieved from GenBank using BioPerl (33), or from batch download ﬁles from FlyBase, and reported this sequence along with its associated numerical value.”
A beginner's guide to eukaryotic genome annotation (2012, methodology): “BioPerl 88 also provides a set of database tools for loading GFF3 files into a ready-made Chado 89 database schema with which an online genome database can be rapidly created that contains a genome and its annotations in a ‘browse-able’ format.”
Large-scale in silico and microarray-based identification of direct 1,25-dihydroxyvitamin D3 target genes. (2005, methodology): “The algorithms were implemented with the Bioperl toolkit (51) and run on the bioinformatics cluster of The Quebec Bioinformatics Network (BioneQ; http://www.”
The Ensembl Variant Effect Predictor (2016, methodology): “Installation of the VEP script triggers automated installation of the Ensembl API, along with the BioPerl API [87] upon which the Ensembl API depends.”
SeqAn An efficient, generic C++ library for sequence analysis (2008, methodology): “Besides these C++ libraries, we are aware of alternative approaches like BioPerl [20] or BioJava [21].”
Phytozome: a comparative platform for green plant genomics (2011, methodology): “Open source visualization components of Phytozome include: Gbrowse (9), the Generic Genome Browser, from the GMOD project, for the visualization of features in their genomic context; Jalview (10), a multiple alignment viewer and editor, for the creation, detailed inspection and modification of multi”
The IntAct molecular interaction database in 2010 (2009, methodology): “For developers who do not use Java as their programming language, the support is limited to a number of libraries that can use PSI-MI XML as an input format, for example, the standalone RIntact R package (25), Bioconductor’s RpsiXML package (26) or the bioperlnetwork package for Perl (27).”
The Sequence Ontology: a tool for the unification of genome annotations (2005, methodology): “Feature_relationships between these objects were inferred from location information using the Bioperl Bio::SeqFeature::Tools::Unflattener code.”
BIGSdb: Scalable analysis of bacterial genome variation at the population level (2010, methodology): “Sequence handling routines are provided by the BIOPERL library [18] and EMBOSS suite of programs [19].”
Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences (2010, methodology): “Tutorials [4,5], software libraries such as Bioconductor [6] and Bioperl [7], and web-based interfaces for tools [8,9] all improve the accessibility of computation.”
BioJava: an open-source framework for bioinformatics (2008, methodology): “∗To whom correspondence should be addressed.”
OrganellarGenomeDRAW—a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets (2013, methodology): “For general parsing and manipulation of GenBank files, OGDRAWmakes use of software provided by the Bioperl project (25).”
Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes (2015, background): “General purpose Bioinformatics toolkits such as BioPerl [66] and BioPython [67] provide basic tools to import trees in the various formats.”
Fungal Community Analysis by Large-Scale Sequencing of Environmental Samples (2005, methodology): “Toolkit [32] and available from the authors upon request) was used to cluster”