Abstract:
BACKGROUND:As molecular biology is creating an increasing amount of sequence and structure data, the multitude of software to analyze this data is also rising. Most of the programs are made for a specific task, hence the user often needs to combine multiple programs in order to reach a goal. This can make the data processing unhandy, inflexible and even inefficient due to an overhead of read/write operations. Therefore, it is crucial to have a comprehensive, accessible and efficient computational biology framework in a scripting language to overcome these limitations. RESULTS:We have developed the Python package Biotite: a general computational biology framework, that represents sequence and structure data based on NumPyndarrays. Furthermore the package contains seamless interfaces to biological databases and external software. The source code is freely accessible at https://github.com/biotite-dev/biotite . CONCLUSIONS:Biotite is unifying in two ways: At first it bundles popular tasks in sequence analysis and structural bioinformatics in a consistently structured package. Secondly it adresses two groups of users: novice programmers get an easy access to Biotite due to its simplicity and the comprehensive documentation. On the other hand, advanced users can profit from its high performance and extensibility. They can implement their algorithms upon Biotite, so they can skip writing code for general functionality (like file parsers) and can focus on what their software makes unique.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Kunzmann P,Hamacher Kdoi
10.1186/s12859-018-2367-zsubject
Has Abstractpub_date
2018-10-01 00:00:00pages
346issue
1issn
1471-2105pii
10.1186/s12859-018-2367-zjournal_volume
19pub_type
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abstract:BACKGROUND:In real-time PCR, it is necessary to consider the efficiency of amplification (EA) of amplicons in order to determine initial target levels properly. EAs can be deduced from standard curves, but these involve extra effort and cost and may yield invalid EAs. Alternatively, EA can be extracted from individual ...
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journal_title:BMC bioinformatics
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journal_title:BMC bioinformatics
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更新日期:2010-02-25 00:00:00
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journal_title:BMC bioinformatics
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更新日期:2014-05-12 00:00:00
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更新日期:2011-07-26 00:00:00
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更新日期:2008-04-21 00:00:00