Biotite: a unifying open source computational biology framework in Python
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 ca...
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| Published in | BMC bioinformatics Vol. 19; no. 1; pp. 346 - 8 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
01.10.2018
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1471-2105 1471-2105 |
| DOI | 10.1186/s12859-018-2367-z |
Cover
| Summary: | 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
NumPy
ndarrays
. 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. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 1471-2105 1471-2105 |
| DOI: | 10.1186/s12859-018-2367-z |