PLOS Computational Biology Software Collection: The Combination of Open Access and Open Source Accelerates Scientific Research
Today PLOS Computational Biology launched a collection of seven existing Software articles which present novel biological insights on an open access platform and break new ground by sharing the open source software that enabled the featured discoveries. This combination of Open Access and Open Source can only help push the development of computational biology’s many diverse fields – and create a model for other scientific disciplines.
According to the criteria for publication, all articles in the PLOS Computational Biology Software collection must use a license approved by the Open Source Initiative (OSI), thus enabling the modification of source codes for follow on innovations by subsequent researchers. Source code provides a human readable language for programmers to use when working with the machine code that drives a computer program. The early adoption of free and open source software by biologists was a direct result of the Herculean task they’ve faced over two decades of unprecedented progress in genomics and biomedical research – progress which has often depended on processing massive amounts of data about how cells, genes and proteain interact under various conditions. “Existing methods are often challenged by new types and amounts of data, so computational biologists create new pieces of software to analyze and interpret the data deluge.
The availability of open source software is of increased importance in the context of research where peer review, reproducibility, and building upon prior work are integral to the advancement of the science. Source code access also helps researchers quickly identify and remedy bugs that might lead to spurious results and adapt programs or pieces of code to suit individual needs, and allows expert users to contribute to code development on an informal basis.
The seven articles released today describe approaches to a wide range of biological problems that could enable advances in fields such as drug development and environmental cleanup. In an editorial introducing the collection, Software editors Andreas Prlić and Hilmar Lapp cite their objective to provide recognition to software developers who they propose are generally under appreciated by the current academic system. This Software Collection, part of The PLOS Computational Biology community journal, remains open for submissions.
PLOS Computational Biology is a peer-reviewed, open-access journal featuring works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. It is an official journal of the International Society for Computational Biology. The International Society for Computational Biology (ISCB) is a scholarly society dedicated to advancing the scientific understanding of living systems through computation. The Society serves over 3,000 members from more than 70 countries.
You can visit the collection at www.ploscollections.org/software.
[…] PLOS Computational Biology Software Collection: The Combination of Open Access and Open Source Accel… Today PLOS Computational Biology launched a collection of seven existing Software articles which present novel biological insights on an open access platform and break new ground by sharing the open source software that enabled the featured discoveries. This combination of Open Access and Open Source can only help push the development of computational biology’s many diverse fields – and create a model for other scientific disciplines. […]
It’s sad to admit it but research very often equals to re-re-re-re-research. With this I mean repeating over and over intead of thinking a way to solve the problem, or automate the repetition. There is a point at which software can give a standard the naked eye or brain can’t give, and good software really can do wonders. I must say that as researcher I started to feel much more complete when I learned programming, analysing images…
In my opinion biochemistry+bioinformatics=win.
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