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GPSRdocker: A Docker-based Resource for Genomics, Proteomics and Systems biology

By Piyush Agrawal, Rajesh Kumar, Salman Sadullah Usmani, Anjali Dhall, Sumeet Patiyal, Neelam Sharma, Harpreet Kaur, Vinod Kumar, Dilraj Kaur, Shipra Jain, Akshara Pande, Sherry Bhalla, Gajendra P.S. Raghava

Posted 01 Nov 2019
bioRxiv DOI: 10.1101/827766

Background In past number of web-based resources has been developed in the field of Bioinformatics. These resources are heavily used by scientific community to provide solution for challenges faced by experimental researchers particularly in the field of biomedical sciences. There are number of challenges in utilizing full potential of these services that includes internet speed, limits on computing power, and security of data. In order to enhance utilities of these web-based assets, we developed a docker-based container that integrates large number resources available in literature. Results This paper describes GPSRdocker a docker-based container developed for providing wide-range of computational tools in the field of bioinformatics particularly in genomics, proteomics and system biology. Majority of tools integrated in GPSRdocker are based on web services developed at Raghava’s group in last two decades. Broadly, these tools can be categorized in three categories; i) general scripts, ii) supporting software and iii) major standalone software. In order to facilitate students or developers working in the field of bioinformatics, we developed general scripts in Perl and Python. These general-purpose scripts serve as building block for any bioinformatics tools like computing features/descriptors of a protein. Supporting software packages includes SCIKIT, WEKA, SVMlight, and PSI-BLAST; these software packages allow one to develop/implement bioinformatics software. Major Standalone software is core of this container which allows predicting function/class of biomolecules. These tools can be classified broadly in following categories; protein annotation, epitope-based vaccines, prediction of interaction and drug discovery. Conclusion A docker-based container has been developed which can be easily run on any operating system as well as it can be directly ported on cloud. Scripts can be run to build pipelines for addressing problems at system level like prediction of vaccine candidate for a pathogen. GPSRdocker including manual is available free for academic use from <https://webs.iiitd.edu.in/gpsrdocker>.

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