WeBIAS: a web server for publishing bioinformatics applications

BMC Research Notes

Bogdan Lesyng²  Bartek Wilczyński¹  Paweł Daniluk² 

[1] Institute of Informatics, University of Warsaw, Warsaw, Poland;Department of Biophysics, Faculty of Physics, University of Warsaw, Warsaw, Poland

关键词: Web services;    Software engineering;    Programming;    Bioinformatics;   

Others  :  1232870
DOI  :  10.1186/s13104-015-1622-x

 received in 2015-05-08, accepted in 2015-10-26,  发布年份 2015

【 摘 要 】

Background

One of the requirements for a successful scientific tool is its availability. Developing a functional web service, however, is usually considered a mundane and ungratifying task, and quite often neglected. When publishing bioinformatic applications, such attitude puts additional burden on the reviewers who have to cope with poorly designed interfaces in order to assess quality of presented methods, as well as impairs actual usefulness to the scientific community at large.

Results

In this note we present WeBIAS—a simple, self-contained solution to make command-line programs accessible through web forms. It comprises a web portal capable of serving several applications and backend schedulers which carry out computations. The server handles user registration and authentication, stores queries and results, and provides a convenient administrator interface. WeBIAS is implemented in Python and available under GNU Affero General Public License. It has been developed and tested on GNU/Linux compatible platforms covering a vast majority of operational WWW servers. Since it is written in pure Python, it should be easy to deploy also on all other platforms supporting Python (e.g. Windows, Mac OS X). Documentation and source code, as well as a demonstration site are available at http://bioinfo.imdik.pan.pl/webias.

Conclusions

WeBIAS has been designed specifically with ease of installation and deployment of services in mind. Setting up a simple application requires minimal effort, yet it is possible to create visually appealing, feature-rich interfaces for query submission and presentation of results.

【 授权许可】

   
2015 Daniluk et al.

【 图 表 】

Fig. 1.

Fig. 2.

Fig. 3.

【 参考文献 】

• [1]Senger M, Rice P, Bleasby A, Oinn T, Uludag M. Soaplab2: more reliable Sesame door to bioinformatics programs. In: Bioinformatics Open Source Conference, BOSC, vol 8. 2008.
• [2]Ren J, Williams N, Clementi L, Krishnan S, Li WW: Opal web services for biomedical applications. Nucleic Acids Res. 2010, 38(suppl 2):724-731.
• [3]Giardine B, Riemer C, Hardison RC, Burhans R, Elnitski L, Shah P, Zhang Y, Blankenberg D, Albert I, Taylor J: Galaxy: a platform for interactive large-scale genome analysis. Genome Res. 2005, 15(10):1451-1455.
• [4]Oinn T, Addis M, Ferris J, Marvin D, Senger M, Greenwood M, Carver T, Glover K, Pocock MR, Wipat A: Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics. 2004, 20(17):3045-3054.
• [5]Papanicolaou A, Heckel DG: The GMOD Drupal Bioinformatic Server Framework. Bioinformatics. 2010, 26(24):3119-3124.
• [6]Néron B, Ménager H, Maufrais C, Joly N, Maupetit J, Letort S, Carrere S, Tuffery P, Letondal C: Mobyle: a new full web bioinformatics framework. Bioinformatics. 2009, 25(22):3005-3011.
• [7]Delon R, Brewer R, Hellegouarch S, Wyglendowski C, Wecker L. CherryPy 3.6: A Minimalist Python Web Framework. 2015. http://cherrypy.org. Accessed 2015.
• [8]Bayer M. SQLAlchemy: The Python SQL Toolkit and Object Relational Mapper. http://www.sqlalchemy.org. Accessed 30 Oct 2015.
• [9]Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, Friedberg I, Hamelryck T, Kauff F, Wilczynski B, de Hoon MJL: Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009, 25(11):1422-1423.
• [10]Mertz D, McIngvale F. Gnosis Utils 1.2.2. http://www.gnosis.cx/download. Accessed 30 Oct 2015.
• [11]Thomas A, Lenz C, Borgström J, Good M, Cross S. Genshi 0.6: Python Toolkit for Generation of Output for the Web. http://genshi.edgewall.org. Accessed 30 Oct 2015.
• [12]Daniluk P. Essentia Proteomica. http://dworkowa.imdik.pan.pl/EP. Accessed 30 Oct 2015.
• [13]Daniluk P, Lesyng B: A novel method to compare protein structures using local descriptors. BMC Bioinform. 2011, 12(1):344. BioMed Central Full Text
• [14]Dziubiński M, Daniluk P, Lesyng B. ResiCon: a method for the identification of dynamic domains, hinges and interfacial regions in proteins. Bioinformatics. 2015.. 10.1093/bioinformatics/btv525 webcite
• [15]Wilczynski B, Darzynkiewicz M, Tiuryn J. MEMOFinder: combining de novo motif prediction methods with a database of known motifs. Nature Precedings. 2008. Available from. http://hdl.handle.net/10101/npre.2008.2289.2 webcite
• [16]Wilczyński B, Dojer N: BNFinder: exact and efficient method for learning Bayesian networks. Bioinformatics. 2009, 25(2):286-287.