W28–W32 Nucleic Acids Research, 2009, Vol. 37, Web Server issue doi:10.1093/nar/gkp354 Published online 11 May 2009 BioBIKE: A Web-based, programmable, integrated biological knowledge base Jeff Elhai1, Arnaud Taton 1 , JP Massar2, John K. Myers3, Mike Travers4, Johnny Casey3, Mark Slupesky2 and Jeff Shrager4,5,* 1Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond VA, 2Berkeley CA, USA, 3Sequoia Consulting, North Hills, 4CollabRx, Inc., Palo Alto and 5Symbolic Systems Program (consulting), Stanford University, Stanford, CA, USA Received January 31, 2009; Revised April 15, 2009; Accepted April 23, 2009 ABSTRACT BioBIKE (biobike.csbc.vcu.edu) is a web-based environment enabling biologists with little pro- gramming expertise to combine tools, data, and knowledge in novel and possibly complex ways, as demanded by the biological problem at hand. BioBIKE is composed of three integrated compo- nents: a biological knowledge base, a graphical programming interface and an extensible set of tools. Each of the five current BioBIKE instances provides all available information (genomic, meta- bolic, experimental) appropriate to a given research community. The BioBIKE programming language and graphical programming interface employ famil- iar operations to help users combine functions and information to conduct biologically meaningful ana- lyses. Many commonly used tools, such as Blast and PHYLIP, are built-in, allowing users to access them within the same interface and to pass results from one to another. Users may also invent their own tools, packaging complex expressions under a single name, which is immediately made accessible through the graphical interface. BioBIKE represents a partial solution to the difficult question of how to enable those with no background in computer programming to work directly and creatively with mass biological information. BioBIKE is distributed under the MIT Open Source license. A description of the underlying language and other technical matters is available at www.Biobike.org. INTRODUCTION Research in all areas of biology has come increasingly to rely upon massive sets of digital data and knowledge, the manipulation of which places most researchers outside their area of comfort. Despite a spectacular range of resources available to analyze biological information (witness this issue of NAR), biological problems still often require the development of novel methods. Existing tools may display results that are easy for humans to read, but they generally do not deliver them in a form that is useful for subsequent computations. Biologists without programming expertise (no doubt the majority) muddle through as best they can, using isolated tools and spreadsheets, or seeking the help of program- mers. In the latter case, the resulting division of knowledge is far from ideal, obscuring the process from the biologist’s view and making it diﬃcult to understand the meaning of the results. Moreover, the biologist loses easy access to surprising intermediate results, which are at the heart of fundamental accidental discoveries (Elhai et al., manuscript submitted for publication). BioBIKE (the Biological Integrated Knowledge Environment; formerly BioLingua, 1) has been developed to allow researchers without programming expertise to combine tools, data and knowledge in ways demanded by the biological problem at hand. BioBIKE is composed of three integrated components: (i) a biological knowledge base, (ii) a graphical programming interface and (iii) an extensible set of tools that can be combined in novel ways. BioBIKE INSTANCES AND THEIR KNOWLEDGE AND DATA BASES A BioBIKE instance provides a framework for all avail- able information needed by a given research community (Table 1), including sets of genomic sequences, gene annotations, functional descriptions, formal categories (e.g. COG), hierarchical groupings of metabolic reactions linked with genes (from KEGG, 2) and internal tables of Blast scores to support rapid protein comparisons. In addition, an instance may be stocked with experimental data, such as results from microarray or proteomic experi- ments. Indeed, any data that can be put into a standard- ized form, such as a table or XML structure, can be *To whom correspondence should be addressed. Tel: +1 650 380 6306; Email: jshrager@stanford.edu 2009 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.