iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

[1]  David N. Kennedy,et al.  The internet analysis tools registry A public resource for image analysis , 2007, Neuroinformatics.

[2]  Arthur W. Toga,et al.  Erratum to “A meta-algorithm for brain extraction in MRI” [NeuroImage 23 (2004) 625–637] , 2008, NeuroImage.

[3]  Hideki Koike,et al.  Fractal approaches for visualizing huge hierarchies , 1993, Proceedings 1993 IEEE Symposium on Visual Languages.

[4]  Luciano da Fontoura Costa,et al.  Skeletonization of two-dimensional shapes via fast numerical calculation of vector fields , 2004, Proceedings. 17th Brazilian Symposium on Computer Graphics and Image Processing.

[5]  Elarbi Badidi,et al.  AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis , 2003, BMC Bioinformatics.

[6]  A. Bonato,et al.  Graphs and Hypergraphs , 2022 .

[7]  Sanjiva Weerawarana,et al.  Unraveling the Web services web: an introduction to SOAP, WSDL, and UDDI , 2002, IEEE Internet Computing.

[8]  Christopher J. Lee,et al.  A genomic view of alternative splicing , 2002, Nature Genetics.

[9]  Martin Vingron,et al.  CORG: a database for COmparative Regulatory Genomics , 2003, Nucleic Acids Res..

[10]  Russ B. Altman,et al.  Time to Organize the Bioinformatics Resourceome , 2005, PLoS Comput. Biol..

[11]  Lihong V. Wang,et al.  2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano , 2004 .

[12]  Arthur W. Toga,et al.  The LONI Debabeler: a mediator for neuroimaging software , 2005, NeuroImage.

[13]  Ramana Rao,et al.  Laying out and visualizing large trees using a hyperbolic space , 1994, UIST '94.

[14]  Thomas E. Wehrly,et al.  An Invariant Approach to Statistical Analysis of Shapes , 2004, Technometrics.

[15]  You Jung Kim,et al.  miBLAST: scalable evaluation of a batch of nucleotide sequence queries with BLAST , 2005, Nucleic acids research.

[16]  Jerrold E. Marsden,et al.  Well-posed quasi-linear second-order hyperbolic systems with applications to nonlinear elastodynamics and general relativity , 1977 .

[17]  Peter Kiernan Extensions of holomorphic maps , 1972 .

[18]  Arthur W. Toga,et al.  A meta-algorithm for brain extraction in MRI , 2004, NeuroImage.

[19]  Arthur W Toga,et al.  The LONI Pipeline Processing Environment , 2003, NeuroImage.

[20]  N. Harris,et al.  Genotator: a workbench for sequence annotation. , 1997, Genome research.

[21]  Stanley Osher,et al.  Level Set Methods , 2003 .

[22]  Ron Kikinis,et al.  3D Slicer , 2012, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[23]  Mark D. Wilkinson,et al.  BioMOBY: An Open Source Biological Web Services Proposal , 2002, Briefings Bioinform..

[24]  Paul M. Thompson,et al.  Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models , 2008, IEEE Transactions on Medical Imaging.

[25]  Pat Hanrahan,et al.  Interactive visualization of large graphs and networks , 2000 .

[26]  S. Osher,et al.  Geometric Level Set Methods in Imaging, Vision, and Graphics , 2011, Springer New York.

[27]  Thomas L. Madden,et al.  BLAST: at the core of a powerful and diverse set of sequence analysis tools , 2004, Nucleic Acids Res..