The study of complex biological systems increasingly depends on vast amounts of dynamic information from diverse sources. The scientific analysis of the parasite Trypanosoma cruzi (T.cruzi), the principal causative agent of human Chagas disease, is the driving biological application of this proposal. Approximately 18 million people, predominantly in Latin America, are infected with the T.cruzi parasite. As many as 40 percent of these are predicted eventually to suffer from Chagas disease, which is the leading cause of heart disease and sudden death in middle-aged adults in the region. Research on T. cruzi is therefore an important human disease related effort. It has reached a critical juncture with the quantities of experimental data being generated by labs around the world, due in large part to the publication of the T.cruzi genome in 2005. Although this research has the potential to improve human health significantly, the data being generated exist in independent heterogeneous databases with poor integration and accessibility. The scientific objectives of this research proposal are to develop and deploy a novel ontology-driven semantic problem-solving environment (PSE) for T.cruzi. This is in collaboration with the National Center for Biomedical Ontologies (NCBO) and will leverage its resources to achieve the objectives of this proposal as well as effectively to disseminate results to the broader life science community, including researchers in human pathogens. The PSE allows the dynamic integration of local and public data to answer biological questions at multiple levels of granularity. The PSE will utilize state-of- the-art semantic technologies for effective querying of multiple databases and, just as important, feature an intuitive and comprehensive set of interfaces for usability and easy adoption by biologists. Included in the multimodal datasets will be the genomic data and the associated bioinformatics predictions, functional information from metabolic pathways, experimental data from mass spectrometry and microarray experiments, and textual information from Pubmed. Researchers will be able to use and contribute to a rigorously curated T.cruzi knowledge base that will make it reusable and extensible. The resources developed as part of this proposal will be also useful to researchers in T.cruzi related kinetoplastids, Trypanosoma brucei and Leishmania major (among other pathogenic organisms), which use similar research protocols and face similar informatics challenges.
The scientific objective of this proposal is to develop and deploy a novel ontology-driven semantic problem-solving environment (PSE) for Trypanosoma cruzi, a parasite that infects approximately 18 million people, predominantly in Latin America. As many as 40 percent of those infected are predicted to eventually suffer from Chagas disease, the leading cause of heart disease and sudden death in middle-aged adults in the region. Facilitating T.cruzi research through the PSE, with the aim of identifying vaccine, diagnostic, and therapeutic targets, is an important human disease related endeavor.
|Thayasivam, Uthayasanker; Doshi, Prashant (2013) Speeding up Batch Alignment of Large Ontologies Using MapReduce. Proc IEEE Int Conf Semant Comput 2013:110-113|
|Parikh, Priti P; Minning, Todd A; Nguyen, Vinh et al. (2012) A semantic problem solving environment for integrative parasite research: identification of intervention targets for Trypanosoma cruzi. PLoS Negl Trop Dis 6:e1458|
|Sahoo, Satya S; Nguyen, Vinh; Bodenreider, Olivier et al. (2011) A unified framework for managing provenance information in translational research. BMC Bioinformatics 12:461|
|Sahoo, Satya S; Bodenreider, Olivier; Hitzler, Pascal et al. (2010) Provenance Context Entity (PaCE): Scalable Provenance Tracking for Scientific RDF Data. Sci Stat Database Manag 6187:461-470|
|Doshi, Prashant; Kolli, Ravikanth; Thomas, Christopher (2009) Inexact Matching of Ontology Graphs Using Expectation-Maximization. Web Semant 7:90-106|