Welcome to the OmniSearch Project

Funded by National Institutes of Health (NIH)/NCI 1U01CA180982-01A1under ITCR Initiative


microRNAs (short for miRNAs or miRs) are a special class of small, non-coding RNA molecules and have been reported to perform important roles in various biological and pathological processes by regulating their respective target genes (short for targets). As such, miRNAs are closely associated with the development, diagnosis, and prognosis of various human diseases including cancer. In fact, prior research has demonstrated that miRNAs may provide critical insights with regard to many aspects of human diseases, including early diagnosis, personalized treatment, prognosis prediction, and so forth.


However, miRNA knowledge acquisition still remains challenging despite of many research efforts in this area. To completely understand and fully delineate miRNA functions, besides performing direct biological experiments in "wet" labs, biologists and bioinformaticians can also query PubMed and TarBase for biologically validated miRNA targets, and various miRNA target prediction databases or websites for computationally predicted targets as well. There exist two significant barriers in this scenario: (1) The number of distinct miRNA target prediction databases is in the neighborhood of 30. Moreover, different databases utilize different prediction algorithms, and more importantly, these databases have, more often than not, quite heterogeneous semantics (that is, the meaning of data) among each other. (2) Each individual miRNA may target on up to hundreds or even more genes. For each and every target gene, either biologically validated or computationally putative, it is often necessary to extract and obtain additional information from other data sources, such as gene expression, protein functions, and affiliated signaling pathways, because such additional information is critical in helping biologists to better explore functions performed by miRNAs. Similarly, these involved data sources are inherently heterogeneous with each other. In short, biologists and bioinformaticians are facing significant barriers in fully delineating miRNA functions and the following effective bio-curation.


To tackle the above-mentioned challenge, we will develop OmniSearch, a semantic search tool, to assist biologists, cancer biologists in particular, in unraveling critical roles of miRNAs in human cancers in an automated and highly efficient manner. We will handle the significant challenge of data sharing, data integration, and effective search in miRNA research in human oncology.

 

Latest News   


11/21/2015 - Paper Accepted
Our paper, A domain ontology for the non-coding RNA field, was accepted and published in Proc. 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM-15), IEEE, Washington D.C., Nov. 2015.

11/21/2015 - Paper Accepted
Our paper, A semantic approach for knowledge capture of microRNA-target gene interactions, was accepted and published in Proc. BHI Workshop at 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM-15), IEEE, Washington D.C., Nov. 2015.



May 2015 � Book Editing
We are editing the book of Bioinformatics in microRNA research: computational methods in exploring microRNAs' functions, which is part of Springer series of Methods in Molecular Biology.


07/19/2014 - Paper Accepted
Our paper, OmniSearch: A Dynamic microRNA Domain Ontology for Microgenomics Knowledge Discovery, Unification, and Bio-Curation, was accepted and published by PLOS ONE.


11/17/2013 - Paper Submitted
Our paper, OmniSearch: A Dynamic microRNA Domain Ontology for Microgenomics Knowledge Discovery, Unification, and Bio-Curation, was submitted to and is currently under review in PLOS ONE.


10/15/2013 - Paper Accepted
Our paper, Semi-Automated microRNA Ontology Development based on Artificial Neural Networks, was accepted and published in Proc. 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2013), Shanghai, China, December 2013.


10/12/2013 - Paper Accepted
Our paper, Semantics-Driven Frequent Data Pattern Mining on Electronic Health Records for Effective Adverse Drug Event Monitoring, was accepted and published in Proc. 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2013), Shanghai, China, December 2013.


08/15/2012 - Paper Accepted
Our paper, An Ontology-Based MicroRNA Knowledge Sharing and Acquisition Framework, was accepted and published in Proc. BHI Workshop at 2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2012), Philadelphia, PA, October 2012.


12/17/2011 - Paper Accepted
Our paper, Knowledge Acquisition, Semantic Text Mining, and Security Risks in Health and Biomedical Informatics, was accepted and published by World Journal of Biological Chemistry, 3(2): 27-33 (PDF), Baishideng, February 2012 (doi: 10.4331/wjbc.v3.i2.27).


06/18/2011 - Paper Accepted
Our paper, OmniSearch: A Domain-Specific Knowledge Base for MicroRNA Target Prediction, was accepted and published by Pharmaceutical Research (impact factor: 4.74) (PDF), Springer, August 2011 (doi:10.1007/s11095-011-0573-8).


08/28/2010 - Paper Accepted
Our paper, OmniSearch: Domain Ontology and Knowledge Acquisition in MicroRNA Target Prediction, was accepted and published in Proc. Ninth International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2010), Crete, Greece, October 2010.


06/21/2010 - Paper Accepted
Our paper, Ontology for MiRNA Target Prediction in Human Cancer, was accepted and published in Proc. First ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB 2010), Niagara Falls, NY, August 2010.


06/06/2010 - Paper Accepted
Our paper, Ontology-Based Knowledge Discovery and Sharing in Bioinformatics and Medical Informatics: A Brief Survey, was accepted and published by Proc. Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2010), Yantai, China, August 2010.


06/01/2010 - Ontology Submitted to NCBO (the National Center for Biomedical Ontology)
The OmniSearch ontology was submitted to the NCBO BioPortal (OmniSearch in NCBO).