title: OMIT: dynamic, semi-automated ontology development for the microRNA domain.
abstract: As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.
authors.affiliation: School of Computing, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: Jingshan
authors.initials: J
authors.lastname: Huang
authors.affiliation: Corporate Technology, Siemens Corporation, Princeton, New Jersey, United States of America.
authors.forename: Jiangbo
authors.initials: J
authors.lastname: Dang
authors.affiliation: Department of Biology, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: Glen M
authors.initials: GM
authors.lastname: Borchert
authors.affiliation: School of Medicine, University of Utah, Salt Lake City, Utah, United States of America.
authors.forename: Karen
authors.initials: K
authors.lastname: Eilbeck
authors.affiliation: School of Computing, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: He
authors.initials: H
authors.lastname: Zhang
authors.affiliation: School of Computing, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: Min
authors.initials: M
authors.lastname: Xiong
authors.affiliation: School of Computing, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: Weijian
authors.initials: W
authors.lastname: Jiang
authors.affiliation: School of Computing, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: Hao
authors.initials: H
authors.lastname: Wu
authors.affiliation: The Jackson Laboratory, Bar Harbor, Maine, United States of America.
authors.forename: Judith A
authors.initials: JA
authors.lastname: Blake
authors.affiliation: Georgetown University Medical Center, Washington, DC, United States of America.
authors.forename: Darren A
authors.initials: DA
authors.lastname: Natale
authors.affiliation: Mitchell Cancer Institute, University of South Alabama, Mobile, Alabama, United States of America.
authors.forename: Ming
authors.initials: M
authors.lastname: Tan
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D063990:Gene Ontology; D006801:Humans; D035683:MicroRNAs / Q000235:genetics* / Q000378:metabolism; D034622:RNA Interference; D012333:RNA, Messenger / Q000235:genetics* / Q000378:metabolism
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger