J
Jingshan Huang
Researcher at University of South Alabama
Publications - 74
Citations - 558
Jingshan Huang is an academic researcher from University of South Alabama. The author has contributed to research in topics: Ontology (information science) & Ontology-based data integration. The author has an hindex of 12, co-authored 73 publications receiving 446 citations. Previous affiliations of Jingshan Huang include Qilu University of Technology & University of South Carolina.
Papers
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Journal ArticleDOI
OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.
Jingshan Huang,Fernando Gutierrez,Harrison J. Strachan,Dejing Dou,Weili Huang,Barry Smith,Judith A. Blake,Karen Eilbeck,Darren A. Natale,Yu Lin,Bin Wu,Nisansa de Silva,Xiaowei Wang,Zixing Liu,Glen M. Borchert,Ming Tan,Alan Ruttenberg +16 more
TL;DR: The Ontology for MIcroRNA Target (OMIT) as mentioned in this paper is a domain-specific application ontology for semantic annotation, data integration, and semantic search in the miRNA field.
Ontology Matching Using an Artificial Neural Network to Learn Weights
TL;DR: This paper takes an artificial neural network approach to learning and adjusting the above weights, and thereby support a new ontology matching algorithm, with the purpose to avoid some of the disadvantages in both rule-based and learning-based ontological matching approaches.
Journal ArticleDOI
OMIT: Dynamic, Semi-Automated Ontology Development for the microRNA Domain
Jingshan Huang,Jiangbo Dang,Glen M. Borchert,Karen Eilbeck,He Zhang,Min Xiong,Weijian Jiang,Hao Wu,Judith A. Blake,Darren A. Natale,Ming Tan +10 more
TL;DR: 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 are explored.
Proceedings ArticleDOI
Discovering Inconsistencies in PubMed Abstracts through Ontology-Based Information Extraction
TL;DR: This study introduces the first ontology-based information extraction model introduced to find shifts in the established knowledge in the medical domain using research paper abstracts, and finds 102 inconsistencies relevant to the microRNA domain.
Journal ArticleDOI
miR-125b regulates differentiation and metabolic reprogramming of T cell acute lymphoblastic leukemia by directly targeting A20
Zixing Liu,Kelly R. Smith,Hung T. Khong,Jingshan Huang,Eun-Young Erin Ahn,Ming Zhou,Ming Tan +6 more
TL;DR: The data demonstrate that miR-125b regulates differentiation and reprogramming of T cell glucose metabolism via targeting A20, and provides novel insights into the understanding and treatment of T-ALL.