Knowledge Base Associated with Autism Construction Using CRFs Learning


Ronggen Yang, Lejun Gong, Journal of Information Processing Systems Vol. 15, No. 6, pp. 1326-1334, Dec. 2019  

10.3745/JIPS.04.0146
Keywords: Autism, Biological Molecular, Conditional Random Fields, Knowledge Base
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Abstract

Knowledge base means a library stored in computer system providing useful information or appropriate solutions to specific area. Knowledge base associated with autism is the complex multidimensional information set related to the disease autism for its pathogenic factor and therapy. This paper focuses on the knowledge of biological molecular information extracted from massive biomedical texts with the aid of widespread used machine learning methods. Six classes of biological molecular information (such as protein, DNA, RNA, cell line, cell component, and cell type) are concerned and the probability statistics method, conditional random fields (CRFs), is utilized to discover these knowledges in this work. The knowledge base can help biologists to etiological analysis and pharmacists to drug development, which can at least answer four questions in question-answering (QA) system, i.e., which proteins are most related to the disease autism, which DNAs play important role to the development of autism, which cell types have the correlation to autism and which cell components participate the process to autism. The work can be visited by the address http://134.175.110.97/bioinfo/index.jsp.


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Cite this article
[APA Style]
Yang, R. & Gong, L. (2019). Knowledge Base Associated with Autism Construction Using CRFs Learning. Journal of Information Processing Systems, 15(6), 1326-1334. DOI: 10.3745/JIPS.04.0146.

[IEEE Style]
R. Yang and L. Gong, "Knowledge Base Associated with Autism Construction Using CRFs Learning," Journal of Information Processing Systems, vol. 15, no. 6, pp. 1326-1334, 2019. DOI: 10.3745/JIPS.04.0146.

[ACM Style]
Ronggen Yang and Lejun Gong. 2019. Knowledge Base Associated with Autism Construction Using CRFs Learning. Journal of Information Processing Systems, 15, 6, (2019), 1326-1334. DOI: 10.3745/JIPS.04.0146.