StemTextSearch: Stem cell gene database with evidence from abstracts.
Previous studies have used many methods to find biomarkers in stem cells, including text mining, experimental data and image storage. However, no text-mining methods have yet been developed which can identify whether a gene plays a positive or negative role in stem cells.



StemTextSearch identifies the role of a gene in stem cells by using a text-mining method to find combinations of gene regulation, stem-cell regulation and cell processes in the same sentences of biomedical abstracts.



The dataset includes 5797 genes, with 1534 genes having positive roles in stem cells, 1335 genes having negative roles, 1654 genes with both positive and negative roles, and 1274 with an uncertain role. The precision of gene role in StemTextSearch is 0.66, and the recall is 0.78. StemTextSearch is a web-based engine with queries that specify (i) gene, (ii) category of stem cell, (iii) gene role, (iv) gene regulation, (v) cell process, (vi) stem-cell regulation, and (vii) species. StemTextSearch is available through http://bio.yungyun.com.tw/StemTextSearch.aspx.
Department of Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan. Electronic address: new.purple@msa.hinet.net.
Chou-Cheng
CC
Chen
Department of Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan; Department of Pathology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan; Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan. Electronic address: clh9@mail.ncku.edu.tw.
Chung-Liang
CL
Ho
D057225:Data Mining; D030541:Databases, Genetic; D015870:Gene Expression; D005796:Genes / Q000502:physiology*; D020407:Internet; D013234:Stem Cells
Gene role; Stem cell; Text mining