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Research and Implement of Gene-Gene Relations Mining System Based on Biomedical Literature

Author: ShenGengYu
Tutor: HuangShuiQing
School: Nanjing Agricultural College
Course: Information Science
Keywords: Text Mining Bioinformatics Information Extraction Biomedical Named EntityRecognition
CLC: TP391.1
Type: Master's thesis
Year: 2012
Downloads: 11
Quote: 0
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Abstract


Along with the high-throughput sequencing experimental methods are widely used in biomedical research,and the sequencing of the human genome and other species completed one after another. At the same time it brings lots of biological information and a progressive prospect for biomedical research. PubMed is the largest biomedical literature database,its indexed literature has reached an unprecedented degree of massive. How to help biomedical researchers ease the burden of reading a large amount of literatures?Take advantage of the state-of-the-art text mining techniques to assist biomedical researchers to discover the the literature various biological relationship is the purpose of this study.As the main object of biomedical text mining is the biomedical literature, the goal is the extraction of biological relationship that the text contains with the information extraction method. In this paper, from the perspective of the regulatory relationships between genes, this study try to extract the mutual relationships between two genes from a large amount of literatures and make use of visualization tools to visually show a network of relationships between genes which are describled in the literatures.Firstly, this paper summarized the existing literature-based systems of mining relationships between genes and simply introduced their mining method and characteristics.Secondly, According to biomedical text mining process,this paper carries out the study of gene named entity recognition within the Literature, information extraction of gene regulation and the visualization of gene regulatory relationships network.In the study of the gene named entity recognition,this paper combine the dictionary-based matching method with machine learning method to identify the gene names in the literature, and deal with the problem of synonyms to ensure a high recognition accuracy and recall rate. In the study of relationship extraction, according to the extracted verbs from biomolecules event corpus with the basic gene-verb-gene pattern rules, we successfully extracte the information from biomedical text,which describe the mutual relationship between two genes.And make use of visualization tools successfully build the gene regulatory relationships network with the structured information of gene regulation relationship.Thirdly, this study develope an text information extracting and results showing system based on the gene mutual relation mining procedures. And the system is designed by different modules, the following is the detailed description of each module’s functions and processes, and briefly describes the realization of the system.In respectively evaluated the recall and precision of gene name recognition,including the information extraction performance of gene-gene relations.The performance of gene name recognition is satisfactory,but there is a great opportunity for the improvement of the relation extraction. Then,the system carries out a mining experiment with gene research literature from some species such as Arabidopsis, rice, human,etc. At last, we analysis the running and mining performance of the system using the gene-gene relationship results extracted from Genetic research literature of different kind of species.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Text Processing
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