Postgraduate Institute of Medicine University of Colombo

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Identifying a Gene-Gene Interaction Network for Pre-eclampsia Using Text Mining of PubMed Abstracts Pre-eclampsia is a hypertensive disorder in pregnancy which has a genetic component, and different genes interact with each other to bring about pre-eclampsia. Most recent data on genegene interactions can only be found in scientific literature. However, manual reading of all the literature to find specific information is now becoming impractical due the ever expanding volume of literature. In the current study, this problem was approached by applying text mining methods on PubMed abstracts. Relevant abstracts were retrieved from PubMed and sentence boundary detection was performed using the GeniaSS tool. Tokenizing and entity recognition were done using the GeniaTagger tool. Gene name normalization was done using a gene name dictionary created for the current work. A sentence which has more than one unique gene symbol and at least one interaction word was selected as a candidate sentence for further processing. Information was extracted by reading candidate sentences and a gene-gene interaction network was created. 457 sentences were selected as candidate sentences out of 11172 sentences found in 1188 abstracts. 42 sentences were found to be describing gene-gene interactions. There were 59 genes involved in 51 interactions. This approach was evaluated using a sample of 45 abstracts which had 435 sentences. It showed 61.5% recall and 28.5% precision. The current approach showed promising results, and it significantly reduced the manual reading work load. Dr. H.W.M.M Hapudeniya mmhapudeniya@gmail.com Supervisors: Prof. Vajira H. W. Dissanayake MBBS, PhD (Nottingham) Chairperson, Specialty Board in Biomedical Informatics Mr. Pubudu Samarakoon BSc, MSc (Bioinformatics) Member, Specialty Board in Biomedical Informatics 47 | P a g e
Visually Exploring the Gene Interaction Network in a Polygenic, Complex, Multifactorial Disease: Essential Hypertension Human essential hypertension (EH) is a complex, multifactorial disorder with genetic, environmental and demographic factors contribute to its aetiology and pathogenesis. It is estimated that globally, there will 1.56 billion people affected with the condition by the year 2025. It has been shown that multiple interactions exist among multiple genes in pathogenesis of essential hypertension. Epistasis is defined simply as „interaction with different genes‟. The more common polygenic form of essential hypertension develops as a consequences of epistasis. This work started with the identification of candidate genes associated with essential hypertension. For this purpose, abstracts published in PubMed database from 01/January/2000 to 01/December/2010 were used. There were 1105 abstracts. From these abstracts, a set of genes consisting of 153 essential hypertension related genes was created manually. Then a subset of ten genes was selected based on a scoring system using gene prospector. As the next step, a gene interaction network was created using Cytoscape. The elimination of the second hierarchical level of the network was done thereafter. The ultimate results gave a gene interaction network with first hierarchical level and statistical analysis. This gene interaction network is important in many ways. The finding of genes related to pathogenesis of essential hypertension is an exhausting task because relevant information in the biomedical literature remains hidden in the form of unstructured text. The other problem is that determining disease-related genes requires laborious experiments.Therefore predicting candidate genes before experimental analysis will save time effort and cost as well. Dr. Kamal Seneviratne kamalse1@gmail.com Supervisors: Prof. Vajira H. W. Dissanayake MBBS, PhD (Nottingham) Chairperson, Specialty Board in Biomedical Informatics Mr. Pubudu Samarakoon BSc, MSc (Bioinformatics) Member, Specialty Board in Biomedical Informatics 48 | P a g e
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