TILD: A strategy to identify cancer-related genes using title information in literature data

Jeongwoo Kim, Hyunjin Kim, Yunku Yeu, Mincheol Shin, Sanghyun Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

After genome project in 1990s, researches which are involved with gene have been progressed. These studies unearthed that gene is cause of disease, and relations between gene and disease are important. In this reason, we proposed a strategy called TILD that identifies cancer-related genes using title information in literature data. To implement our method, we selected cancerspecific literature data from the online database. We then extracted genes using text mining. In the next step, we classified into two kinds for extracted genes using title information. If genes are located in title, then they are classified as hub genes. In the contrast, if genes are located in body, then they are classified as sub genes which are connected with hub genes. We iterated the processes for each paper to construct the cancer-specific local gene network. In the last step, we constructed global cancerspecific gene network by integrating all local gene network, and calculated a score for each gene based on analysis of the global gene network. We assumed that genes in title have meaningful relations with cancer, and other genes in the body are related with the title genes. For validation, we compared with other methods for the top 20 genes inferred by each approach. Our approach found more cancer-related genes than comparable methods.

Original languageEnglish
Title of host publicationDTMBIO 2014 - Proceedings of the ACM 8th International Workshop on Data and Text Mining in Bioinformatics, co-located with CIKM 2014
PublisherAssociation for Computing Machinery, Inc
Number of pages1
ISBN (Electronic)9781450312752
DOIs
Publication statusPublished - 2014 Nov 7
Event8th ACM International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO 2014 - Shanghai, China
Duration: 2014 Nov 7 → …

Publication series

NameDTMBIO 2014 - Proceedings of the ACM 8th International Workshop on Data and Text Mining in Bioinformatics, co-located with CIKM 2014

Other

Other8th ACM International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO 2014
CountryChina
CityShanghai
Period14/11/7 → …

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications

Fingerprint Dive into the research topics of 'TILD: A strategy to identify cancer-related genes using title information in literature data'. Together they form a unique fingerprint.

  • Cite this

    Kim, J., Kim, H., Yeu, Y., Shin, M., & Park, S. (2014). TILD: A strategy to identify cancer-related genes using title information in literature data. In DTMBIO 2014 - Proceedings of the ACM 8th International Workshop on Data and Text Mining in Bioinformatics, co-located with CIKM 2014 (DTMBIO 2014 - Proceedings of the ACM 8th International Workshop on Data and Text Mining in Bioinformatics, co-located with CIKM 2014). Association for Computing Machinery, Inc. https://doi.org/10.1145/2665970.2665992