LIF: A method to infer disease-gene relationships using literature data and impact factor

Jeongwoo Kim, Chunghun Kim, Jinyoung Lee, Sanghyun Park, Heechul Kang

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

Abstract

Biological relationships are important in discovering the causes of disease. Therefore, a number of studies have been conducted to extract information regarding the relationships between biological entities. However, given the large number of journals and amount of literature that is available, it is difficult to assess data regarding biological relationships. In this study, we present a method called LIF, which infers disease-gene relationships using literature data and impact factor. Since the impact factor is influenced by a large number of researchers, we considered that the impact factor can be used as a measure to evaluate relationships that are extracted from literature data. To implement the LIF method, we extracted genes from disease-specific literature data. We then calculated the weight of the genes based on the impact factor of the literature in which the genes were described. For validation, we investigated the top N inferred genes for lung cancer, using an answer set. The answer set comprised several databases that contained information on disease- gene relationships. We demonstrated that the LIF is a useful method to infer disease-gene relationships compared with existing methods.

Original languageEnglish
Title of host publication32nd Annual ACM Symposium on Applied Computing, SAC 2017
PublisherAssociation for Computing Machinery
Pages3-10
Number of pages8
ISBN (Electronic)9781450344869
DOIs
Publication statusPublished - 2017 Apr 3
Event32nd Annual ACM Symposium on Applied Computing, SAC 2017 - Marrakesh, Morocco
Duration: 2017 Apr 42017 Apr 6

Publication series

NameProceedings of the ACM Symposium on Applied Computing
VolumePart F128005

Other

Other32nd Annual ACM Symposium on Applied Computing, SAC 2017
CountryMorocco
CityMarrakesh
Period17/4/417/4/6

All Science Journal Classification (ASJC) codes

  • Software

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  • Cite this

    Kim, J., Kim, C., Lee, J., Park, S., & Kang, H. (2017). LIF: A method to infer disease-gene relationships using literature data and impact factor. In 32nd Annual ACM Symposium on Applied Computing, SAC 2017 (pp. 3-10). (Proceedings of the ACM Symposium on Applied Computing; Vol. Part F128005). Association for Computing Machinery. https://doi.org/10.1145/3019612.3019613