Disease candidate gene identification and gene regulatory network building through medical literature mining

Yong Wang; Chenyang Jiang; Jinbiao Cheng; Xiaoqun Wang

doi:10.1007/978-3-319-38771-0_44

Disease candidate gene identification and gene regulatory network building through medical literature mining

Yong Wang^*, Chenyang Jiang, Jinbiao Cheng, Xiaoqun Wang

^*Corresponding author for this work

School of Computer Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Finding key genes associated with diseases is an essential problem of disease diagnosis and treatment, and drug design. Bioinformatics takes advantage of computer technology to analyze biomedical data to help finding the information about these genes. Biomedical literatures, which consists of original experimental data and results, are attracting more attention from bio-informatics researchers because literature mining technology can extract knowledge more efficiently. This paper designs an algorithm to estimate the association degree between genes according to their co-citations in biomedical literatures from PubMed database, and to further predict the causative genes associated with a disease. The paper also uses hierarchical clustering algorithm to build a specific genes regulation network. Experiments on uterine cancer shows that the proposed algorithm can identify pathogenic genes of uterine cancer accurately and rapidly.

Original language	English
Title of host publication	Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015
Editors	Lakhmi C. Jain, Xiangmo Zhao, Valentina Emilia Balas
Publisher	Springer Verlag
Pages	453-461
Number of pages	9
ISBN (Print)	9783319387697
DOIs	https://doi.org/10.1007/978-3-319-38771-0_44
Publication status	Published - 2017
Event	International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015 - Xi’an, China Duration: 12 Dec 2015 → 13 Dec 2015

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	455
ISSN (Print)	2194-5357

Conference

Conference	International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015
Country/Territory	China
City	Xi’an
Period	12/12/15 → 13/12/15

Keywords

Co-citation
Gene regulatory network
Hierarchical clustering
Literature mining
Pathogenic gene

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-38771-0_44

Cite this

Wang, Y., Jiang, C., Cheng, J., & Wang, X. (2017). Disease candidate gene identification and gene regulatory network building through medical literature mining. In L. C. Jain, X. Zhao, & V. E. Balas (Eds.), Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015 (pp. 453-461). (Advances in Intelligent Systems and Computing; Vol. 455). Springer Verlag. https://doi.org/10.1007/978-3-319-38771-0_44

Wang, Yong ; Jiang, Chenyang ; Cheng, Jinbiao et al. / Disease candidate gene identification and gene regulatory network building through medical literature mining. Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015. editor / Lakhmi C. Jain ; Xiangmo Zhao ; Valentina Emilia Balas. Springer Verlag, 2017. pp. 453-461 (Advances in Intelligent Systems and Computing).

@inproceedings{5e6ba9728a5a43b3a666ca095dc17769,

title = "Disease candidate gene identification and gene regulatory network building through medical literature mining",

abstract = "Finding key genes associated with diseases is an essential problem of disease diagnosis and treatment, and drug design. Bioinformatics takes advantage of computer technology to analyze biomedical data to help finding the information about these genes. Biomedical literatures, which consists of original experimental data and results, are attracting more attention from bio-informatics researchers because literature mining technology can extract knowledge more efficiently. This paper designs an algorithm to estimate the association degree between genes according to their co-citations in biomedical literatures from PubMed database, and to further predict the causative genes associated with a disease. The paper also uses hierarchical clustering algorithm to build a specific genes regulation network. Experiments on uterine cancer shows that the proposed algorithm can identify pathogenic genes of uterine cancer accurately and rapidly.",

keywords = "Co-citation, Gene regulatory network, Hierarchical clustering, Literature mining, Pathogenic gene",

author = "Yong Wang and Chenyang Jiang and Jinbiao Cheng and Xiaoqun Wang",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2017.; International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015 ; Conference date: 12-12-2015 Through 13-12-2015",

year = "2017",

doi = "10.1007/978-3-319-38771-0_44",

language = "English",

isbn = "9783319387697",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "453--461",

editor = "Jain, {Lakhmi C.} and Xiangmo Zhao and Balas, {Valentina Emilia}",

booktitle = "Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015",

address = "Germany",

}

Wang, Y, Jiang, C, Cheng, J & Wang, X 2017, Disease candidate gene identification and gene regulatory network building through medical literature mining. in LC Jain, X Zhao & VE Balas (eds), Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015. Advances in Intelligent Systems and Computing, vol. 455, Springer Verlag, pp. 453-461, International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015, Xi’an, China, 12/12/15. https://doi.org/10.1007/978-3-319-38771-0_44

Disease candidate gene identification and gene regulatory network building through medical literature mining. / Wang, Yong; Jiang, Chenyang; Cheng, Jinbiao et al.
Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015. ed. / Lakhmi C. Jain; Xiangmo Zhao; Valentina Emilia Balas. Springer Verlag, 2017. p. 453-461 (Advances in Intelligent Systems and Computing; Vol. 455).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Disease candidate gene identification and gene regulatory network building through medical literature mining

AU - Wang, Yong

AU - Jiang, Chenyang

AU - Cheng, Jinbiao

AU - Wang, Xiaoqun

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2017.

PY - 2017

Y1 - 2017

N2 - Finding key genes associated with diseases is an essential problem of disease diagnosis and treatment, and drug design. Bioinformatics takes advantage of computer technology to analyze biomedical data to help finding the information about these genes. Biomedical literatures, which consists of original experimental data and results, are attracting more attention from bio-informatics researchers because literature mining technology can extract knowledge more efficiently. This paper designs an algorithm to estimate the association degree between genes according to their co-citations in biomedical literatures from PubMed database, and to further predict the causative genes associated with a disease. The paper also uses hierarchical clustering algorithm to build a specific genes regulation network. Experiments on uterine cancer shows that the proposed algorithm can identify pathogenic genes of uterine cancer accurately and rapidly.

AB - Finding key genes associated with diseases is an essential problem of disease diagnosis and treatment, and drug design. Bioinformatics takes advantage of computer technology to analyze biomedical data to help finding the information about these genes. Biomedical literatures, which consists of original experimental data and results, are attracting more attention from bio-informatics researchers because literature mining technology can extract knowledge more efficiently. This paper designs an algorithm to estimate the association degree between genes according to their co-citations in biomedical literatures from PubMed database, and to further predict the causative genes associated with a disease. The paper also uses hierarchical clustering algorithm to build a specific genes regulation network. Experiments on uterine cancer shows that the proposed algorithm can identify pathogenic genes of uterine cancer accurately and rapidly.

KW - Co-citation

KW - Gene regulatory network

KW - Hierarchical clustering

KW - Literature mining

KW - Pathogenic gene

UR - http://www.scopus.com/inward/record.url?scp=84996928521&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-38771-0_44

DO - 10.1007/978-3-319-38771-0_44

M3 - Conference contribution

AN - SCOPUS:84996928521

SN - 9783319387697

T3 - Advances in Intelligent Systems and Computing

SP - 453

EP - 461

BT - Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015

A2 - Jain, Lakhmi C.

A2 - Zhao, Xiangmo

A2 - Balas, Valentina Emilia

PB - Springer Verlag

T2 - International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015

Y2 - 12 December 2015 through 13 December 2015

ER -

Wang Y, Jiang C, Cheng J, Wang X. Disease candidate gene identification and gene regulatory network building through medical literature mining. In Jain LC, Zhao X, Balas VE, editors, Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015. Springer Verlag. 2017. p. 453-461. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-38771-0_44

Disease candidate gene identification and gene regulatory network building through medical literature mining

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this