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

^*此作品的通讯作者

计算机学院

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

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.

源语言	英语
主期刊名	Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015
编辑	Lakhmi C. Jain, Xiangmo Zhao, Valentina Emilia Balas
出版商	Springer Verlag
页	453-461
页数	9
ISBN（印刷版）	9783319387697
DOI	https://doi.org/10.1007/978-3-319-38771-0_44
出版状态	已出版 - 2017
活动	International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015 - Xi’an, 中国期限: 12 12月 2015 → 13 12月 2015

出版系列

姓名	Advances in Intelligent Systems and Computing
卷	455
ISSN（印刷版）	2194-5357

会议

会议	International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015
国家/地区	中国
市	Xi’an
时期	12/12/15 → 13/12/15

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

访问文件

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

其它文件与链接

链接到 Scopus 的出版物

引用此

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

Wang, Yong ; Jiang, Chenyang ; Cheng, Jinbiao 等. / 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. 编辑 / Lakhmi C. Jain ; Xiangmo Zhao ; Valentina Emilia Balas. Springer Verlag, 2017. 页码 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. 在 LC Jain, X Zhao & VE Balas (编辑), 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, 卷 455, Springer Verlag, 页码 453-461, International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015, Xi’an, 中国, 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 等.
Information Technology and Intelligent Transportation System - Volume 2, Proceedings of the International Conference on Information Technology and Intelligent Transportation Systems, ITITS 2015. 编辑 / Lakhmi C. Jain; Xiangmo Zhao; Valentina Emilia Balas. Springer Verlag, 2017. 页码 453-461 (Advances in Intelligent Systems and Computing; 卷 455).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

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. 在 Jain LC, Zhao X, Balas VE, 编辑, 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. 页码 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

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此