Discovering disease-associated drugs using web crawl data

Hyunjin Kim, Sang Hyun Park

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

2 Citations (Scopus)

Abstract

The purpose of research on biomedical literature-based discovery is to bring out new knowledge from the existing biomedical information. Beginning with Dr. Swanson's ABC model, many studies extended or applied the ABC model to find new associations between biomedical entities. While the methods applied to data have advanced, in most cases biomedical literature has been used for the text data. Assuming that web crawl data is helpful in studying literature-based discovery as well as biomedical literature which is the existing but rather limited data source, we discovered new disease-drug associations using web crawl data in addition to biomedical literature. We also analyzed how helpful the additional use of web crawl data is for biomedical literature mining. Literature-based discovery using web crawl data has its significance as a pioneering work utilizing new data.

Original languageEnglish
Title of host publication2016 Symposium on Applied Computing, SAC 2016
PublisherAssociation for Computing Machinery
Pages9-14
Number of pages6
ISBN (Electronic)9781450337397
DOIs
Publication statusPublished - 2016 Apr 4
Event31st Annual ACM Symposium on Applied Computing, SAC 2016 - Pisa, Italy
Duration: 2016 Apr 42016 Apr 8

Publication series

NameProceedings of the ACM Symposium on Applied Computing
Volume04-08-April-2016

Other

Other31st Annual ACM Symposium on Applied Computing, SAC 2016
CountryItaly
CityPisa
Period16/4/416/4/8

All Science Journal Classification (ASJC) codes

  • Software

Cite this

Kim, H., & Park, S. H. (2016). Discovering disease-associated drugs using web crawl data. In 2016 Symposium on Applied Computing, SAC 2016 (pp. 9-14). (Proceedings of the ACM Symposium on Applied Computing; Vol. 04-08-April-2016). Association for Computing Machinery. https://doi.org/10.1145/2851613.2851615
Kim, Hyunjin ; Park, Sang Hyun. / Discovering disease-associated drugs using web crawl data. 2016 Symposium on Applied Computing, SAC 2016. Association for Computing Machinery, 2016. pp. 9-14 (Proceedings of the ACM Symposium on Applied Computing).
@inproceedings{8a0ca9cec425498889376f4a3f80aa82,
title = "Discovering disease-associated drugs using web crawl data",
abstract = "The purpose of research on biomedical literature-based discovery is to bring out new knowledge from the existing biomedical information. Beginning with Dr. Swanson's ABC model, many studies extended or applied the ABC model to find new associations between biomedical entities. While the methods applied to data have advanced, in most cases biomedical literature has been used for the text data. Assuming that web crawl data is helpful in studying literature-based discovery as well as biomedical literature which is the existing but rather limited data source, we discovered new disease-drug associations using web crawl data in addition to biomedical literature. We also analyzed how helpful the additional use of web crawl data is for biomedical literature mining. Literature-based discovery using web crawl data has its significance as a pioneering work utilizing new data.",
author = "Hyunjin Kim and Park, {Sang Hyun}",
year = "2016",
month = "4",
day = "4",
doi = "10.1145/2851613.2851615",
language = "English",
series = "Proceedings of the ACM Symposium on Applied Computing",
publisher = "Association for Computing Machinery",
pages = "9--14",
booktitle = "2016 Symposium on Applied Computing, SAC 2016",

}

Kim, H & Park, SH 2016, Discovering disease-associated drugs using web crawl data. in 2016 Symposium on Applied Computing, SAC 2016. Proceedings of the ACM Symposium on Applied Computing, vol. 04-08-April-2016, Association for Computing Machinery, pp. 9-14, 31st Annual ACM Symposium on Applied Computing, SAC 2016, Pisa, Italy, 16/4/4. https://doi.org/10.1145/2851613.2851615

Discovering disease-associated drugs using web crawl data. / Kim, Hyunjin; Park, Sang Hyun.

2016 Symposium on Applied Computing, SAC 2016. Association for Computing Machinery, 2016. p. 9-14 (Proceedings of the ACM Symposium on Applied Computing; Vol. 04-08-April-2016).

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

TY - GEN

T1 - Discovering disease-associated drugs using web crawl data

AU - Kim, Hyunjin

AU - Park, Sang Hyun

PY - 2016/4/4

Y1 - 2016/4/4

N2 - The purpose of research on biomedical literature-based discovery is to bring out new knowledge from the existing biomedical information. Beginning with Dr. Swanson's ABC model, many studies extended or applied the ABC model to find new associations between biomedical entities. While the methods applied to data have advanced, in most cases biomedical literature has been used for the text data. Assuming that web crawl data is helpful in studying literature-based discovery as well as biomedical literature which is the existing but rather limited data source, we discovered new disease-drug associations using web crawl data in addition to biomedical literature. We also analyzed how helpful the additional use of web crawl data is for biomedical literature mining. Literature-based discovery using web crawl data has its significance as a pioneering work utilizing new data.

AB - The purpose of research on biomedical literature-based discovery is to bring out new knowledge from the existing biomedical information. Beginning with Dr. Swanson's ABC model, many studies extended or applied the ABC model to find new associations between biomedical entities. While the methods applied to data have advanced, in most cases biomedical literature has been used for the text data. Assuming that web crawl data is helpful in studying literature-based discovery as well as biomedical literature which is the existing but rather limited data source, we discovered new disease-drug associations using web crawl data in addition to biomedical literature. We also analyzed how helpful the additional use of web crawl data is for biomedical literature mining. Literature-based discovery using web crawl data has its significance as a pioneering work utilizing new data.

UR - http://www.scopus.com/inward/record.url?scp=84975885763&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84975885763&partnerID=8YFLogxK

U2 - 10.1145/2851613.2851615

DO - 10.1145/2851613.2851615

M3 - Conference contribution

T3 - Proceedings of the ACM Symposium on Applied Computing

SP - 9

EP - 14

BT - 2016 Symposium on Applied Computing, SAC 2016

PB - Association for Computing Machinery

ER -

Kim H, Park SH. Discovering disease-associated drugs using web crawl data. In 2016 Symposium on Applied Computing, SAC 2016. Association for Computing Machinery. 2016. p. 9-14. (Proceedings of the ACM Symposium on Applied Computing). https://doi.org/10.1145/2851613.2851615