Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research

Terry Camerlengo; Hatice Gulcin Ozer; Pearlly Yan; Jeffrey Parvin; Tim Huang; Kun Huang; Mingxiang Teng; Lang Li; Yunlong Liu; Francisco Perez; Tahsin Kurc

doi:10.1109/BIBM.2009.84

Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research

Terry Camerlengo
, Hatice Gulcin Ozer
, Pearlly Yan
, Jeffrey Parvin
, Tim Huang
, Kun Huang
, Mingxiang Teng
, Lang Li
, Yunlong Liu
, Francisco Perez
, Tahsin Kurc

Biomedical Informatics

Ohio State University
Indiana University-Purdue University Indianapolis
Wistar Institute

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

Abstract

Enabling data analysis in large data depositories for high throughput experimental data such as gene microarrays and ChIP-seq is challenging. In this paper, we discuss three methods for integrating QUEST, a data depository for epigenetic experiments, with a web-based data analysis platform GenePattern. These methods are universal and can serve as an exemplary implementation resolving the dilemma facing many similar database systems in integrating data analysis tools.

Original language	English
Title of host publication	2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
Pages	392-395
Number of pages	4
DOIs	https://doi.org/10.1109/BIBM.2009.84
State	Published - 2009
Event	2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 - Washington, D.C., United States Duration: Nov 1 2009 → Nov 4 2009

Publication series

Name	2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009

Conference

Conference	2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
Country/Territory	United States
City	Washington, D.C.
Period	11/1/09 → 11/4/09

Keywords

ChIP-seq
GenePattern
High-throughput database

Access to Document

10.1109/BIBM.2009.84

Cite this

Camerlengo, T., Ozer, H. G., Yan, P., Parvin, J., Huang, T., Huang, K., Teng, M., Li, L., Liu, Y., Perez, F., & Kurc, T. (2009). Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research. In 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 (pp. 392-395). Article 5341750 (2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009). https://doi.org/10.1109/BIBM.2009.84

Camerlengo, Terry ; Ozer, Hatice Gulcin ; Yan, Pearlly et al. / Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research. 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009. 2009. pp. 392-395 (2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009).

@inproceedings{bf93ef2fc91341d69fd37889bd9fdb05,

title = "Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research",

abstract = "Enabling data analysis in large data depositories for high throughput experimental data such as gene microarrays and ChIP-seq is challenging. In this paper, we discuss three methods for integrating QUEST, a data depository for epigenetic experiments, with a web-based data analysis platform GenePattern. These methods are universal and can serve as an exemplary implementation resolving the dilemma facing many similar database systems in integrating data analysis tools.",

keywords = "ChIP-seq, GenePattern, High-throughput database",

author = "Terry Camerlengo and Ozer, \{Hatice Gulcin\} and Pearlly Yan and Jeffrey Parvin and Tim Huang and Kun Huang and Mingxiang Teng and Lang Li and Yunlong Liu and Francisco Perez and Tahsin Kurc",

year = "2009",

doi = "10.1109/BIBM.2009.84",

language = "English",

isbn = "9780769538853",

series = "2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009",

pages = "392--395",

booktitle = "2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009",

note = "2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 ; Conference date: 01-11-2009 Through 04-11-2009",

}

Camerlengo, T, Ozer, HG, Yan, P, Parvin, J, Huang, T, Huang, K, Teng, M, Li, L, Liu, Y, Perez, F & Kurc, T 2009, Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research. in 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009., 5341750, 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009, pp. 392-395, 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009, Washington, D.C., United States, 11/1/09. https://doi.org/10.1109/BIBM.2009.84

Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research. / Camerlengo, Terry; Ozer, Hatice Gulcin; Yan, Pearlly et al.
2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009. 2009. p. 392-395 5341750 (2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009).

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

TY - GEN

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AU - Camerlengo, Terry

AU - Ozer, Hatice Gulcin

AU - Yan, Pearlly

AU - Parvin, Jeffrey

AU - Huang, Tim

AU - Huang, Kun

AU - Teng, Mingxiang

AU - Li, Lang

AU - Liu, Yunlong

AU - Perez, Francisco

AU - Kurc, Tahsin

PY - 2009

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N2 - Enabling data analysis in large data depositories for high throughput experimental data such as gene microarrays and ChIP-seq is challenging. In this paper, we discuss three methods for integrating QUEST, a data depository for epigenetic experiments, with a web-based data analysis platform GenePattern. These methods are universal and can serve as an exemplary implementation resolving the dilemma facing many similar database systems in integrating data analysis tools.

AB - Enabling data analysis in large data depositories for high throughput experimental data such as gene microarrays and ChIP-seq is challenging. In this paper, we discuss three methods for integrating QUEST, a data depository for epigenetic experiments, with a web-based data analysis platform GenePattern. These methods are universal and can serve as an exemplary implementation resolving the dilemma facing many similar database systems in integrating data analysis tools.

KW - ChIP-seq

KW - GenePattern

KW - High-throughput database

UR - https://www.scopus.com/pages/publications/74549159655

U2 - 10.1109/BIBM.2009.84

DO - 10.1109/BIBM.2009.84

M3 - Conference contribution

AN - SCOPUS:74549159655

SN - 9780769538853

T3 - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009

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BT - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009

T2 - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009

Y2 - 1 November 2009 through 4 November 2009

ER -

Camerlengo T, Ozer HG, Yan P, Parvin J, Huang T, Huang K et al. Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research. In 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009. 2009. p. 392-395. 5341750. (2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009). doi: 10.1109/BIBM.2009.84

Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research

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Keywords

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