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

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

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 (US)
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
Externally published	Yes
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

Other

Other	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

ASJC Scopus subject areas

Software
Artificial Intelligence
Health Informatics
Biomedical Engineering

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10.1109/BIBM.2009.84

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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

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

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

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

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).

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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.",

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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

Publication series

Other

Keywords

ASJC Scopus subject areas

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