A multi-omics informatics approach for identifying molecular mechanisms and biomarkers in clinical patients with endometriosis

Sadia Akter, Gil Wilshire, J. Wade Davis, John Bromfield, Sarah Crowder, Trupti Joshi, Katherine Pelch, Danny J. Schust, Angela Meng, Bret Barrier, Susan C. Nagel

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

1 Scopus citations

Abstract

Endometriosis is a complex gynecological disorder. The diagnostic process of endometriosis involves an invasive procedure thus delaying the diagnosis for about 10 years on average. Both DNA-methylation data and RNA-seq data has the potential to uncover molecular mechanisms of diseases. The objective of this project is to identify diagnostic molecular mechanisms of endometriosis using a multi-omics approach that will lead to noninvasive diagnostic procedure.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2221-2223
Number of pages3
ISBN (Electronic)9781509030491
DOIs
StatePublished - 15 Dec 2017
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: 13 Nov 201716 Nov 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Conference

Conference2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
CountryUnited States
CityKansas City
Period13/11/1716/11/17

Keywords

  • endometriosis
  • methylation
  • multi-omics
  • RNA-Seq

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  • Cite this

    Akter, S., Wilshire, G., Davis, J. W., Bromfield, J., Crowder, S., Joshi, T., Pelch, K., Schust, D. J., Meng, A., Barrier, B., & Nagel, S. C. (2017). A multi-omics informatics approach for identifying molecular mechanisms and biomarkers in clinical patients with endometriosis. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Eds.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pp. 2221-2223). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8218003