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

Sadia Akter, Gil Wilshire, J. Wade Davis, John J. Bromfield, Sarah Crowder, Trupti Joshi, Katherine E. Pelch, Danny J. Schust, Angela Meng, Bret Barrier, Susan C. Nagel
In: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2017 · pp. 2221–2223 · doi:10.1109/bibm.2017.8218003 · W2771985228
OA: closed CC0 ⤵ 4 in-corpus citations
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This study used DNA methylation and RNA sequencing data to identify molecular mechanisms and potential biomarkers for noninvasive endometriosis diagnosis.

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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.

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Condition tags

endometriosis

Citation neighborhood (2-hop)

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. Outer rings show 2-hop neighbours — papers reached through the immediate citers/citees. [ collapse to 1-hop ]

References (10)

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