Single cell genomics unleashed: exploring the landscape of endometriosis with machine learning, gene expression profiling, and therapeutic target discovery

Sudip Mondal
In: Data Science in the Medical Field · 2024 · pp. 377–389 · doi:10.1016/b978-0-443-24028-7.00027-1 · W4403142397
book-chapter OA: closed CC0
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⚙ AI-generated summary by claude@2026-06, 2026-06-07 ⓘ

This study utilizes single-cell genomics, machine learning, and gene expression profiling to explore endometriosis, aiming to identify potential therapeutic targets.

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Condition tags

endometriosis

Citation neighborhood

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. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (39)

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last seen: 2026-06-10T17:14:06.276822+00:00
License: CC0 · commercial use OK