Analysis of Half a Billion Datapoints Across Ten Machine-Learning Algorithms Identifies Key Elements Associated With Insulin Transcription in Human Pancreatic Islet Cells

Analysis of Half a Billion Datapoints Across Ten Machine-Learning Algorithms Identifies Key Elements Associated With Insulin Transcription in Human Pancreatic Islet Cells

Machine learning (ML)-workflows enable unprejudiced/robust evaluation of complex datasets. Here, we analyzed over 490,000,000 data points to compare 10 different ML-workflows in a large (N=11,652) training dataset of human pancreatic single-cell (sc-)transcriptomes to identify genes associated with...

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Bibliographic Details
Main Authors: Wilson K. M. Wong, Vinod Thorat, Mugdha V. Joglekar, Charlotte X. Dong, Hugo Lee, Yi Vee Chew, Adwait Bhave, Wayne J. Hawthorne, Feyza Engin, Aniruddha Pant, Louise T. Dalgaard, Sharda Bapat, Anandwardhan A. Hardikar
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Endocrinology
Subjects:
machine-learning (ML) algorithms
insulin
diabetes
beta-cell
single-cell RNA-sequencing (scRNAseq)
human islet
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2022.853863/full

Internet

https://www.frontiersin.org/articles/10.3389/fendo.2022.853863/full

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