TimeCycle: topology inspired method for the detection of cycling transcripts in circadian time-series data | Zendy

Elan Ness-Cohn | Zendy; Rosemary Braun | Zendy

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TimeCycle: topology inspired method for the detection of cycling transcripts in circadian time-series data

Author(s) -

Elan Ness-Cohn,

Rosemary Braun

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab476

Subject(s) - embedding , computer science , circadian rhythm , persistent homology , time series , topology (electrical circuits) , data mining , algorithm , computational biology , machine learning , artificial intelligence , biology , mathematics , neuroscience , combinatorics

The circadian rhythm drives the oscillatory expression of thousands of genes across all tissues. The recent revolution in high-throughput transcriptomics, coupled with the significant implications of the circadian clock for human health, has sparked an interest in circadian profiling studies to discover genes under circadian control.

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