Prediction of single-cell gene expression for transcription factor analysis | Zendy

Fatemeh Behjati Ardakani | Zendy; Kathrin Kattler | Zendy; Tobias Heinen | Zendy; Florian Schmidt | Zendy; David Feuerborn | Zendy; Gilles Gasparoni | Zendy; Konstantin Lepikhov | Zendy; Patrick Nell | Zendy; Jan G. Hengstler | Zendy; Jörn Walter | Zendy; Marcel H. Schulz | Zendy

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Prediction of single-cell gene expression for transcription factor analysis

Author(s) -

Fatemeh Behjati Ardakani,

Kathrin Kattler,

Tobias Heinen,

Florian Schmidt,

David Feuerborn,

Gilles Gasparoni,

Konstantin Lepikhov,

Patrick Nell,

Jan G. Hengstler,

Jörn Walter,

Marcel H. Schulz

Publication year - 2020

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giaa113

Subject(s) - computational biology , transcription factor , cell type , gene expression , gene , computer science , workflow , cell , biology , regulation of gene expression , genetics , database

Single-cell RNA sequencing is a powerful technology to discover new cell types and study biological processes in complex biological samples. A current challenge is to predict transcription factor (TF) regulation from single-cell RNA data.

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