z-logo
open-access-imgOpen Access
Boosting gene expression clustering with system-wide biological information: a robust autoencoder approach
Author(s) -
Yuting Liang,
Randy Paffenroth,
Dmitry Korkin,
Xinyu Dai,
Hongzhu Cui,
Chong Zhou
Publication year - 2020
Publication title -
international journal of computational biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.107
H-Index - 13
eISSN - 1756-0764
pISSN - 1756-0756
DOI - 10.1504/ijcbdd.2020.10026793
Subject(s) - cluster analysis , autoencoder , artificial intelligence , computer science , expression (computer science) , gene expression , data mining , machine learning , computational biology , gene , pattern recognition (psychology) , deep learning , biology , genetics , programming language

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom