Ensemble multi-objective evolutionary algorithm for gene regulatory network reconstruction based on fuzzy cognitive maps

Ensemble multi-objective evolutionary algorithm for gene regulatory network reconstruction based on fuzzy cognitive maps

Many methods aim to use data, especially data about gene expression based on high throughput genomic methods, to identify complicated regulatory relationships between genes. The authors employ a simple but powerful tool, called fuzzy cognitive maps (FCMs), to accurately reconstruct gene regulatory n...

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Bibliographic Details
Main Authors: Jing Liu, Yaxiong Chi, Zongdong Liu, Shan He
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
genetics
fuzzy set theory
evolutionary computation
biology computing
genomics
learning (artificial intelligence)
optimisation
MOEA
historical data
target network
distinct optimal local information
efficient ensemble strategy
selected networks
final network
synthetic FCMs
FCM -GRN
GRNs
ensemble multiobjective evolutionary algorithm
gene regulatory network reconstruction
gene expression
genomic methods
complicated regulatory relationships
simple but powerful tool
called fuzzy cognitive maps
gene regulatory networks
automated methods
training FCMs
observed time sequence data
FCM learning problem
network structure information
EMOEA
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1059

Internet

https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1059

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