Data-Driven and Knowledge-Based Algorithms for Gene Network Reconstruction on High-Dimensional Data

Previous efforts in gene network reconstruction have mainly focused on data-driven modeling, with little attention paid to knowledge-based approaches. Leveraging prior knowledge, however, is a promising paradigm that has been gaining momentum in network reconstruction and computational biology resea...

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Vydáno v:	IEEE/ACM transactions on computational biology and bioinformatics Ročník 19; číslo 3; s. 1545 - 1557
Hlavní autoři:	Abbaszadeh, Omid, Azarpeyvand, Ali, Khanteymoori, Alireza, Bahari, Abbas
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.05.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Atrophy Bayes methods Bayes Theorem Bayesian analysis Computational Biology - methods Computer applications Covariance matrices Covariance matrix covariance matrix estimation Eigenvalues and eigenfunctions Gaussian graphical model Gene expression Gene network reconstruction Gene Regulatory Networks - genetics Graphical models high-dimensional data Humans Knowledge based systems knowledge-base learning Normal Distribution Reconstruction shrinkage estimator Sparse matrices
ISSN:	1545-5963, 1557-9964, 1557-9964
On-line přístup:	Získat plný text
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