Gene regulatory network inference using mixed-norms regularized multivariate 
model with covariance selection

Mbebi, A. J.; Nikoloski, Z.

doi:10.1371/journal.pcbi.1010832

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Gene regulatory network inference using mixed-norms regularized multivariate model with covariance selection

Mbebi, A. J., & Nikoloski, Z. (2023). Gene regulatory network inference using mixed-norms regularized multivariate model with covariance selection. PLoS Computational Biology, 19(7): e1010832. doi:10.1371/journal.pcbi.1010832.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-9E42-7 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-9E44-5

Genre: Journal Article

Alternative Title : PLOS COMPUTATIONAL BIOLOGY

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Creators:
Mbebi, A. J.¹, Author
Nikoloski, Z.¹, Author

Affiliations:
1Mathematical Modelling and Systems Biology - Nikoloski, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753310

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Language(s): eng - English

Dates: Published Online: 2023-07-31Date issued: 2023-07

Publication Status: Issued

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Identifiers: DOI: 10.1371/journal.pcbi.1010832

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Title: PLoS Computational Biology

Source Genre: Journal

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Publ. Info: San Francisco, CA : Public Library of Science

Pages: - Volume / Issue: 19 (7) Sequence Number: e1010832 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1