The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks
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Author
Ben, Guebila, M.Wang, T.

Lopes-Ramos, C.M.
Fanfani, V.
Weighill, D.
Burkholz, R.
Schlauch, D.
Paulson, J.N.
Altenbuchinger, M.
Shutta, K.H.
Sonawane, A.R.
Lim, J.
Calderer, G.
van IJzendoorn, D.G.P.
Morgan, D.
Marin, A.
Chen, C.-Y.
Song, Q.
Saha, E.
DeMeo, D.L.
Padi, M.
Platig, J.
Kuijjer, M.L.
Glass, K.
Quackenbush, J.
Affiliation
Department of Molecular and Cellular Biology, University of ArizonaIssue Date
2023-03-09
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BioMed Central LtdCitation
Ben Guebila, M., Wang, T., Lopes-Ramos, C.M. et al. The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks. Genome Biol 24, 45 (2023). https://doi.org/10.1186/s13059-023-02877-1Journal
Genome BiologyRights
© The Author(s) 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Inference and analysis of gene regulatory networks (GRNs) require software that integrates multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is a collection of open-source methods to infer GRNs, conduct differential network analyses, estimate community structure, and explore the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages and between methods to allow better integration of these tools into analytical pipelines. We demonstrate the utility using multi-omic data from the Cancer Cell Line Encyclopedia. We will continue to expand the netZoo to incorporate additional methods. © 2023, The Author(s).Note
Open access journalISSN
1474-7596Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1186/s13059-023-02877-1
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Except where otherwise noted, this item's license is described as © The Author(s) 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License.