The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks

Marouen Ben Guebila; Tian Wang; Camila M. Lopes-Ramos; Viola Fanfani; Des Weighill; Rebekka Burkholz; Daniel Schlauch; Joseph N. Paulson; Michael Altenbuchinger; Katherine H. Shutta; Abhijeet R. Sonawane; James Lim; Genis Calderer; David G.P. van IJzendoorn; Daniel Morgan; Alessandro Marin; Cho Yi Chen; Qi Song; Enakshi Saha; Dawn L. DeMeo; Megha Padi; John Platig; Marieke L. Kuijjer; Kimberly Glass; John Quackenbush

doi:10.1186/s13059-023-02877-1

The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks

Marouen Ben Guebila, Tian Wang, Camila M. Lopes-Ramos, Viola Fanfani, Des Weighill, Rebekka Burkholz, Daniel Schlauch, Joseph N. Paulson, Michael Altenbuchinger, Katherine H. Shutta, Abhijeet R. Sonawane, James Lim, Genis Calderer, David G.P. van IJzendoorn, Daniel Morgan, Alessandro Marin, Cho Yi Chen, Qi Song, Enakshi Saha, Dawn L. DeMeoMegha Padi, John Platig, Marieke L. Kuijjer, Kimberly Glass, John Quackenbush

Molecular and Cellular Biology

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Article number	45
Journal	Genome biology
Volume	24
Issue number	1
DOIs	https://doi.org/10.1186/s13059-023-02877-1
State	Published - Dec 2023

Keywords

Gene regulation
Multi-omic analysis
Network biology
Open-source software

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

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10.1186/s13059-023-02877-1

Cite this

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., ... Quackenbush, J. (2023). The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks. Genome biology, 24(1), [45]. https://doi.org/10.1186/s13059-023-02877-1

Ben Guebila, M, Wang, T, Lopes-Ramos, CM, Fanfani, V, Weighill, D, Burkholz, R, Schlauch, D, Paulson, JN, Altenbuchinger, M, Shutta, KH, Sonawane, AR, Lim, J, Calderer, G, van IJzendoorn, DGP, Morgan, D, Marin, A, Chen, CY, Song, Q, Saha, E, DeMeo, DL, Padi, M, Platig, J, Kuijjer, ML, Glass, K & Quackenbush, J 2023, 'The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks', Genome biology, vol. 24, no. 1, 45. https://doi.org/10.1186/s13059-023-02877-1

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title = "The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks",

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.",

keywords = "Gene regulation, Multi-omic analysis, Network biology, Open-source software",

author = "{Ben Guebila}, Marouen and Tian Wang and Lopes-Ramos, {Camila M.} and Viola Fanfani and Des Weighill and Rebekka Burkholz and Daniel Schlauch and Paulson, {Joseph N.} and Michael Altenbuchinger and Shutta, {Katherine H.} and Sonawane, {Abhijeet R.} and James Lim and Genis Calderer and {van IJzendoorn}, {David G.P.} and Daniel Morgan and Alessandro Marin and Chen, {Cho Yi} and Qi Song and Enakshi Saha and DeMeo, {Dawn L.} and Megha Padi and John Platig and Kuijjer, {Marieke L.} and Kimberly Glass and John Quackenbush",

note = "Funding Information: This work was supported by the National Institutes of Health through grants to KG (R01HL155749), JP (K25HL140186), DD (R01HG125975), KS (P01HL114501), and MBG, JQ, VF, CMLR, RB, and DW (R35CA220523). Furthermore MBG and JQ are supported by U24CA231846 and JQ is additionally supported by R01HG011393 and P50CA127003. CMLR and KS are supported by T32HL007427 from the National Heart, Lung, and Blood Institute (NHLBI) and CMLR is supported by the American Lung Association through grant LCD-821824. MLK and GC are supported by the Norwegian Research Council, Helse S{\o}r-{\O}st, and University of Oslo through the Centre for Molecular Medicine Norway (187615). MLK is additionally supported by grants from the Norwegian Cancer Society (214871) and the Norwegian Research Council (313932). MA is supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant no. 01ZX1912C). Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = dec,

doi = "10.1186/s13059-023-02877-1",

language = "English (US)",

volume = "24",

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TY - JOUR

T1 - The Network Zoo

T2 - a multilingual package for the inference and analysis of gene regulatory networks

AU - Ben Guebila, Marouen

AU - Wang, Tian

AU - Lopes-Ramos, Camila M.

AU - Fanfani, Viola

AU - Weighill, Des

AU - Burkholz, Rebekka

AU - Schlauch, Daniel

AU - Paulson, Joseph N.

AU - Altenbuchinger, Michael

AU - Shutta, Katherine H.

AU - Sonawane, Abhijeet R.

AU - Lim, James

AU - Calderer, Genis

AU - van IJzendoorn, David G.P.

AU - Morgan, Daniel

AU - Marin, Alessandro

AU - Chen, Cho Yi

AU - Song, Qi

AU - Saha, Enakshi

AU - DeMeo, Dawn L.

AU - Padi, Megha

AU - Platig, John

AU - Kuijjer, Marieke L.

AU - Glass, Kimberly

AU - Quackenbush, John

N1 - Funding Information: This work was supported by the National Institutes of Health through grants to KG (R01HL155749), JP (K25HL140186), DD (R01HG125975), KS (P01HL114501), and MBG, JQ, VF, CMLR, RB, and DW (R35CA220523). Furthermore MBG and JQ are supported by U24CA231846 and JQ is additionally supported by R01HG011393 and P50CA127003. CMLR and KS are supported by T32HL007427 from the National Heart, Lung, and Blood Institute (NHLBI) and CMLR is supported by the American Lung Association through grant LCD-821824. MLK and GC are supported by the Norwegian Research Council, Helse Sør-Øst, and University of Oslo through the Centre for Molecular Medicine Norway (187615). MLK is additionally supported by grants from the Norwegian Cancer Society (214871) and the Norwegian Research Council (313932). MA is supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant no. 01ZX1912C). Publisher Copyright: © 2023, The Author(s).

PY - 2023/12

Y1 - 2023/12

N2 - 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.

AB - 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.

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KW - Multi-omic analysis

KW - Network biology

KW - Open-source software

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JO - Genome Biology

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ER -

The Network Zoo: a multilingual package for the inference and analysis of gene regulatory networks

Abstract

Keywords

ASJC Scopus subject areas

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