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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "networkABC" in publications use:'
type: software
license: GPL-3.0-only
title: 'networkABC: Network Reverse Engineering with Approximate Bayesian Computation'
version: 0.8-1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.networkABC
- type: url
  value: https://github.com/fbertran/networkABC/
abstract: We developed an inference tool based on approximate Bayesian computation
  to decipher network data and assess the strength of the inferred links between network's
  actors. It is a new multi-level approximate Bayesian computation (ABC) approach.
  At the first level, the method captures the global properties of the network, such
  as a scale-free structure and clustering coefficients, whereas the second level
  is targeted to capture local properties, including the probability of each couple
  of genes being linked. Up to now, Approximate Bayesian Computation (ABC) algorithms
  have been scarcely used in that setting and, due to the computational overhead,
  their application was limited to a small number of genes. On the contrary, our algorithm
  was made to cope with that issue and has low computational cost. It can be used,
  for instance, for elucidating gene regulatory network, which is an important step
  towards understanding the normal cell physiology and complex pathological phenotype.
  Reverse-engineering consists in using gene expressions over time or over different
  experimental conditions to discover the structure of the gene network in a targeted
  cellular process. The fact that gene expression data are usually noisy, highly correlated,
  and have high dimensionality explains the need for specific statistical methods
  to reverse engineer the underlying network.
authors:
- family-names: Bertrand
  given-names: Frederic
  email: frederic.bertrand@utt.fr
  orcid: https://orcid.org/0000-0002-0837-8281
- family-names: Maumy-Bertrand
  given-names: Myriam
  email: myriam.maumy@utt.fr
  orcid: https://orcid.org/0000-0002-4615-1512
preferred-citation:
  type: manual
  title: Network Reverse Engineering with Approximate Bayesian Computation
  authors:
  - family-names: Bertrand
    given-names: F.
  - family-names: Maumy-Bertrand
    given-names: M.
  publisher:
    name: manual
  year: '2022'
  notes: R package version 0.8-1
  url: https://fbertran.github.io/homepage/
repository: https://fbertran.r-universe.dev
repository-code: https://github.com/fbertran/networkABC/issues/
commit: 3cd3adb483971d67a21f533ae9a3640748039541
url: https://fbertran.github.io/networkABC/
date-released: '2022-10-18'
contact:
- family-names: Bertrand
  given-names: Frederic
  email: frederic.bertrand@utt.fr
  orcid: https://orcid.org/0000-0002-0837-8281
references:
- type: article
  title: Network Reverse Engineering with Approximate Bayesian Computation
  authors:
  - family-names: Maumy
    given-names: M.
  - family-names: Bertrand
    given-names: F.
  journal: user! 2021
  year: '2021'
  notes: Zurich
  url: https://user2021.r-project.org/participation/technical_notes/t164/technote/