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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 "appnn" in publications use:'
type: software
license: GPL-3.0-only
title: 'appnn: Amyloid Propensity Prediction Neural Network'
version: 1.0-1
identifiers:
- type: doi
  value: 10.32614/CRAN.package.appnn
abstract: Amyloid propensity prediction neural network (APPNN) is an amyloidogenicity
  propensity predictor based on a machine learning approach through recursive feature
  selection and feed-forward neural networks, taking advantage of newly published
  sequences with experimental, in vitro, evidence of amyloid formation.
authors:
- family-names: Família
  given-names: Carlos
  email: carlosfamilia@gmail.com
- family-names: Dennison
  given-names: Sarah R.
- family-names: Quintas
  given-names: Alexandre
- family-names: Phoenix
  given-names: David A.
preferred-citation:
  type: manual
  title: 'appnn: Amyloid Propensity Prediction Neural Network'
  authors:
  - family-names: Família
    given-names: Carlos
    email: carlosfamilia@gmail.com
  - family-names: Dennison
    given-names: Sarah R.
  - family-names: Quintas
    given-names: Alexandre
  - family-names: Phoenix
    given-names: David A.
  year: '2024'
  notes: R package version 1.0-1
  url: https://CRAN.R-project.org/package=appnn
repository: https://CRAN.R-project.org/package=appnn
date-released: '2024-12-05'
contact:
- family-names: Família
  given-names: Carlos
  email: carlosfamilia@gmail.com
references:
- type: article
  title: Prediction of Peptide and Protein Propensity for Amyloid Formation
  authors:
  - family-names: Família
    given-names: Carlos
  - family-names: Dennison
    given-names: Sarah R.
  - family-names: Quintas
    given-names: Alexandre
  - family-names: Phoenix
    given-names: David A.
  journal: PLoS ONE
  doi: 10.1371/journal.pone.0134679
  pmcid: PMC4524629
  year: '2015'
  issue: '8'
  volume: '10'
  month: '8'
  start: e0134679