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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: HP2NET - High Performance Phylogenetic Network
message: 'If you use this framework, please cite it as below'
type: software
authors:
  - given-names: Rafael
    family-names: Terra
    email: rafaelst@posgrad.lncc.br
    affiliation: National Laboratory for Scientific Computing
    orcid: 'https://orcid.org/0000-0002-3811-4527'
  - given-names: Diego
    family-names: Carvalho
    orcid: 'https://orcid.org/0000-0003-1592-6327'
    affiliation: Federal Center for Technological Education Celso Suckow da Fonseca
  - given-names: Carla
    family-names: Osthoff
    email: osthoff@lncc.br
    affiliation: National Laboratory for Scientific Computing
    orcid: 'https://orcid.org/0000-0002-4694-7182'
  - given-names: Kary
    family-names: Ocaña
    email: karyann@lncc.br
    affiliation: National Laboratory for Scientific Computing
    orcid: 'https://orcid.org/0000-0002-2151-7418'
identifiers:
  - type: doi
    value: 10.48546/workflowhub.workflow.703.1
repository-code: 'https://github.com/rafaelstjf/HP2NET'
abstract: >-
  Phylogeny refers to the evolutionary history and
  relationship between biological lineages related by common
  descent. Reticulate evolution refers to the origination of
  lineages through the complete or partial merging of
  ancestor lineages. Networks may be used to represent
  lineage independence events in non-treelike phylogenetic
  processes.

  The methodology for reconstructing networks is still in
  development. Here we explore two methods for
  reconstructing rooted explicit phylogenetic networks,
  PhyloNetworks and Phylonet, which employ computationally
  expensive and time consuming algorithms. The construction
  of phylogenetic networks follows a coordinated processing
  flow of data sets analyzed and processed by the
  coordinated execution of a set of different programs,
  packages, libraries or pipelines, called workflow
  activities.

  In view of the complexity in modeling network experiments,
  the present work introduces a workflow for phylogenetic
  network analyses coupled to be executed in
  High-Performance Computing (HPC) environments. The
  workflow aims to integrate well-established software,
  pipelines and scripts, implementing a challenging task
  since these tools do not consistently profit from the HPC
  environment, leading to an increase in the expected
  makespan and idle computing resources.
keywords:
  - Scientific Workflows
  - Phylogenetic Networks
  - High-Performance Computing
  - Parsl
license: MIT