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RANGER-DTL 2.0: rigorous reconstruction of gene-family evolution by duplication, transfer and loss.
Bansal, Mukul S; Kellis, Manolis; Kordi, Misagh; Kundu, Soumya.
Afiliação
  • Bansal MS; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.
  • Kellis M; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Kordi M; Broad Institute, Cambridge, MA, USA.
  • Kundu S; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.
Bioinformatics ; 34(18): 3214-3216, 2018 09 15.
Article em En | MEDLINE | ID: mdl-29688310
ABSTRACT

Summary:

RANGER-DTL 2.0 is a software program for inferring gene family evolution using Duplication-Transfer-Loss reconciliation. This new software is highly scalable and easy to use, and offers many new features not currently available in any other reconciliation program. RANGER-DTL 2.0 has a particular focus on reconciliation accuracy and can account for many sources of reconciliation uncertainty including uncertain gene tree rooting, gene tree topological uncertainty, multiple optimal reconciliations and alternative event cost assignments. RANGER-DTL 2.0 is open-source and written in C++ and Python. Availability and implementation Pre-compiled executables, source code (open-source under GNU GPL) and a detailed manual are freely available from http//compbio.engr.uconn.edu/software/RANGER-DTL/. Supplementary information Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Evolução Molecular / Biologia Computacional / Duplicação Gênica Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Evolução Molecular / Biologia Computacional / Duplicação Gênica Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos