DLCpar specifications

Information


Unique identifier OMICS_16628
Name DLCpar
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
Computer skills Advanced
Version 1.0
Stability Stable
Requirements
Numpy
Maintained Yes

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Maintainer


  • person_outline Yi-Chieh Wu <>

Publication for DLCpar

DLCpar in publication

PMCID: 4851173
PMID: 25281847
DOI: 10.1093/sysbio/syu082

[…] distances can be easily implemented as well, taking advantage of our solution to the normalization constant. an example of a promising distance would be one based on the recently developed dlcpar algorithm (), which can find the most parsimonious reconciliation scenario by considering duplications, losses, and deep coalescences at once. another option would be based on algorithms […]


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DLCpar institution(s)
Department of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA; Broad Institute, Cambridge, MA, USA
DLCpar funding source(s)
Supported by National Science Foundation CAREER award 0644282 and by a fellowship from the MIT/Whitehead/Broad Computational Genetics Training Program training grant through the National Institutes of Health.

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