Evidence map›Paper›PMID 28130227›Full record

ArticleBioinformatics (Oxford, England)2017

Unrealistic phylogenetic trees may improve phylogenetic footprinting.

Martin Nettling, Hendrik Treutler, Jesus Cerquides, Ivo Grosse

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Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Martin NettlingInstitute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.
Hendrik TreutlerDepartment of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Halle, Germany.
Jesus CerquidesInstitut d'Investigació en Intel ligència Artificial, IIIA-CSIC, Campus UAB, Cerdanyola, Spain.
Ivo GrosseInstitute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThe computational investigation of DNA binding motifs from binding sites is one of the classic tasks in bioinformatics and a prerequisite for understanding gene regulation as a whole. Due to the development of sequencing technologies and the increasing number of available genomes, approaches based on phylogenetic footprinting become increasingly attractive. Phylogenetic footprinting requires phylogenetic trees with attached substitution probabilities for quantifying the evolution of binding sites, but these trees and substitution probabilities are typically not known and cannot be estimated easily.

resultsHere, we investigate the influence of phylogenetic trees with different substitution probabilities on the classification performance of phylogenetic footprinting using synthetic and real data. For synthetic data we find that the classification performance is highest when the substitution probability used for phylogenetic footprinting is similar to that used for data generation. For real data, however, we typically find that the classification performance of phylogenetic footprinting surprisingly increases with increasing substitution probabilities and is often highest for unrealistically high substitution probabilities close to one. This finding suggests that choosing realistic model assumptions might not always yield optimal predictions in general and that choosing unrealistically high substitution probabilities close to one might actually improve the classification performance of phylogenetic footprinting. AVAILABILITY AND IMPLEMENTATION: The proposed PF is implemented in JAVA and can be downloaded from https://github.com/mgledi/PhyFoo. CONTACT: : martin.nettling@informatik.uni-halle.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Gene Regulatory NetworksPhylogenySoftwareAnimalsBinding SitesComputational BiologyDNA-Binding ProteinsHumansSequence Analysis, DNASequence Analysis, ProteinDNA-Binding Proteins

Identifiers

PMID28130227
PMCPMC5447242

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.