A Preliminary Comparison of P-Tool Consistency

  • Javier Murillo
  • , Flavio Spetale
  • , Elizabeth Tapia
  • , Flavia Krsticevic
  • , Olivier Cailloux
  • , Serge Guillaume
  • , Gustavo Vazquez
  • , Tamara Fernandez
  • , Sebastien Destercke
  • , Sergio Ponce
  • , Pilar Bulacio

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Many Bioinformatics tools, known as p-tools, have been developed to predict the effect of single nucleotide polymorphisms (SNPs) on gene functionality, in an effort to reduce the need for in-vivo assays. However, the large number of p-tools available and the heterogeneity of their output make their selection and comparison difficult. To study the consistency of predictions across p-tools, here we present two indices and test them on five p-tools whose predictions are based on different types of background information. For this test, SNPs from well-known organism Drosophila melanogaster are considered.

Original languageEnglish
Title of host publication8th Latin American Conference on Biomedical Engineering and 42nd National Conference on Biomedical Engineering - Proceedings of CLAIB-CNIB 2019
EditorsCésar A. González Díaz, Christian Chapa González, Eric Laciar Leber, Hugo A. Vélez, Norma P. Puente, Dora-Luz Flores, Adriano O. Andrade, Héctor A. Galván, Fabiola Martínez, Renato García, Citlalli J. Trujillo, Aldo R. Mejía
PublisherSpringer
Pages731-735
Number of pages5
ISBN (Print)9783030306472
DOIs
StatePublished - 2020
Event8th Latin American Conference on Biomedical Engineering and the 42nd National Conference on Biomedical Engineering, CLAIB-CNIB 2019 - Cancún, Mexico
Duration: 2 Oct 20195 Oct 2019

Publication series

NameIFMBE Proceedings
Volume75
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277

Conference

Conference8th Latin American Conference on Biomedical Engineering and the 42nd National Conference on Biomedical Engineering, CLAIB-CNIB 2019
Country/TerritoryMexico
CityCancún
Period2/10/195/10/19

Keywords

  • Gene functionality
  • Missense nonsense mutation
  • SNP

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