Home » MOL2NET-03 » Section 03: Computational Sciences, Statistics, Artificial Intelligence, Complex Networks, Machine Learning, and Big Data » Paper

[] Prediction of RIFIN proteins with gene orientation network indices

1 RNASA-IMEDIR, Computer Science Faculty, University of A Coruña, 15071, A Coruña, Spain
2 Universidad Estatal Amazónica
3 Dept. of Organic Chemistry II, University of the Basque Country UPV/EHU, 48940, Leioa, Biscay, Spain
* Author to whom correspondence should be addressed.
23 January 2018
293 views
0/5 rated ( 0 ratings )

Abstract

Gene orientation may have a direct influence on the expression of genes. In this work, we developed a Linear Discriminant Analysis (LDA) model able to predict RIFIN-like proteins of out of 5365 of Plasmodium falciparum proteins with Sensitivity and Specificity 70-80% in training and external validation series.

Keywords

Malaria; Plasmodium sp. proteome; Chromosome microstructure; Gene orientation; Complex Networks; Machine Learning

Cite this article as

Quevedo, V.; Ortega-Tenezaca, B.; Vargas-Burgos, J.; Pazos-Sierra, A.; González-Díaz, H. Prediction of RIFIN proteins with gene orientation network indices. In Proceedings of the MOL2NET, International Conference on Multidisciplinary Sciences, 15 January–15 December 2017; Sciforum Electronic Conference Series, Vol. 3, 2017 ; doi:10.3390/mol2net-03-05124

Presentation

Comments on Prediction of RIFIN proteins with gene orientation network indices