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.
Previous Article in event
Employment of hyphenated approach for metabolomic fingerprinting of phenolics from Torilis leptophylla rootsPrevious Article in congress
Next Article in event
Study of microbiological laboratory techniques for the etiological diagnosis and guidance in the treatment of invasive candidiasisNext Article in congress
Prediction of RIFIN proteins with gene orientation network indices
Published: 23 January 2018 by MDPI in MOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed. congress USEDAT-03: USA-EU Data Analysis Training Prog. Work., Cambridge, UK-Bilbao, Spain-Duluth, USA, 2017
Keywords: Malaria; Plasmodium sp. proteome; Chromosome microstructure; Gene orientation; Complex Networks; Machine Learning