Now showing items 1-4 of 4
Automated training for algorithms that learn from genomic data
(BioMed Research International, 2015-01)
Supervised machine learning algorithms are used by life scientists for a variety of objectives. Expert-curated public gene and protein databases are major resources for gathering data to train these algorithms. While these ...
ApicoAP: The first computational model for predicting apicoplast-targeted proteins for multiple species of Apicomplexa
(PLoS ONE, 2012-05)
Most of the parasites of the phylum Apicomplexa contain a relict prokaryotic-derived plastid called the apicoplast. This organelle is important not only for the survival of the parasite, but its unique properties make it ...
ApicoAMP: The first computational model for identifying apicoplast-targeted transmembrane proteins in Apicomplexa
In this work, we develop a method for predicting apicoplast-targeted transmembrane proteins for multiple species of Apicomplexa, whereby several classifiers trained on different feature sets and based on different algorithms ...
Computational approaches for the prediction of apicoplast-targeted proteins
Motivation:The cells of eukaryotic organisms contain subunits called organelles. The apicoplast is a unique organelle found in a group of parasites, known as Apicomplexa, that are responsible for a wide range of serious ...