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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 ...
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 ...
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 ...