title: Novel Gene Discovery in the Human Malaria Parasite using Nucleosome Positioning Data.
abstract: Recent genome-wide studies on nucleosome positioning in model organisms have shown strong evidence that nucleosome landscapes in the proximity of protein-coding genes exhibit regular characteristic patterns. Here, we propose a computational framework to discover novel genes in the human malaria parasite genomeP. falciparumusing nucleosome positioning inferred from MAINE-seq data. We rely on a classifier trained on the nucleosome landscape profiles of experimentally verified genes, and then used to discover new genes (without considering the primary DNA sequence). Cross-validation experiments show that our classifier is very accurate. About two thirds of the locations reported by the classifier match experimentally determined expressed sequence tags in GenBank, for which no gene has been annotated in the human malaria parasite.
authors: Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.
authors: N
authors: N
authors: Pokhriyal
authors: Department of Cell Biology and Neuroscience, University of California, Riverside, CA 92521, USA.
authors: N
authors: N
authors: Ponts
authors: Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.
authors: E Y
authors: EY
authors: Harris
authors: Department of Cell Biology and Neuroscience, University of California, Riverside, CA 92521, USA.
authors: K G
authors: KG
authors: Le Roch
authors: Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.
authors: S
authors: S
authors: Lonardi