6533b824fe1ef96bd1280255

RESEARCH PRODUCT

A multi-layer method to study genome-scale positions of nucleosomes

Luca PinelloDavide CoronaGuo-cheng YuanGiosuè Lo BoscoVito Di Gesù

subject

Feature extractionNucleosome positioningGenomicsSaccharomyces cerevisiaeComputational biologyHidden Markov Modelchemistry.chemical_compoundSettore BIO/10 - BiochimicaNucleosome positioning Hidden Markov Model Classification Multi-layer methodGeneticsHumansNucleosomeMulti-layer methodHidden Markov modelBase PairingMulti layerOligonucleotide Array Sequence AnalysisGeneticsBase SequenceSettore INF/01 - InformaticabiologyGenome HumanClassificationMarkov ChainsNucleosomesChromatinHistonechemistrybiology.proteinDNA

description

AbstractThe basic unit of eukaryotic chromatin is the nucleosome, consisting of about 150 bp of DNA wrapped around a protein core made of histone proteins. Nucleosomes position is modulated in vivo to regulate fundamental nuclear processes. To measure nucleosome positions on a genomic scale both theoretical and experimental approaches have been recently reported. We have developed a new method, Multi-Layer Model (MLM), for the analysis of nucleosome position data obtained with microarray-based approach. The MLM is a feature extraction method in which the input data is processed by a classifier to distinguish between several kinds of patterns. We applied our method to simulated-synthetic and experimental nucleosome position data and found that besides a high nucleosome recognition and a strong agreement with standard statistical methods, the MLM can identify distinct classes of nucleosomes, making it an important tool for the genome wide analysis of nucleosome position and function. In conclusion, the MLM allows a better representation of nucleosome position data and a significant reduction in computational time.

yearjournalcountryeditionlanguage
2009-02-01Genomics
https://doi.org/10.1016/j.ygeno.2008.09.012