ArticleBMC bioinformatics2010
Predicting nucleosome positioning using a duration Hidden Markov Model.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.
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82 citing papers in PubMed, 160 citations in OpenAlex.
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- Learning to quantify uncertainty in off-target activity for CRISPR guide RNAs.Nucleic acids research · 2024Article
- The importance of DNA sequence for nucleosome positioning in transcriptional regulation.Life science alliance · 2024Article
- Evolutionary Dynamics of Chromatin Structure and Duplicate Gene Expression in Diploid and Allopolyploid Cotton.Molecular biology and evolution · 2024Article
- Enhancing Cell Line Stability by CRISPR/Cas9-Mediated Site-Specific Integration Based on Histone Modifications.Methods in molecular biology (Clifton, N.J.) · 2024Article
- piCRISPR: Physically informed deep learning models for CRISPR/Cas9 off-target cleavage prediction.Artificial intelligence in the life sciences · 2023Article
- Microhomology-mediated circular DNA formation from oligonucleosomal fragments during spermatogenesis.eLife · 2023Article
- Natural promoters and promoter engineering strategies for metabolic regulation in Saccharomyces cerevisiae.Journal of industrial microbiology & biotechnology · 2023Review
- Dual-plasmid interactions stimulate the accumulation of valencene inBiotechnology notes (Amsterdam, Netherlands) · 2023Article
- Comprehensive computational analysis of epigenetic descriptors affecting CRISPR-Cas9 off-target activity.BMC genomics · 2022Article
22 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe nucleosome is the fundamental packing unit of DNAs in eukaryotic cells. Its detailed positioning on the genome is closely related to chromosome functions. Increasing evidence has shown that genomic DNA sequence itself is highly predictive of nucleosome positioning genome-wide. Therefore a fast software tool for predicting nucleosome positioning can help understanding how a genome's nucleosome organization may facilitate genome function.
resultsWe present a duration Hidden Markov model for nucleosome positioning prediction by explicitly modeling the linker DNA length. The nucleosome and linker models trained from yeast data are re-scaled when making predictions for other species to adjust for differences in base composition. A software tool named NuPoP is developed in three formats for free download.
conclusionsSimulation studies show that modeling the linker length distribution and utilizing a base composition re-scaling method both improve the prediction of nucleosome positioning regarding sensitivity and false discovery rate. NuPoP provides a user-friendly software tool for predicting the nucleosome occupancy and the most probable nucleosome positioning map for genomic sequences of any size. When compared with two existing methods, NuPoP shows improved performance in sensitivity.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.