Gaussian mixture model-based unsupervised nucleotide modification number detection using nanopore-sequencing readouts is a research paper published in Bioinformatics (2020). On theSindex it has a DataRank of 0. It has been cited 29 times.
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National Institutes of Health
Grant: U54HG007990
National Institutes of Health
Grant: U01HL137183
National Institutes of Health
Grant: 2U41HG007234
National Institutes of Health
Grant: 5R01HG010053
W.M. Keck Foundation
Grant: DT06172015
NHGRI NIH HHS
Grant: R01 HG010053
NHGRI NIH HHS
Grant: U41 HG007234
National Institutes of Health
Grant: 1R01HG010053-01
A Unified Nanopore Platform for Direct Sequencing of Individual Full Length RNA Strands Bearing Modified Nucleotides
National Institutes of Health
Grant: 3U54HG007990-03S3
Center for Big Data in Translational Genomics
National Institutes of Health
Grant: 1U01HL137183-01
Unbiased analysis of genomic correlates of gene expression in health and disease
FWCI
1.69
Citation Percentile
0.8%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Additional file 1 of DNAscent v2: detecting replication forks in nanopore sequencing data with deep learning
Additional file 1 of DNAscent v2: detecting replication forks in nanopore sequencing data with deep learning