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Qiang Song 0003

dblp:39/4333-3 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2013
0000-0002-5923-0842ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
epigenomics
0.322013
MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation · Bioinform. 2013
Identifying dispersed epigenomic domains from ChIP-Seq data · Bioinform. 2011
Bioinformatics and computational biology › epigenomics › DNA methylation › DNA methylation analysis
methylation level estimation
0.212013
MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation · Bioinform. 2013
Bioinformatics and computational biology › epigenomics
ChIP-seq analysis
0.012011
Identifying dispersed epigenomic domains from ChIP-Seq data · Bioinform. 2011

Methods — techniques the papers use, named apart from their topics

joint statistical modeling · 0.2bisulfite sequencing analysis · 0.2hidden markov model · 0.1differential histone modification detection · 0.1
YearPublicationVenuePosition
2013 MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation
abstract
MOTIVATION: The two major epigenetic modifications of cytosines, 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC), coexist with each other in a range of mammalian cell populations. Increasing evidence points to important roles of 5-hmC in demethylation of 5-mC and epigenomic regulation in development. Recently developed experimental methods allow direct single-base profiling of either 5-hmC or 5-mC. Meaningful analyses seem to require combining these experiments with bisulfite sequencing, but doing so naively produces inconsistent estimates of 5-mC or 5-hmC levels. RESULTS: We present a method to jointly model read counts from bisulfite sequencing, oxidative bisulfite sequencing and Tet-Assisted Bisulfite sequencing, providing simultaneous estimates of 5-hmC and 5-mC levels that are consistent across experiment types. AVAILABILITY: http://smithlab.usc.edu/software/mlml
Jianghan Qu, Qiang Song 0003, Elizabeth E. Hong, Andrew D. Smith
Bioinform.3
2011 Identifying dispersed epigenomic domains from ChIP-Seq data
abstract
MOTIVATION: Post-translational modifications to histones have several well known associations with regulation of gene expression. While some modifications appear concentrated narrowly, covering promoters or enhancers, others are dispersed as epigenomic domains. These domains mark contiguous regions sharing an epigenomic property, such as actively transcribed or poised genes, or heterochromatically silenced regions. While high-throughput methods like ChIP-Seq have led to a flood of high-quality data about these epigenomic domains, there remain important analysis problems that are not adequately solved by current analysis tools. RESULTS: We present the RSEG method for identifying epigenomic domains from ChIP-Seq data for histone modifications. In contrast with other methods emphasizing the locations of 'peaks' in read density profiles, our method identifies the boundaries of domains. RSEG is also able to incorporate a control sample and find genomic regions with differential histone modifications between two samples. AVAILABILITY: RSEG, including source code and documentation, is freely available at http://smithlab.cmb.usc.edu/histone/rseg/.
Qiang Song 0003, Andrew D. Smith
Bioinform.1