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Melissa J. Moore

dblp:135/5817 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1

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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein structure analysis › protein binding site analysis
binding site detection
0.212013
ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq · Bioinform. 2013
Bioinformatics and computational biology › epigenomics › ChIP-seq analysis
peak detection
0.212013
ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq · Bioinform. 2013
Bioinformatics and computational biology
protein-RNA interaction
0.212013
ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq · Bioinform. 2013
Bioinformatics and computational biology
sequence analysis
0.212013
ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq · Bioinform. 2013
YearPublicationVenuePosition
2013 ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq
abstract
SUMMARY: Unlike DNA, RNA abundances can vary over several orders of magnitude. Thus, identification of RNA-protein binding sites from high-throughput sequencing data presents unique challenges. Although peak identification in ChIP-Seq data has been extensively explored, there are few bioinformatics tools tailored for peak calling on analogous datasets for RNA-binding proteins. Here we describe ASPeak (abundance sensitive peak detection algorithm), an implementation of an algorithm that we previously applied to detect peaks in exon junction complex RNA immunoprecipitation in tandem experiments. Our peak detection algorithm yields stringent and robust target sets enabling sensitive motif finding and downstream functional analyses. AVAILABILITY: ASPeak is implemented in Perl as a complete pipeline that takes bedGraph files as input. ASPeak implementation is freely available at https://sourceforge.net/projects/as-peak under the GNU General Public License. ASPeak can be run on a personal computer, yet is designed to be easily parallelizable. ASPeak can also run on high performance computing clusters providing efficient speedup. The documentation and user manual can be obtained from http://master.dl.sourceforge.net/project/as-peak/manual.pdf.
Alper Küçükural, Hakan Özadam, Guramrit Singh, Melissa J. Moore, Can Cenik
Bioinform.4