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Joel McManus

dblp:178/2932 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 2

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics › transcript isoform analysis
isoform quantification
0.212016
Isoform-level ribosome occupancy estimation guided by transcript abundance with Ribomap · Bioinform. 2016
Bioinformatics and computational biology › transcriptomics
ribosome profiling
0.212016
Isoform-level ribosome occupancy estimation guided by transcript abundance with Ribomap · Bioinform. 2016
Bioinformatics and computational biology
transcriptomics
0.212016
Isoform-level ribosome occupancy estimation guided by transcript abundance with Ribomap · Bioinform. 2016
Bioinformatics and computational biology › RNA biology
translation
0.212016
Accurate Recovery of Ribosome Positions Reveals Slow Translation of Wobble-Pairing Codons in Yeast · RECOMB 2016
YearPublicationVenuePosition
2016 Accurate Recovery of Ribosome Positions Reveals Slow Translation of Wobble-Pairing Codons in Yeast
Hao Wang 0024, Joel McManus, Carl Kingsford
RECOMB2
2016 Isoform-level ribosome occupancy estimation guided by transcript abundance with Ribomap
abstract
UNLABELLED: : Ribosome profiling is a recently developed high-throughput sequencing technique that captures approximately 30 bp long ribosome-protected mRNA fragments during translation. Because of alternative splicing and repetitive sequences, a ribosome-protected read may map to many places in the transcriptome, leading to discarded or arbitrary mappings when standard approaches are used. We present a technique and software that addresses this problem by assigning reads to potential origins proportional to estimated transcript abundance. This yields a more accurate estimate of ribosome profiles compared with a naïve mapping. AVAILABILITY AND IMPLEMENTATION: Ribomap is available as open source at http://www.cs.cmu.edu/∼ckingsf/software/ribomap CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Hao Wang 0024, Joel McManus, Carl Kingsford
Bioinform.2