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Ken Dewar

dblp:37/4340 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2004
0000-0003-2688-138XORCID · corroborated

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 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › multiple sequence alignment
multiple sequence alignment analysis
0.012004
Identifying multiple alignment regions satisfying simple formulas and patterns · Bioinform. 2004

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

pattern specification · 0.0formula-based region matching · 0.0statistical test · 0.0graph-based resolution · 0.0
YearPublicationVenuePosition
2004 Identifying multiple alignment regions satisfying simple formulas and patterns
abstract
MOTIVATION: When studying multiple alignments of genomic sequences one frequently aims to locate and count regions which satisfy a set of constraints. These regions may be putatively functional, but researchers may also be interested in quantifying the frequency of occurrences of certain patterns. RESULTS: We have developed a program that applies simple formulas and pattern specifications to multiple alignments, reporting the positions and counts of conforming regions. As an example, we have navigated a 15-species alignment of the CAV2-CAV1 region and outlined some findings regarding PPARgamma binding sites. AVAILABILITY: Our software and the accompanying documentation can be obtained at no charge by contacting the authors. It can also be accessed at http://ranger.uta.edu/~nick/compgen
Nikola Stojanovic, Ken Dewar
Bioinform.2
2002 Identification of mixups among DNA sequencing plates
abstract
Abstract Motivation: During the process of high-throughput genome sequencing there are opportunities for mixups of reagents and data associated with particular projects. The sequencing templates or sequence data generated for an assembly may become contaminated with reagents or sequences from another project, resulting in poorer quality and inaccurate assemblies. Results: We have developed a system to assess sequence assemblies and monitor for laboratory mixups. We describe several methods for testing the consistency of assemblies and resolving mixed ones. We use statistical tests to evaluate the distribution of sequencing reads from different plates into contigs, and a graph-based approach to resolve situations where data has been inappropriately combined. While these methods have been designed for use in a high-throughput DNA sequencing environment processing thousands of clones, they can be applied in any situation where distinct sequencing projects are performed at redundant coverage. Availability: Our software is available for downloading from: ftp-genome.wi.mit.edu/distribution/mixups_detection Contact: [email protected] * To whom correspondence should be addressed.
Nikola Stojanovic, Jean L. Chang, Jessica Lehoczky, Michael C. Zody, Ken Dewar
Bioinform.5