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Brian D. Dynlacht

dblp:90/5911 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
functional genomics
0.112007
Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data · Bioinform. 2007
Bioinformatics and computational biology › gene expression analysis
microarray data analysis
0.112007
Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data · Bioinform. 2007
Bioinformatics and computational biology › epigenomics
ChIP-chip analysis
0.012007
Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data · Bioinform. 2007

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

adaptive multiscale algorithm · 0.1
YearPublicationVenuePosition
2007 Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data
abstract
UNLABELLED: We present a fast, versatile and adaptive-multiscale algorithm for analyzing a wide-variety of DNA microarray data. Its primary application is in normalization of array data as well as subsequent identification of 'enriched targets', e.g. differentially expressed genes in expression profiling arrays and enriched sites in ChIP-on-chip experimental data. We show how to accommodate the unique characteristics of ChIP-on-chip data, where the set of 'enriched targets' is large, asymmetric and whose proportion to the whole data varies locally. SUPPLEMENTARY INFORMATION: Supplementary figures, related preprint, free software as well as our raw DNA microarray data with PCR validations are available at http://www.math.umn.edu/~lerman/supp/bioinfo06 as well as Bioinformatics online.
Gilad Lerman, Joseph McQuown, Alexandre Blais, Brian D. Dynlacht, Guangliang Chen, Bud Mishra
Bioinform.4