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Timothy R. Zacharewski

dblp:76/3956 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2005
—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 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis
microarray data analysis
0.122005
Normalization of two-channel microarray experiments: a semiparametric approach · Bioinform. 2005
GP3: GenePix post-processing program for automated analysis of raw microarray data · Bioinform. 2002

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

local regression smoothing · 0.1analysis of variance · 0.1batch processing · 0.0
YearPublicationVenuePosition
2005 Normalization of two-channel microarray experiments: a semiparametric approach
abstract
MOTIVATION: An important underlying assumption of any experiment is that the experimental subjects are similar across levels of the treatment variable, so that changes in the response variable can be attributed to exposure to the treatment under study. This assumption is often not valid in the analysis of a microarray experiment due to systematic biases in the measured expression levels related to experimental factors such as spot location (often referred to as a print-tip effect), arrays, dyes, and various interactions of these effects. Thus, normalization is a critical initial step in the analysis of a microarray experiment, where the objective is to balance the individual signal intensity levels across the experimental factors, while maintaining the effect due to the treatment under investigation. RESULTS: Various normalization strategies have been developed including log-median centering, analysis of variance modeling, and local regression smoothing methods for removing linear and/or intensity-dependent systematic effects in two-channel microarray experiments. We describe a method that incorporates many of these into a single strategy, referred to as two-channel fastlo, and is derived from a normalization procedure that was developed for single-channel arrays. The proposed normalization procedure is applied to a two-channel dose-response experiment.
Jeanette E. Eckel, C. Gennings, Terry M. Therneau, L. D. Burgoon, D. R. Boverhof, Timothy R. Zacharewski
Bioinform.6
2002 GP3: GenePix post-processing program for automated analysis of raw microarray data
abstract
Abstract Summary: Here we describe an automated and customizable program to correct, filter and normalize raw microarray data captured using GenePix, a commonly used microarray image analysis application. Files can be processed individually or in batch mode for increased throughput. User defined inputs specify the stringency of data filtering and the method and conditions of normalization. The output includes gene summaries for replicate spots and descriptive statistics for each experiment. The source code (Perl) can also be adapted to handle raw data output from other image analysis applications. Availability: http://bch.msu.edu/~zacharet/microarray/GP3.html Contact: [email protected] Supplementary information: http://bch.msu.edu/~zacharet/microarray/GP3.html * To whom correspondence should be addressed.
M. R. Fielden, R. G. Halgren, E. Dere, Timothy R. Zacharewski
Bioinform.4