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Paul Polakis

dblp:54/7029 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cancer genomics
0.012004
GEPIS - quantitative gene expression profiling in normal and cancer tissues · Bioinform. 2004
Bioinformatics and computational biology › transcriptomics
expressed sequence tag analysis
0.012004
GEPIS - quantitative gene expression profiling in normal and cancer tissues · Bioinform. 2004
Bioinformatics and computational biology
gene expression analysis
0.012004
GEPIS - quantitative gene expression profiling in normal and cancer tissues · Bioinform. 2004
Bioinformatics and computational biology › gene expression analysis › gene expression pattern analysis
tissue-specific gene expression
0.012004
GEPIS - quantitative gene expression profiling in normal and cancer tissues · Bioinform. 2004
YearPublicationVenuePosition
2004 GEPIS - quantitative gene expression profiling in normal and cancer tissues
abstract
MOTIVATION: Expression profiling in diverse tissues is fundamental to understanding gene function as well as therapeutic target identification. The vast collection of expressed sequence tags (ESTs) and the associated tissue source information provides an attractive opportunity for studying gene expression. RESULTS: To facilitate EST-based expression analysis, we developed GEPIS (gene expression profiling in silico), a tool that integrates EST and tissue source information to compute gene expression patterns in a large panel of normal and tumor samples. We found EST-based expression patterns to be consistent with published papers as well as our own experimental results. We also built a GEPIS Regional Atlas that depicts expression characteristics of all genes in a selected genomic region. This program can be adapted for large-scale screening for genes with desirable expression patterns, as illustrated by our large-scale mining for tissue- and tumor-specific genes. AVAILABILITY: The email server version of the GEPIS application is freely available at http://share.gene.com/share/gepis. An interactive version of GEPIS will soon be freely available at http://www.cgl.ucsf.edu/Research/genentech/gepis/. The source code, modules, data and gene lists can be downloaded at http://share.gene.com/share/gepis.
David A. Eberhard, Gretchen D. Frantz, Patrick Dowd, Thomas D. Wu, Colin K. Watanabe, Shiuh-Ming Luoh, Paul Polakis, Kenneth J. Hillan, William I. Wood, Zemin Zhang
Bioinform.9