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P. N. Shah

dblp:96/6743 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—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 › gene expression analysis
microarray data analysis
0.012003
A tool-kit for cDNA microarray and promoter analysis · Bioinform. 2003
Bioinformatics and computational biology › gene expression analysis › microarray data preprocessing
microarray data normalization
0.012003
A tool-kit for cDNA microarray and promoter analysis · Bioinform. 2003
Bioinformatics and computational biology › gene regulation
promoter analysis
0.012003
A tool-kit for cDNA microarray and promoter analysis · Bioinform. 2003
Bioinformatics and computational biology › gene regulation › transcription factor binding site prediction
transcription factor binding site analysis
0.012003
A tool-kit for cDNA microarray and promoter analysis · Bioinform. 2003

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

data standardization · 0.0EST mapping · 0.0
YearPublicationVenuePosition
2003 A tool-kit for cDNA microarray and promoter analysis
abstract
We describe two sets of programs for expediting routine tasks in analysis of cDNA microarray data and promoter sequences. The first set permits bad data points to be flagged with respect to a number of parameters and performs normalization in three different ways. It allows combining of result files into comprehensive data sets, evaluation of the quality of both technical and biological replicates and row and/or column standardization of data matrices. The second set supports mapping ESTs in the genome, identifying the corresponding genes and recovering their promoters, analyzing promoters for transcription factor binding sites, and visual representation of the results. The programs are designed primarily for Arabidopsis thaliana researchers, but can be adapted readily for other model systems. Availability and Supplementary information: http://www.personal.psu.edu/nhs109/Programs/
Nigam H. Shah, D. C. King, P. N. Shah, Nina V. Fedoroff
Bioinform.3