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Roberto Carta

dblp:48/5931 · 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis
microarray data analysis
0.112007
Short oligonucleotide probes containing G-stacks display abnormal binding affinity on Affymetrix microarrays · Bioinform. 2007
Bioinformatics and computational biology
microarray probe design
0.112007
Short oligonucleotide probes containing G-stacks display abnormal binding affinity on Affymetrix microarrays · Bioinform. 2007

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

positional dependent nearest neighbor model · 0.1
YearPublicationVenuePosition
2007 Short oligonucleotide probes containing G-stacks display abnormal binding affinity on Affymetrix microarrays
abstract
MOTIVATION: In microarray experiments, probe design is critical to the specific and accurate measurement of target concentrations. Current designs select suitable probes through in silico scanning of transcriptome/genome based on first principles. However, due to lack of tools, the observed microarray data have not been used to assess the performance of individual probes to provide feedback to improve future designs. RESULT: In this study, we describe a probe performance assessment method based on the concordance of the observed signals from probes that share common targets. Using this method, we found that probes containing multiple guanines in a row (G-stacks) have abnormal binding behavior compared with other probes, both in gene expression assays and genotyping assays using Affymetrix microarrays. These probes are less likely to covary with other probes that interrogate the same genes. Moreover, we found that these probes are much more likely to produce outliers when fitting the observed signals according to the positional dependent nearest neighbor model, which gives reasonable estimates of binding affinity for most other probes. These results suggest that probes containing G-stacks tend to have increased cross hybridization signals and reduced target-specific hybridization signals, presumably due to multiplex binding forming G-quartet structures. Our findings are expected to be useful in microarray design and data analysis.
Chunlei Wu, Keith A. Baggerly, Roberto Carta
Bioinform.4