Demo Data from EDBT 2026 / reviewers in the wild / expert
Kaveh Maghsoudi
dblp:13/1435
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis
microarray data analysis |
0.1 | 1 | 2007 | Microarray blob-defect removal improves array analysis · Bioinform. 2007 |
Bioinformatics and computational biology › epigenomics
ChIP-chip analysis |
0.0 | 1 | 2007 | Microarray blob-defect removal improves array analysis · Bioinform. 2007 |
Methods — techniques the papers use, named apart from their topics
spike-in experiment · 0.1blob detection · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Microarray blob-defect removal improves array analysisabstractMOTIVATION: New generation Affymetrix oligonucleotide microarrays often have blob-like image defects that will require investigators to either repeat their hybridization assays or analyze their data with the defects left in place. We investigated the effect of analyzing a spike-in experiment on Affymetrix ENCODE tiling arrays in the presence of simulated blobs covering between 1 and 9% of the array area. Using two different ChIP-chip tiling array analysis programs (Affymetrix tiling array software, TAS, and model-based analysis of tiling arrays, MAT), we found that even the smallest blob defects significantly decreased the sensitivity and increased the false discovery rate (FDR) of the spike-in target prediction. RESULTS: We introduced a new software tool, the microarray blob remover (MBR), which allows rapid visualization, detection and removal of various blob defects from the .CEL files of different types of Affymetrix microarrays. It is shown that using MBR significantly improves the sensitivity and FDR of a tiling array analysis compared to leaving the affected probes in the analysis. AVAILABILITY: The MBR software and the sample array .CEL files used in this article are available at: http://liulab.dfci.harvard.edu/Software/MBR/MBR.htm Jun S. Song, Kaveh Maghsoudi, Wei Li 0036, John Quackenbush, Xiaole Shirley Liu |
Bioinform. | 2 |