Demo Data from EDBT 2026 / reviewers in the wild / expert
Lee-Jen Wei
dblp:01/5936
· DBLP profile ↗
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 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
cancer genomics |
0.0 | 1 | 2004 | dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data · Bioinform. 2004 |
Bioinformatics and computational biology › genomics
genome visualization |
0.0 | 1 | 2004 | dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data · Bioinform. 2004 |
Bioinformatics and computational biology › statistical genetics
genotype data analysis |
0.0 | 1 | 2004 | dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data · Bioinform. 2004 |
Bioinformatics and computational biology › cancer genomics › chromosomal aberration detection
loss of heterozygosity detection |
0.0 | 1 | 2004 | dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data · Bioinform. 2004 |
Bioinformatics and computational biology › statistical genetics
single nucleotide polymorphism analysis |
0.0 | 1 | 2004 | dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data · Bioinform. 2004 |
Methods — techniques the papers use, named apart from their topics
statistical inference · 0.0clustering · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity dataabstractMOTIVATION: Oligonucleotide microarrays allow genotyping of thousands of single-nucleotide polymorphisms (SNPs) in parallel. Recently, this technology has been applied to loss-of-heterozygosity (LOH) analysis of paired normal and tumor samples. However, methods and software for analyzing such data are not fully developed. RESULT: Here, we report automated methods for pooling SNP array replicates to make LOH calls, visualizing SNP and LOH data along chromosomes in the context of genes and cytobands, making statistical inference to identify shared LOH regions, clustering samples based on LOH profiles and correlating the clustering results to clinical variables. Application of these methods to prostate and breast cancer datasets generates biologically important results. AVAILABILITY: The software module dChipSNP implementing these methods is available at http://biosun1.harvard.edu/complab/dchip/snp/ SUPPLEMENTARY INFORMATION: The breast cancer data are provided by Andrea L. Richardson, Zhigang C. Wang and James D. Iglehart. Lee-Jen Wei, William R. Sellers, Marshall Lieberfarb, Wing Hung Wong, Cheng Li 0016 |
Bioinform. | 2 |