Demo Data from VLDB 2026 / reviewers in the wild / expert
Delnaz Roshandel
dblp:98/7309
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-4902-8587ORCID · reported
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › population genetics
haplotype block detection |
0.4 | 1 | 2019 | gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks · Bioinform. 2019 |
Bioinformatics and computational biology › population genetics
linkage disequilibrium |
0.4 | 1 | 2019 | gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks · Bioinform. 2019 |
Bioinformatics and computational biology
population genetics |
0.4 | 1 | 2019 | gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks · Bioinform. 2019 |
Bioinformatics and computational biology › genomics
genome visualization |
0.1 | 1 | 2019 | gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
clustering algorithms · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocksabstractSUMMARY: For the analysis of high-throughput genomic data produced by next-generation sequencing (NGS) technologies, researchers need to identify linkage disequilibrium (LD) structure in the genome. In this work, we developed an R package gpart which provides clustering algorithms to define LD blocks or analysis units consisting of SNPs. The visualization tool in gpart can display the LD structure and gene positions for up to 20 000 SNPs in one image. The gpart functions facilitate construction of LD blocks and SNP partitions for vast amounts of genome sequencing data within reasonable time and memory limits in personal computing environments. AVAILABILITY AND IMPLEMENTATION: The R package is available at https://bioconductor.org/packages/gpart. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Sun-Ah Kim, Myriam Brossard, Delnaz Roshandel, Andrew D. Paterson, Shelley B. Bull, Yun Joo Yoo |
Bioinform. | 3 |