Demo Data from EDBT 2026 / reviewers in the wild / expert
Somayyeh Fahiminiya
dblp:157/9419
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · unresolved
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › cancer genomics
allelic imbalance detection |
0.2 | 1 | 2015 | ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data · Bioinform. 2015 |
Bioinformatics and computational biology
cancer genomics |
0.2 | 1 | 2015 | ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data · Bioinform. 2015 |
Bioinformatics and computational biology › cancer genomics › chromosomal aberration detection
loss of heterozygosity detection |
0.2 | 1 | 2015 | ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
statistical approach · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing dataabstractSUMMARY: Whole-exome sequencing (WES) has extensively been used in cancer genome studies; however, the use of WES data in the study of loss of heterozygosity or more generally allelic imbalance (AI) has so far been very limited, which highlights the need for user-friendly and flexible software that can handle low-quality datasets. We have developed a statistical approach, ExomeAI, for the detection of recurrent AI events using WES datasets, specifically where matched normal samples are not available. AVAILABILITY: ExomeAI is a web-based application, publicly available at: http://genomequebec.mcgill.ca/exomeai. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Javad Nadaf, Jacek Majewski, Somayyeh Fahiminiya |
Bioinform. | 3 |