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Somayyeh Fahiminiya

dblp:157/9419 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › cancer genomics
allelic imbalance detection
0.212015
ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data · Bioinform. 2015
Bioinformatics and computational biology
cancer genomics
0.212015
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
0.212015
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
YearPublicationVenuePosition
2015 ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data
abstract
SUMMARY: 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