VLDB 2026 Research / reviewers in the wild / expert
Mehmet Tekman
dblp:211/6191
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0002-4181-2676ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author
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 › statistical genetics
haplotype analysis |
0.3 | 1 | 2017 | HaploForge: a comprehensive pedigree drawing and haplotype visualization web application · Bioinform. 2017 |
Bioinformatics and computational biology › genomics
haplotype inference |
0.3 | 1 | 2017 | HaploForge: a comprehensive pedigree drawing and haplotype visualization web application · Bioinform. 2017 |
Bioinformatics and computational biology › biological data visualization
haplotype visualization |
0.3 | 1 | 2017 | HaploForge: a comprehensive pedigree drawing and haplotype visualization web application · Bioinform. 2017 |
Bioinformatics and computational biology › statistical genetics
pedigree analysis |
0.3 | 1 | 2017 | HaploForge: a comprehensive pedigree drawing and haplotype visualization web application · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
identity by descent · 0.3a* search · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | OVAS: an open-source variant analysis suite with inheritance modellingabstractBACKGROUND: The advent of modern high-throughput genetics continually broadens the gap between the rising volume of sequencing data, and the tools required to process them. The need to pinpoint a small subset of functionally important variants has now shifted towards identifying the critical differences between normal variants and disease-causing ones. The ever-increasing reliance on cloud-based services for sequence analysis and the non-transparent methods they utilize has prompted the need for more in-situ services that can provide a safer and more accessible environment to process patient data, especially in circumstances where continuous internet usage is limited. RESULTS: To address these issues, we herein propose our standalone Open-source Variant Analysis Sequencing (OVAS) pipeline; consisting of three key stages of processing that pertain to the separate modes of annotation, filtering, and interpretation. Core annotation performs variant-mapping to gene-isoforms at the exon/intron level, append functional data pertaining the type of variant mutation, and determine hetero/homozygosity. An extensive inheritance-modelling module in conjunction with 11 other filtering components can be used in sequence ranging from single quality control to multi-file penetrance model specifics such as X-linked recessive or mosaicism. Depending on the type of interpretation required, additional annotation is performed to identify organ specificity through gene expression and protein domains. In the course of this paper we analysed an autosomal recessive case study. OVAS made effective use of the filtering modules to recapitulate the results of the study by identifying the prescribed compound-heterozygous disease pattern from exome-capture sequence input samples. CONCLUSION: OVAS is an offline open-source modular-driven analysis environment designed to annotate and extract useful variants from Variant Call Format (VCF) files, and process them under an inheritance context through a top-down filtering schema of swappable modules, run entirely off a live bootable medium and accessed locally through a web-browser. Monika Mozere, Mehmet Tekman, Jameela Kari, Detlef Bockenhauer, Robert Kleta, Horia Stanescu |
BMC Bioinform. | 2 |
| 2017 | HaploForge: a comprehensive pedigree drawing and haplotype visualization web applicationabstractMOTIVATION: Haplotype reconstruction is an important tool for understanding the aetiology of human disease. Haplotyping infers the most likely phase of observed genotypes conditional on constraints imposed by the genotypes of other pedigree members. The results of haplotype reconstruction, when visualized appropriately, show which alleles are identical by descent despite the presence of untyped individuals. When used in concert with linkage analysis, haplotyping can help delineate a locus of interest and provide a succinct explanation for the transmission of the trait locus. Unfortunately, the design choices made by existing haplotype visualization programs do not scale to large numbers of markers. Indeed, following haplotypes from generation to generation requires excessive scrolling back and forth. In addition, the most widely used program for haplotype visualization produces inconsistent recombination artefacts for the X chromosome. RESULTS: To resolve these issues, we developed HaploForge, a novel web application for haplotype visualization and pedigree drawing. HaploForge takes advantage of HTML5 to be fast, portable and avoid the need for local installation. It can accurately visualize autosomal and X-linked haplotypes from both outbred and consanguineous pedigrees. Haplotypes are coloured based on identity by descent using a novel A* search algorithm and we provide a flexible viewing mode to aid visual inspection. HaploForge can currently process haplotype reconstruction output from Allegro, GeneHunter, Merlin and Simwalk. AVAILABILITY AND IMPLEMENTATION: HaploForge is licensed under GPLv3 and is hosted and maintained via GitHub. https://github.com/mtekman/haploforge. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Mehmet Tekman, Alan Medlar, Monika Mozere, Robert Kleta, Horia Stanescu |
Bioinform. | 1 |