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Hakan Alakus

dblp:132/3464 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-3889-3276ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 94% Medical and health informatics · 6%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
epigenetic biomarker discovery
0.212014
Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression · Bioinform. 2014
Bioinformatics and computational biology › gene regulation › gene regulatory network
gene regulatory network analysis
0.212014
Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression · Bioinform. 2014
Bioinformatics and computational biology › metagenomics › amplicon sequencing
amplicon sequencing analysis
0.212013
Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing · Bioinform. 2013
Bioinformatics and computational biology › sequence analysis
sequencing data analysis
0.212013
Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing · Bioinform. 2013
Bioinformatics and computational biology › cancer genomics › somatic mutation analysis
somatic mutation detection
0.212013
Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing · Bioinform. 2013
Medical and health informatics
cancer prognosis
0.112014
Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression · Bioinform. 2014

Methods — techniques the papers use, named apart from their topics

survival analysis · 0.2network topology analysis · 0.2differential methylation analysis · 0.2variant calling pipeline · 0.2
YearPublicationVenuePosition
2014 Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression
abstract
MOTIVATION: A rapid progression of esophageal squamous cell carcinoma (ESCC) causes a high mortality rate because of the propensity for metastasis driven by genetic and epigenetic alterations. The identification of prognostic biomarkers would help prevent or control metastatic progression. Expression analyses have been used to find such markers, but do not always validate in separate cohorts. Epigenetic marks, such as DNA methylation, are a potential source of more reliable and stable biomarkers. Importantly, the integration of both expression and epigenetic alterations is more likely to identify relevant biomarkers. RESULTS: We present a new analysis framework, using ESCC progression-associated gene regulatory network (GRN escc), to identify differentially methylated CpG sites prognostic of ESCC progression. From the CpG loci differentially methylated in 50 tumor-normal pairs, we selected 44 CpG loci most highly associated with survival and located in the promoters of genes more likely to belong to GRN escc. Using an independent ESCC cohort, we confirmed that 8/10 of CpG loci in the promoter of GRN escc genes significantly correlated with patient survival. In contrast, 0/10 CpG loci in the promoter genes outside the GRN escc were correlated with patient survival. We further characterized the GRN escc network topology and observed that the genes with methylated CpG loci associated with survival deviated from the center of mass and were less likely to be hubs in the GRN escc. We postulate that our analysis framework improves the identification of bona fide prognostic biomarkers from DNA methylation studies, especially with partial genome coverage.
Chun-Pei Cheng, I-Ying Kuo, Hakan Alakus, Kelly A. Frazer, Olivier Harismendy, Yi-Ching Wang, Vincent S. Tseng
Bioinform.3
2013 Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing
abstract
SUMMARY: We present Mutascope, a sequencing analysis pipeline specifically developed for the identification of somatic variants present at low-allelic fraction from high-throughput sequencing of amplicons from matched tumor-normal specimen. Using datasets reproducing tumor genetic heterogeneity, we demonstrate that Mutascope has a higher sensitivity and generates fewer false-positive calls than tools designed for shotgun sequencing or diploid genomes. AVAILABILITY: Freely available on the web at http://sourceforge.net/projects/mutascope/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Shawn E. Yost, Hakan Alakus, Hiroko Matsui, Richard B. Schwab, Kristen Jepsen, Kelly A. Frazer, Olivier Harismendy
Bioinform.2