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Murat Ozcelik (born 1 January 1954) is a Turkish politician, civil servant and diplomat from the Republican People's Party (CHP), who has served as a Member of Parliament for Istanbul's third electoral district since 7 June 2015.
What was the political party of Murat Özçelik?

In cancer research, background models for mutation rates have been extensively calibrated in coding regions, leading to the identification of many driver genes, recurrently mutated more than expected. Noncoding regions are also associated with disease; however, background models for them have not been investigated in as much detail. This is partially due to limited noncoding functional annotation. Also, great mutation heterogeneity and potential correlations between neighboring sites give rise to substantial overdispersion in mutation count, resulting in problematic background rate estimation. Here, we address these issues with a new computational framework called LARVA. It integrates variants with a comprehensive set of noncoding functional elements, modeling the mutation counts of the elements with a -binomial distribution to handle overdispersion. LARVA, moreover, uses regional genomic features such as replication timing to better estimate local mutation rates and mutational hotspots. We demonstrate LARVA's effectiveness on 760 whole-genome tumor sequences, showing that it identifies well-known noncoding drivers, such as mutations in the TERT promoter. Furthermore, LARVA highlights several novel highly mutated regulatory sites that could potentially be noncoding drivers. We make LARVA available as a software tool and release our highly mutated annotations as an online resource (larva.gersteinlab.org).
Which tool is used for the identification of recurrent variants in noncoding regions?

To validate the presence and demonstrate the clinical value of the type I interferon (IFN)-signature during arthritis development. In 115 seropositive arthralgia patients who were followed for the development of arthritis (Amsterdam Reade cohort), and 25 presymptomatic individuals who developed rheumatoid arthritis (RA) later, and 45 population-based controls (Northern Sweden cohort), the expression levels of 7 type I IFN response genes were determined with multiplex qPCR and an IFN-score was calculated. The diagnostic performance of the IFN-score was evaluated using Cox regression and Receiver Operating Characteristics (ROC)-curve analysis. In 44 of the 115 at-risk individuals (38%) from the Amsterdam Reade cohort, arthritis developed after a median period of 8 months (IQR 5-13). Stratification of these individuals based on the IFN-score revealed that 15 out of 25 IFN(high) individuals converted to arthritis, compared with 29 out of 90 IFN(low) individuals (p=0.011). In the Northern Sweden cohort, the level of the IFN-score was also significantly increased in presymptomatic individuals who developed RA compared with population-based controls (p=0.002). Cox regression analysis of the Amsterdam Reade cohort showed that the hazard ratio (HR) for development of arthritis was 2.38 (p=0.008) for IFN(high) at-risk individuals after correction for anticitrullinated protein antibodies (ACPA) and rheumatoid factor (RF). The ROC-curve area under the curve (AUC) for the IFN-score combined with ACPA and RF in the prediction of arthritis was 78.5% (p=0.0001, 95% CI 0.70 to 0.87). The results demonstrated clinical utility for the IFN-signature as a biomarker in the prediction of arthritis development.

Which is the most common gene signature in Rheumatoid Arthritis patients?