Berkay Özçelik Email & Phone Number

Istanbul, Turkey

Istanbul, Türkiye

Design and develop profitability reports forecasting pipelines.Create extended BI reports using PowerBI in sales, marketing, finance, and partner services.

Jena, Thuringia, Germany

AI in Microbiome and Aging Research Group - MD Lab Main Workflow: Journal Club Presentations- Topics: Liquid Neural Networks with ODE, Batch Effect correction using Auto-Encoders.- Objective: Dissemination of advanced methodologies and technologies in the field. - Internship Project: Aging and Sepsis Disease's Microbial Content in Blood Research: Project Presentation available at: https://docs.google.com/presentation/d/1JIHeiOQtfDc7xrT3C0JADlQ2g_VCTCx8/edit?usp=sharing&ouid=117143033315170127674&rtpof=true&sd=true Tasks: - Literature review; non-polyA captured, transcriptomics (NGS) datasets in aging and sepsis field. - Data quality and control; FASTQC, MULTIQC & Paired-end or Single-end etc. - Data cleaning; Removing adaptor sequences. - Classification; Kraken2 (k-mer based taxonomic classification) and Bracken (Bayesian Reestimation of Abundance with KrakEN) interpretation. - DEGs analysis; T-Test with Benjamini/Hochberg correction. - Feature extraction; Abundance and bracken adjusted reads filtering using Pandas and SQL (pd.query). - Results interpretation with Mann Whitney U Test. Side Project: Web-Based Gene-Enrichment and Functional Annotation Tool: - Objective: To provide a comprehensive set of functional annotation tools for researchers to understand the biological meaning behind large lists of genes. - Project Repository: https://github.com/noepinefrin/n2rich Used tech and libraries: Machine Learning (sci-kit learn & PyTorch), Linux/Bash, Statistical Evaluation (SciPy), Data Manipulation (Pandas & SQL), Containerization (Docker), Django (Backend), Celery (Background task and queueing for enrichment analysis), Redis (In-memory DB for Celery), PostgreSQL (Database).

Istanbul, Turkey

System's Bioengineering Research Group - Arga Lab• Biomarker discovery using normalization, statistical significance analysis, and machine learning on Lung adenocarcinoma (TCGA-LUAD) and lung squamous cell carcinoma (TCGA-LUSC) mRNA gene expression datasets featured on The Cancer Genome Atlas (a.k.a TCGA). Up-regulated and down-regulated), enrichment analysis (Ontology, "GO", pathway, "KEGG" and Disease "OMIM") followed by model evaluation (complexity matrix "sensitivity, specificity and F1 score", ROC curve "AUC" , Youden's J statistic) and investigation of early diagnosis possibilities. w/ Professor Kazim Yalcin ARGA• Normalization (FPKM) on the gene expression dataset encoded GSE123544 on Gene Expression Omnibus (Gene Expression Omnibus, a.k.a GEO), biomarker discovery for each drug on P. aeruginosa exposed to 4 different drugs (on antimicrobial resistance), venn diagram, statistical significance analysis, model evaluation (complexity matrix "sensitivity, specificity and F1 score", ROC curve "AUC") and determination of treatment modalities. w/ Professor Kazim Yalcin ARGA, Dr. Ceyda Kula• Data cleaning and preprocessing, normalization, statistical significance analysis on Invasive Breast Cancer (TCGA-BRCA) mRNA gene expression datasets on The Cancer Genome Atlas (a.k.a TCGA), models that can be used in early diagnosis discovery, model evaluation (complexity matrix "sensitivity, specificity and F1 score", ROC curve "AUC") and enrichment analysis (Ontology, "GO", pathway, "KEGG" and Disease "OMIM") using machine learning methods. w/ Professor Kazim Yalcin ARGA, Dr. Medi Kori

İstanbul, Türkiye

TÜBİTAK STAR 2247-C, Proje Numarası: 221S424, Proje Başlığı: Abdominal Aort Anevrizmasının Erken Teşhis ve Tedavisine Yönelik Biyobelirteç ve İlaç Adayların Belirlenmesi