Catalin-George Clinciu

Bioinformatics master's graduate with diverse computational skills and a strong capacity for rapid skill acquisition. Proficient in pipeline construction for NGS data analysis, implementing explainable AI, and
use of machine learning tools. Extensive hands-on laboratory experience, culminating in a promotion to section manager, reflexion of my hard work and dedication. Eager to further enhance my expertise and capabilities while on the path to becoming a distinguished bioinformatics specialist.

Conducted research at a renowned institution, utilizing explainable AI and epigenetic features to predict enhancer activity across various cell types.
Developed expertise in analysing various types of sequencing data (ChIP-seq, ATAC-seq, DNase-seq, WGBS and STARR-seq).
Proposed and autonomously executed new research projects, showcasing independent bioinformatics proficiency.
Performed rigorous data quality control and validation procedures to ensure accuracy and reliability of results.
Advanced coding skills in R and its bioinformatics packages.
Used HPC and optimized workflow efficacy, integrating parallel job submission.
Created efficient, scalable and reproducible data analysis pipelines.
Delivered concise presentation of computational results.

Distinction expected
Kept conventional directory structures for computational projects.
Ability to handle large genomic datasets and use of bioinformatics tools.
Constructed and evaluated reference genomes and reference gene sets.
Worked with both Illumina short reads and Nanopore long reads.
Trained in a variety of programming languages (Python, R, SQL and HTML)
Deep understanding of statistical analysis of bioinformatics data.
Experience with genomics, transcriptomics and proteomics data sets.
Used ML models (Scikit-learn, Pandas, Matplotlib) to assess sample types with most diagnostic value for Crohn's disease: trained, applied and evaluated supervised ML models (support vector machines and random forests).
Developed a web application (Flask, HTML, CSS) for retrieval of genetic variants from all known associations to T1D and integrate them with population and functional information and analysis.
Used SQL to build, manage and use a relational database for a web application.
Gained the ability to understand advanced technical terms and build on existing skills that allow me to adapt to any bioinformatics demand.