Bioinformatics Specialist
Specializing in single-cell RNA-seq, spatial transcriptomics, and multi-omics integration. I develop custom bioinformatics pipelines and interactive applications that accelerate drug discovery and enable data-driven therapeutic insights.
I'm a bioinformatics specialist with expertise in analyzing complex omics data, building analytical pipelines, and developing user-friendly applications for biological research. My work bridges the gap between computational biology and practical software engineering.
With experience spanning pharmaceutical industry and academic research, I specialize in single-cell RNA-seq analysis, spatial transcriptomics, and creating tools that enable researchers to explore their data more effectively. I've collaborated succesfully with many clients spanning from small biotechnology companies to the biggest pharmaceutical companies, contributed to publications and presented my work publicly at international conferences and webinars.
Published study integrating scRNA-seq data from 14 public datasets to validate a 3D in vitro model. Identified SPP1+ tumor-associated macrophage signatures across cancer types and inflammatory diseases, establishing clinical relevance for immunotherapy testing.
Read PublicationCo-hosted webinar with Immudex focusing on bioinformatic analysis of scRNA-seq data using dCODE® reagents. Covered T and B cell receptor analysis, comprehensive bioinformatics workflows, and experimental design strategies for precise immune profiling.
View DetailsPublished research using WES and RNA-seq data from 71 colorectal cancer patients to identify personalized therapeutic targets. Implemented AI-driven neoantigen prediction and identified synthetic lethality gene pairs for precision medicine applications.
Read PublicationPresented comprehensive overview of single-cell RNA-seq analysis capabilities at Ardigen. Covered data preprocessing, quality control, and downstream analyses for drug discovery, including dataset integration and target validation approaches with a respiratory disease case study.
View DetailsPresented poster and talk at ISMB/ECCB 2023 introducing scDisco, a user-friendly app for single-cell RNA-seq analysis. The tool enables non-experts to explore and compare data through intuitive visualizations including dot plots, comparative analyses, and cell proportion quantification.
View DetailsEarned globally recognized certifications demonstrating fundamental level of Professional Scrum Product Ownership and Scrum mastery. PSPO I certification proves intermediate understanding of the Scrum framework and how to apply it to maximize value delivery, including optimizing return on investment and total cost of ownership. PSM I certification demonstrates consistent use of Scrum terminology and approach as described in the Scrum Guide.
View Scrum.org ProfileConducted comprehensive transcriptional profiling of peripheral blood and lamina propria mononuclear cells in ulcerative colitis patients. Analyzed differential gene expression patterns and immune cell composition to identify disease-associated signatures and potential therapeutic targets.
View DetailsKraków, Poland
Barcelona, Spain
Barcelona, Spain
Universitat Autònoma de Barcelona - High Performance Computing and Big Data Analytics
University of Dundee, Scotland
This study integrated single-cell RNA-seq data from 14 public datasets spanning multiple cancer types and inflammatory lung diseases to validate a 3D human cell-based model for drug testing. We identified that macrophages in the in vitro system share key transcriptional signatures with SPP1+ tumor-associated macrophages (TAMs) found across diverse disease contexts, establishing the model as a clinically relevant platform for testing immunotherapy targeting this pro-angiogenic and pro-fibrotic macrophage population.
Using whole exome sequencing and bulk RNA-seq data from 71 Polish colorectal cancer patients, we implemented three complementary AI-driven approaches to identify personalized therapeutic targets. Our ARDentify neoantigen prediction pipeline identified approximately 8,700 unique neoepitopes with limited patient overlap, while a novel AI approach aligning patient profiles with cancer cell lines successfully identified synthetic lethality gene pairs (APC-CTNNB1, BRAF-DUSP4, APC-TCF7L2) and VPS4A-VPS4B as potential therapeutic targets.
I'm available for consulting, contract work, and collaboration on bioinformatics projects. Whether you need custom analysis pipelines, data visualization tools, or bioinformatics expertise, I'd love to hear from you.