Named after the ACTN3 "Speed Gene" - We accelerate your discoveries
🧬 AI-Powered Genomics • 📦 Production Pipelines • 🔬 Reproducible Research • 🚀 Open Source
Transforming raw sequencing data into clinical insights through modern bioinformatics workflows
The ACTN3 gene (the "Speed Gene") is associated with explosive muscle performance and athletic prowess. Just like this gene enables peak physical performance, ACTN3 Bioinformatics delivers fast, efficient, and high-performance genomic analysis solutions.
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Accelerate drug discovery and precision medicine by providing:
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Production-grade Snakemake pipeline transforming scRNA-seq CRISPR screens into balanced, harmonized datasets for AI/ML training
Key Features:
- 🔄 Automated QC + normalization (Scanpy)
- ⚖️ Smart class balancing for unbiased ML
- 🔗 Batch integration (Harmony/BBKNN)
- 🧬 Feature engineering (pathways, TF regulons)
- 📊 Leave-genes-out cross-validation
- 🐍 Python 3.10, Snakemake, Quarto
Performance: Processes 10k cells in ~15 minutes on laptop (AMD Ryzen 5 7535HS, 16GB RAM)
Impact: Virtual Cell Challenge 2025 submission showcasing production-ready bioinformatics engineering
Comprehensive Quarto knowledge base documenting R/Pharma 2025 conference workshops, trends, and best practices
Content Highlights:
- 📝 19 workshop summaries (AI/LLM, Clinical Reporting, Validation, Bayesian Methods)
- 🎤 30+ presentation summaries
- 📈 Industry trend analysis (AI revolution, GSK's 50%+ R adoption)
- 🛠️ Complete A-Z tools catalog (ellmer, gtsummary, teal, officer, etc.)
- 💼 Career insights for R pharma professionals
Technologies: Quarto, RMarkdown, GitHub Actions, GitHub Pages
Recognition: Showcases expertise in modern documentation workflows and pharmaceutical R ecosystem
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From FASTQ to Figures
Format: Quarto reports + GitHub repo |
Production-Ready Workflows
Format: Reproducible code + pkgdown site |
Modern AI-Powered Analysis
Format: Trained models + deployment scripts |
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Bioconductor Standards
Format: Fully documented package |
Shiny Applications
Format: Hosted app + source code |
From Analysis to Paper
Format: Camera-ready materials |
R/Bioconductor: limma, edgeR, DESeq2, fgsea, ComplexHeatmap, Seurat, crisprVerse, MAGeCK
Python: Scanpy, AnnData, PyTorch, TensorFlow, scikit-learn, Harmony, gseapy
Pipelines: Snakemake ≥7.0, Nextflow DSL2, Bash scripting
Reproducibility: Quarto, RMarkdown, knitr, pkgdown, GitHub Actions
Infrastructure: Docker, Conda/Mamba, HPC (Slurm), AWS/Azure
AI/LLM: ellmer, OpenAI API, Anthropic Claude, Prompt Engineering
1. Transcription factor Zfx regulates tumor immune evasion | iScience (2025)
Role: CRISPR screen analysis (~160K sgRNAs), ChIP-seq, TCGA survival models
2. Transcriptional subtypes in lung adenocarcinoma | Clinical Cancer Research (2021)
Role: NMF subtype discovery, 113-gene PAM classifier (87-91% accuracy)
3. T cell-dependent bispecific therapy | Cancer Immunology Research (2024)
Role: NK cell RNA-seq, GSEA, pathway enrichment
📖 View All Publications on ORCID
We stay at the forefront of pharmaceutical bioinformatics trends:
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Status: Production-ready
Industry Evidence:
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Status: Mainstream
Industry Milestone:
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Status: Validated
Regulatory Landscape:
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Status: Production
Industry Impact:
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Szymon Myrta
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10+ Years in Pharma/Biotech
Core Competencies:
Languages: English (Fluent), Polish (Native) |
🤖 AI in Bioinformatics:
- LLM-assisted code generation & debugging
- AI-powered variant annotation
- Automated literature mining for pathway enrichment
- Prompt engineering best practices
🧬 Multi-Modal Omics:
- Spatial transcriptomics (10X Visium, Xenium)
- Single-cell + proteomics + epigenomics integration
- Multi-omic predictive modeling for precision medicine
🧪 Non-coding RNA:
- lncRNA, miRNA, circRNA in cancer & development
- Integration and correlation analysis (ncRNA ↔ mRNA)
- Regulatory network reconstruction
⚙️ Software Development:
- R package development (Bioconductor standards)
- Positron IDE + Quarto for literate programming
- Nextflow DSL2 + Wave containers for cloud scalability
- Git-based collaboration for reproducible science
🎯 CRISPR & Functional Genomics:
- Perturb-seq analysis pipelines
- Base/prime editor screen optimization
- Screen hit validation workflows
🏥 Precision Medicine:
- Real-time clinical decision support systems
- Pharmacogenomics + liquid biopsy integration
- Patient-specific therapy modeling| Advantage | Description |
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| ⚡ Speed | Established pipelines ensure rapid turnaround (RNA-seq: 2-4 weeks, scRNA-seq: 4-8 weeks) |
| 🏆 Quality | Pharma-grade standards from 9+ years at Roche/Genentech |
| 🤖 Modern | AI/LLM integration, Positron IDE, Quarto documentation, cutting-edge methods |
| 📚 Proven | 6 publications in top journals, 800+ patients analyzed, 160K sgRNAs processed |
| 🔬 Reproducible | Full GitHub repos, Docker containers, CI/CD, comprehensive documentation |
| ✅ Compliant | ISO experience, GxP-ready workflows, validated pipelines, audit trails |
| 🌐 Remote | 9+ years remote work experience, international teams, flexible time zones |
| 🤝 Collaborative | Contributing to pharmaverse, open-source first, knowledge sharing |
We're available for:
- 🧬 Contract NGS analysis projects (4-20 weeks)
- 📦 Custom R package development (4-12 weeks)
- ⚙️ Production pipeline engineering (4-12 weeks)
- 🤖 AI/ML integration consulting (6-16 weeks)
- 📊 Interactive Shiny dashboard creation (4-6 weeks)
- 📖 Publication support (methods, figures, analyses)
- 🎓 Training & workshops (R/Bioconductor, reproducible research)
Company Email: kontakt@actn3.pl
Personal Email: szymon.myrta@gmail.com
Response Time: Within 24 hours
⚡ ACTN3 Bioinformatics - Where Speed Meets Science
"Transforming genomic data into insights through reproducible pipelines and AI-powered workflows"
All public repositories are licensed under the MIT License unless otherwise specified.
⭐ If you find our work valuable, please star our repositories!
