Denver N³
"Data never sleeps"
Computational biologist with a deep interest in utilizing bioinformatics tools to extract actionable intelligence from 'omics' data
Research Expertise
RNA-seq Analysis
Differential expression analysis, pathway enrichment, and transcriptomic data interpretation using DESeq2, edgeR, and custom pipelines.
Machine Learning
Applying ML algorithms to biological data, feature engineering for 'omics datasets, and predictive modeling for biological systems.
'Omics Data Integration
Multi-omics analysis, data harmonization, and systems biology approaches to understand complex biological phenomena.
Technical Skills
Programming
Python, R, Bash, Jupyter Notebooks, Git version control
Data Analysis
Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Plotly
Bioinformatics
Bioconductor, DESeq2, GSEA, Pathway analysis, Sequence analysis, Spatial Transcriptomics
Infrastructure
HPC clusters, Docker, Cloud computing, Pipeline automation
Featured Projects
Comprehensive collection of machine learning tutorials specifically designed for biological data analysis. Covers supervised and unsupervised learning techniques with practical bioinformatics applications.
End-to-end RNA-seq analysis pipeline from raw reads to biological insights. Includes quality control, alignment, differential expression, and pathway enrichment analysis.
Integration of Real world clinical data and transcriptomics data to identify biomarkers predictive of survival in colorectal cancer.
A basic SnakeMake pipeline for automated generation of annotated variants for downstream curation.
Denver Ncube, Ph.D.
Clinical Translational Scientist
Professional Experience
- Provided expert input on clinical studies incorporating Precision Medicine endpoints including transcriptomics, metabolomics, and proteomics
- Integrated RWD-RWE from EHR into transcriptomic analysis of phase 1-2a clinical trials in IBD
- Designed translational Statistical Analysis Plans for bulk and spatial transcriptomics
- Developed internal LLM-based repository using AWS Amazon Q for Business
- Led migration of data analysis pipelines to AWS cloud infrastructure
- Participated in RFP responses, project pricing, and bid defenses
- Review and interpret customer Aristotle Test reports
- Conduct personalized health consultations based on test results
- Developed CLIA validation protocol for the Aristotle test
- Implement high-end data analytics and AI-integrated solutions
- Developed custom pipelines for spatial transcriptomics data analysis adhering to CLIA/CAP guidelines
- Led analysis for 4 RUO and CLIA assay validations for custom oncology panels
- Implemented project tracking through HIVE, increasing turnaround time by 80%
- Optimized raw NGS data processing, reducing client delivery time by 60%
- Analyzed multi-omic data using network biology databases (PPI, GSEA, KEGG)
Technical Expertise
Bioinformatics & Data Analysis
- NGS data analysis with R, Python & Linux
- Single-cell and bulk RNAseq, WGS, WES
- Spatial transcriptomics (Nanostring GeoMx, 10X Visium)
- Multi-Omics data integration
- GATK, Samtools, Picard, vcf/bcf tools
Computational Tools
- Machine Learning (scikit-learn, rdkit)
- Cloud computing (AWS S3 and EC2)
- Pipeline development (NextFlow, Snakemake)
- CI/CD deployment
- R-Shiny app development
Education
Ph.D. in Biology (Neuroscience)
University of Oregon • Eugene, OR • 2021