I'm a wet bench and computational biologist with 19+ years of experience in transcriptional regulation research, specializing in ChIP-seq and RNA-seq analysis. I develop tools and pipelines that transform raw sequencing data into biological insights.
🔬 Currently: Senior Research Assistant at University of Colorado
Anschutz, Bentley Lab
📍 Location: Denver, Colorado
📧 Contact:
Benjamin.Erickson@cuanschutz.edu
- Transcriptional regulation and RNA Polymerase II dynamics
- Nascent RNA sequencing (NETseq, BrUseq, ChIPseq)
- Alternative splicing and RNA processing
- Chromatin modifications and gene expression
Genomics & Bioinformatics:
ChIP-seq • RNA-seq • NET-seq • BRU-seq • Differential Expression • Peak Calling
Alternative Splicing • RNA Editing • Motif Analysis
Programming & Data Science:
Bioinformatics Tools:
STAR • Bowtie2 • samtools • bedtools • deepTools • MACS • HOMER
DESeq2 • rMATS • MAJIQ • Salmon • SUPPA • BBtools • Snakemake
🧰 BenTools
Custom R package for genomics data analysis and visualization. Functions for processing ChIP-seq and RNA-seq data with publication-quality plotting capabilities.
Key Features: Metagene plots • Coverage analysis • Custom genomic visualizations
Production-ready Snakemake workflows for processing sequencing data. Automated, reproducible pipelines from raw FASTQ to publication-ready results.
Technologies: Snakemake • Docker • Cluster computing
Interactive Shiny application for RNA-seq and ChIP-seq data exploration and visualization. Enables researchers to analyze data without programming knowledge.
Stack: R Shiny • ggplot2 • Interactive dashboards
Author on 19 peer-reviewed publications in high-impact journals including:
- Cell Reports (First Author, 2024)
- PNAS (2024, 2011)
- Genes & Development (First Author, 2018, 2022)
- Molecular Cell (2019, 2015, 2012)
- eLife (2024, 2022, 2021)
- Nature Structural & Molecular Biology (2011, 2010)
📖 View full publication list on Google Scholar
🔬 View profile on ResearchGate
- R Programming (Coursera)
- Getting and Cleaning Data (Coursera)
- Reproducible Research (Coursera)
- Interactive Programming in Python (Coursera)
"Transforming sequencing data into biological discoveries through computational innovation"