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Hi, I'm Mike đź‘‹

I am a bioinformatics scientist with a passion for making sense of complex omics data and uncovering meaningful patterns that help turn hypotheses into actionable insights. My background is rooted in next-gen sequencing technologies and data analysis which has allowed me to work across a multitude of omics data modalities—including spatial proteomics via imaging mass cytometry, spatial transcriptomics, single-cell ATAC/RNA-Seq, bulk RNA-Seq, and metagenomics. I love collaborating with bench scientists, helping them navigate their data, teaching them that bioinformatics is not scary, and learning about their research along the way. I also have experience debugging software, troubleshooting NGS workflows, and setting up reproducible pipelines through workflow management languages like Snakemake. When I’m not sifting through sequencing files or surfing the command line, you’ll probably find me in the gym putting up weights or playing the drums to my favorite nu-metal songs.

Mike Martinez headshot

Tech Stack

R and Snakemake are my daily drivers. I also ship in Bash and Python, with a focus on reproducibility, scalability, and clean reporting.
R logo R
Snakemake logo Snakemake
Bash logo Bash
Python logo Python

Highlighted Projects

RGenEDA

RGenRDA (R Package)

R package for reproducible exploratory data analysis for genomics data.

View on GitHub
SCOutR

SCoutR

R package of single cell preprocessing and plotting utility functions.

View on GitHub
Clover-Seq

Clover-Seq

Snakemake workflow for the analysis of tRNAs and smRNAs from high-throughput sequencing data.

View on GitHub
Targetted WES Pipeline

Targetted WES Pipeline

Snakemake workflow for the preprocessing and analysis of targetted whole exome sequencing (WES) data.

View on GitHub

Experience

Geisel logo

Research Scientist

Oct 2024 - Present

Geisel School of Medicine at Dartmouth - Center for Quantitative Biology

  • Developed reproducible Snakemake workflows for WES and bulk ATAC-Seq, reducing data-preprocessing time and allowing for increased scalability.
  • Supported Dartmouth researchers by developing boutique-analysis pipelines for tRNA-Seq and proprietary sequencing strategies.
  • Analyzed a wide range of projects for core clientele spanning Eukaryotic and prokaryotic genomics including scRNA and ATAC-seq, 10X spatial (visium and xenium), and MGX.
  • Created an R-package, RGenEDA, to ensure reproducible exploratory data analysis and reduce analysis times.
UConn Health logo

Clinical Research Technician I

Jun 2023 – Sept 2024

UConn Health Center - Department of Molecular Oncology

  • Spearheaded the design and implementation of computational methods in R for multi-omics studies including bulk RNA-Seq, 16S amplicon sequencing, and targeted metabolomics.
  • Utilized bash scripting on an HPC to automate bulk RNA-Seq preprocessing.
  • Conducted a full DEG/GSEA analysis of bulk colon tissue from Pirc rats to highlight the combinatorial effect of naproxen and EPA on colon cancer chemoprevention.
  • Analyzed colonic spatial immune architecture via multiplex imaging mass cytometry.
  • Generated effective and publication-quality figures using R, ggplot2 to easily communicate findings.
Intus Biosciences logo

Bioinformatics R&D Intern

Jun 2022 – Sept 2022

Intus Biosciences

  • Leveraged synthetic PacBio and ONT long reads as a standardized, ground-truth input to validate and benchmark proprietary microbiome clustering software.
  • Contributed to pipeline development through a series of custom R scripts to generate taxonomy call files.
UConn logo

Student Researcher

Sept 2021 – May 2023

Jonathan Klassen Lab (UConn MCB)

  • Managed LIMs database and deposition of raw sequencing reads to NCBI's SRA database.
  • Assembled and annotated bacterial genomes from Illumina MiSeq reads using SPAdes and Prokka.
  • Investigated fungal communities of T. septentrionalis fungus gardens to highlight ant symbiotic dynamics.

Education

M.S. | University of Connecticut | Microbial Systems Analysis
Advisors: Dr. Joerg Graf, Dr. Jonathan Klassen, Dr. Sarah Hird
May 2023
B.S. | University of Connecticut | Molecular and Cell Biology
Minor: Psychological Sciences
May 2021

Contact

If you have any questions or would like to collaborate, please email me.