Hi, I’m Dan Nasko, a multi-disciplined data scientist, particularly focused around microbial ecology, high-dimensional datasets, and experimental systems. “Distilling terabytes of data into meaningful insights” sounds like a catchy thing to say, but that’s a lot of what I do!

My goal is to demystify data science for biologists by designing analysis pipelines capable of generating meaningful and reproducible insights from ‘omics datasets. Data is good, metadata is great. Working closely with biologist to understand their systems and assumptions is critically important to downstream data analysis because it’s impossible to make biologically relevant conclusions from data without metadata and context.

I currently work and live in San Diego as a Senior Data Scientist at Novozymes A/S after my first start up, Biota Technology, was acquired by Novozymes in March 2021. Before that I was at the University of Maryland where I worked with: Todd Treangen (Rice University), Mihai Pop (UMD UMIACS), Krista Ternus (Signature Science), Don Milton (UMD SPH), and Amy Sapkota (UMD SPH).

And prior to all of that I was a PhD student in Eric Wommack and Shawn Polson’s Viral Ecology and Informatics Lab at the University of Delaware.

Experience

Biota Technology

Apr 2019 - Present

Senior Data Scientist

University of Maryland

Jul 2018 - Mar 2019

Assistant Research Scientist

University of Maryland

Jul 2017 - Jun 2018

Post-Doctoral Associate

University of Delaware

Jan 2011 - Jul 2017

Graduate Research Assistant

Accugenix, Inc

Dec 2008 - Jan 2011

Molecular Associate

Education

Ph.D. Bioinformatics and Systems Biology

Univeristy of Delaware

B.Sc. Pharmaceutical Product Development

West Chester University

Software

CASC

A CRISPR finding tool

CASC A’int Simply CRT

Rubble

Protein-protein BLAST-like tool

Rubble

Tools & technologies

  • AWS Services (e.g. EC2, RDS)

  • Nextflow

  • PostgreSQL

  • Bioinformatics applications – QIIME, BLAST, BWA, Bowtie, Samtools, PacBio® SMRT Analysis Software, CLC Genomics Workbench, MAFFT, MOTHUR, CD-HIT, USEARCH, MetaGene, de Bruijn graph and overlap consensus assemblers, Anvi-o, PhyML, Phylip, Jellyfish, Kraken, Cytoscape, BLAT, LAST.

  • General applications – Jupyter, LaTeX, Trello, Microsoft Word, Excel, Powerpoint, Adobe Illustrator.

Skills

  • Meta-*-Omics data analysis
  • Python
  • Unix
  • Parallel computing (e.g. Slurm, Torque PBS)

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