Matt Ralston

Matt Ralston

M.Sc. Bioinfo + 5 years industry exp. - - - Currently writing a DNA sequence alignment, quasi-mapper, and graph algorithm and manuscript (for bioRxiv). I play math rock on my guitar, I write open-source software on GitHub, I pay my bills in the DE-NJ-PA tri-state area near Delco, and I'm launching a DE-based LLC for Univ. of Delaware and local NGS sequencing projects.

5+ yrs. professional

“The scientific method is like a bicycle: you can go somewhere on it if you want to, but it’s not really the sort of thing you can just play around with.”

  • Terry Pratchett

About Me

Target audience: scientists, engineers, managers, and academic partners

Seeking a dynamic addition to your team? I bring 5 years of industry biopharmaceutical R&D team experience coupled with a decade of experience in wet-bench biology, Linux, and data analysis with Python/Perl/R. Let’s elevate your projects together!

About the author

Do you consider cultural values, communication style, productivity, and dedication in your decision to hire new talent? Do you require a professional adept at communicating in-between diverse disciplines?

Do you need to know something more specific about my laboratory experience, software projects, data_science experience, industry experience, or coding proficiencies? Use the links here or on the main page/sitemap to find out more.

Industry experience

Wet-bench Molecular Biology and Biochemistry

I have worked in a variety of laboratory settings including analytical chemistry, organic synthesis, molecular biology and disease physiology research, translational oncology labs with patient tissue samples, extreme anaerobic and BSL-2 microbiolgy aseptic culture, and much more. In addition to laminar-flow hoods and GLP environments, I am familiar with a wide range of instrumentation and bioassay designs. I have worked with qRT-PCR, immunological assays, immunofluorescence, Northern/Western blots, HPLC, GC/LC-MS, UV-VIS and more. Please see the skills section for specific details and a list of known lab protocols.

I keep a good laboratory notebook, I can run experiments independently if sample quality is off (e.g. RIN score), and I deeply enjoy performing molecular assays at the bench, whether its microbiology, human or mammalian pathology and physiology, or otherwise. I am organized and detail oriented with a focus on replicate quality and understanding instrument limitations, positive controls, and core goals of hypothesis testing and data modeling.

If you’re looking for someone who can aliquot 1uL to instrument tolerance, or who can run a multi-factor experiment or bioassay from innoculation through sample preparation and instrumental analysis, I’m your guy.

Science and computation meets software development and agile teams

I primarily work in GNU/Linux environments on biological sequence analysis and Illumina short-read WGS/WES/RNAseq problems. I have many years of experience writing Python, Perl, R, Javascript, HTML/CSS, SQL, bash, and more recently, a little bit of Rust.

My projects have included technologies such as kubernetes code, Dockerized workflows, shell scripts for HPC environments and grid engines like UGE/SGE and SLURM. I can build MVC/MVVC web applications and I studied database systems (SQL) at the graduate level.

I specialize in writing command-line interface (CLI) tools including languages like Python, Perl, R, NodeJS, and more recently, some Rust. Nvidia CUDA GPU programming and distributed environments are an additional strength for applications requiring excessive parallelism.

Also, my experience with web applications, Javascript/HTML/CSS, front-end frameworks (mostly Alpine.js, React, Jquery, Jquery-UI, D3.js, and SVG), REST-API design, and database architecture lets me create strong tools for developers and scientists alike.

Specific research experience stories are given below.

  • Developed robust backend systems using Python, NodeJS, and R to streamline data processing workflows.
  • Demonstrated excellence in laboratory skillsets with replicate correlation coefficients > 95% on Illumina HiSeq 2500 RNA-Seq libraries.
  • Implemented cloud infrastructure on AWS, leveraging services such as EC2, S3, and Lambda for scalable and cost-effective solutions.
  • Containerized applications and workflows using Docker and Kubernetes (k8s), ensuring consistency across development, testing, and production environments.
  • Utilized Linux command line tools, including bash, grep, and sed, for data manipulation and system administration tasks.
  • Designed and implemented interactive data visualizations using D3.js, enhancing data-driven decision-making processes.
  • Scripted automation tasks in Perl and Python to optimize repetitive processes, reducing manual effort by 40%.
  • Managed document preparation and typesetting using LaTeX for high-quality technical documentation.

Training

Univ. of Delaware B.Sc. Biochemistry and M.Sc. Bioinformatics and Computational Biology (3.96 GPA)

Undergraduate program

I developed laboratory fundamentals as a wet-bench laboratory biochemist and molecular biologist. I learned aseptic culture, some immunological, and fluorescent assay techniques, and RT-PCR in a translational cancer laboratory. The UD chemistry department emphasized other laboratory fundamentals such as HPLC, GC-MS, spectrometry, and organic synthesis.

Subects studied include organic, phyical and biological chemistries, molecular biology, genetics, physiology, microbiology, virology, physics, linear algebra, probability, calc I/II/III and more.

Graduate program

My thesis was hybrid wet-lab and dry-lab 2-year project developing the first strand-specific Illumina NGS map of the C. acetobutylicum transcriptome during solventogensis and sporulation stresses. Owing of course the help of my advisors Drs. Papoutsakis and Venkataramanan, I investigated the whole-transcriptome response of a biofuel-producing bacterium to the biophysical stresses of solvent/biofuel accumulation and associated stress-response adaptations in anaerobic fermentation conditions. I formulated a fixed media, prepared the bioreactors and innocula, sampled across time points for small molecule characterization by HPLC, RNA-quality investigation, subsequent PCR-mediated Illumina HiSeq 2500 library prepration, and delivered my samples to the Delaware Biotech. Institute core for sequencing.

Afterwards, I developed both genome browser and interactive volcano-plot visualization web-applications for assessing differential expression of transcripts across the time-stress design.

Subjects included in my graduate program include metabolic engineering, bioinformatics, computational biology, database systems, algorithm topics, sequence alignment, Illumina NGS, biostatistics, Linux HPC training, web application development, Perl, Python and bourne shell (bash) programming.

Skills

My skillsets fall into four categories:

Wet laboratory skills

  • Laboratory sciences major (biology and chemistry specialization BSc. Biochemistry, UD ‘12)

I have core competencies in laboratory skills, soft skills related to team organization and responsibility and relevant course work covering [molecular biology, human and mammalian genomics, mammalian physiology, microorganism genomics (bacterial, viral) metagenomics and phylogenomics, biofuels and cell culture bioreactor,] process optimization, [novel methodologies and protocols, Illumina RNA-seq library preparation, qRT-PCR, RT-PCR, PAGE: Western blot, Northern blot, ELISA, HPLC, nucleic acid extraction, enzymatic treatment], FACS, [light microscopy, fluorescence microscopy, immunohistochemistry, immunofluorescence, gene knockdown, cloning,] bioassay development, and additionally [media formulation, contaminant testing and detection], [technical and software expertise], [GLP, ELN], and additional undergraduate lab and bioscience, [natural sciences, undergraduate mathematics, probability, statistics, molecular diversity], [data standards and reporting, technical writing, trends and conventions in biodata archiving]. Skills listed above in brackets indicate genuine industry experiences and/or experience at a professional level.

Spectrometry: UV-Vis, Fluorometry, Nanodrop, MS methods… some training related to tandem MS and flux modeling.

Cell culture: Human/mammalian cell culture, anaerobic bacterial cell culture, fermentation,

Engineering skills

  • Computer science major (masters of science in Comptuer Science, concentration in bioinformatics, 3.96 GPA, UD ‘15)

  • Bioinformatics

Sequence alignment: Hisat2, Bowtie2, Tophat, BWA, Blast, Blat, ClustalO, HMMs

Assembly: Cufflinks, Trinity, Velvet

Illumina data processing: Fastqc, Samtools, Picard, Bedtools

Miscellaneous: Tuxedo suite, samtools, DEseq, limma, Circos, PFAM, David

  • Software development

Cloud and containers: Amazon Web Services (AWS), Docker, OCI, k8s

Programming: Python, R, Bash, Javascript/NodeJS, Rust, Emacs, D3.js, Julia, Perl, awk, grep/sed, LaTeX, Matlab, HTML/CSS, MySQL, Oracle, PostgreSQL, miniconda

Data Management: Oracle SQL, PostgreSQL, rdflib, snapshotting

Cloud Computing: S3, Elastic Compute (EC2), CodeBuild, Elastic Container Repository (ECR), Elastic Container Service (ECS), Docker, IAM, Azure/GCP/AWS k8s

Networking: Slurm, Sun Gride Engine (SGE/UGE), firewalld, iptables, tmux, nixos

Systems Administration: systemd, Docker, Ansible/chef, tmux, Nginx, Apache, web servers, Sun Grid Engine (SGE/UGE), bash, parallel

  • Statistics and data science

Statistics: Hypothesis testing, ANOVA/regression, distribution fitting, R/Rstudio/Rshiny, Bioconductor, discrete/continuous probability, multivariate statistical analysis, regression, least-squares estimation, PCA, clustering, classification, normalization, regularization, variance reduction, naive Bayes, random forest, XGBoost,

Dimensionality reduction: PCA/SVD, Uniform Manifold Approximation and Projection (UMAP), t-SNE, canonical correlation analysis,

Optimizers: Gradient descent, simplex, particle swarm, simulated annealing, self-organizing maps, others.

Kernels: kernel trick, linear programming, matrix math, linear algebra, abstract algebra, discrete math

Maching learning: perceptron, SVM, PCA, UMAP, t-SNE, DNN, RNN, recurrence relations, linear regression and formal OLS-family assumptions and caveats, SAS programming, R programming, Python programming

Data Science: Python programming, numpy, pandas, staticly-typed compiled languages (rustc/cargo, zig, Typescript, Scala/Java/Clojure, C extensions in Python and R), RAII, CUDA, Cython, anaconda, apline linux, Docker, k8s

Team skills

  • Culture:

With good recommendations from industry managers, I’ve delivered value on projects within integrated teams of laboratory scientists, programmers, engineers, and managers on projects in wet-bench biology, bioinformatic and cheminformatic research areas. I take statistics, data, and modeling efforts seriously and I encourage you to check out the my /software page, the /research page, my life sciences message at /biosciences, my inactive profile on LinkedIn, and my manager testimonials section and perhaps my modest publicly facing GitHub and /portfolio page. I hope that you’ll see I have some familiarity with publishing and I write usable and effective documentation, literate programming, and reproducibilty reports and analyses. I boast 3-5 modest open source genomics projects concerning sequence alignment conceptural understanding, molecular species and diversity, correlation analyses, k-mer and minimizer expertise, Illumina data profiling, and I am not too opinionated about preferences execpting my engineering training, my scientific and code development process, and my R&D process.

  • Communication:

With proficiencies in technical writing, science, engineering, and stats/probability/mathematics, I’ve delivered value and knowledge to others without losing touch. Your high-value team demands written style and know-how in publications, meetings, and documentation. Clear and compelling written style is essential to today’s business successes, tomorrow’s publications, and our quarterly progress. Check out the publications or testimonials sections for more reasons why I’m a just above an ordinarily spectacular fit for your business needs.

Who am I?

I’m Matt Ralston and I’m a data science, scientific computing, devops, and knowledge-economy professional. If you want to get to know me, please check out the various topics you can find throughout my website on the /about me page.

Matt in a nutshell

I work in groups of engineers, analysts, and wet-bench laboratory professionals, team leads, associate directors, and alike. I listen to as many voices as I can, and I share my experiences with others; I am detail oriented and I enjoy the problem solving process, and I can discuss your needs in a variety of ways going forwards.

    • has soft skills, style and brevity in communication
    • track-record and wide technical expertise in engineering, chemistry, biology and genomics, bioinformatics, and Illumina WGS/WES/RNAseq/metagenomics
    • knowledge of agile methodology
    • system design mindset: design, benchmarking and testing
    • cloud-native and Docker containers

Go-to menu | statements considered harmful

Life science specialty

And, so, I do wet-laboratory science as well. I’m effecient and effective and timely in the lab. Asepsis leads to less errors, and as a bench molecular biologist I’m familiar with the autoclave and where the imaging equipment is. I can perform single-gene targetted expression studies (sometimes referred to as qPCR or rt-PCR on mRNA molecules. I also work with Illumina lab reagent kit technologies).

Disclaimer and software licensing

I am certainly not an expert at modeling, data-processing, and visualization techniques such as R, Cython/Python, Javascript, Linux/bash, Docker, AWS/cloud and more. But It’s more than just websites, APIs, numbers and figures here; my strong fundamentals and data-driven design strategy have been employted towares diverse goals in industry: hypothesis generation, key-questions and KPIs, application or integration needs, and more, such that my products are reproducibile, documented, and clearly written. I can adapt to your team.

I am familiar with open source standards, commercial licensing and procurement, software licenses, and EULAs.

And god willing I do multiplex in the lab and on the computer.

I have some conceptual familiarity with a lot of different methods from chemical analytical, bioassay, immunoassay, fluorimetry, MS, GC-MS, LC-MS, ELISA, and an intimate understanding of cell culture and laminar flow hoods.

My last acura was an Illumina but my last published report was validations of Northerns and novel lnc-RNAs, antisense RNAs, RNAi, and Illumina transcriptomics with strand-specific protocols.

Communications and Documentation

I work independently with consistent email and Slack communications, and project updates and logging via Version Control and git. My project management software is often plain text, also git-based, metrics, org-files for Pandoc compatibility, second-brain, markdown where possible, license documents, source files and configurations, Dockerfiles where possible, and I write LaTeX primarily in .Rmd.

Committed to continuous learning and staying updated with the latest advancements in these fields, my breadth of knowledge allows me to model, program, and problem solve in engineering teams. With my natural science knowledge I can ask intelligent questions about variables and covariates, treatment conditions, and their effects in your experimental design. I write clearly in technical and team messaging.

I have stylistic Javascript and UI/UX ecosystem and preference set and functional and OOP style knowledge. I can write CSS/HTMX, and I can build web apps in any language. I’m very partial to having a static asset stack where possible, Nginx, and I like Github Pages and Jekyll CMS. Most of my content is Markdown, plain-text, and org-mode when it’s not software projects.

That being said, most of my technical reporting is LaTeX, Pandoc, and Rmarkdown for scientific documentation.

I use Sphinx and Markdown for most simple code-and-a-story literate programming.

I am no stranger to Flask, FastAPI, Dask, OpenMPI, LAPACK, Tableau, Jupyter, and other standard app-and-reporting codebase trends and ease-of-use and lifetime centric development.

I’ve worked in Agile teams and I am familiar with scrum, sprints, stories and other development team concepts.

I’ve used Slack, Skype, and Atlassian distributed-team software and I am consistent on issues tracking, reporting, kanban, application lifetime management suggestions, and of course version control and repository feng-shui.

GTD/Productivity mindset

Productivity is a modest topic for discussion and I find it enjoyable because you see others perspectives on engineering concerns, assumptions, testing needs, Blue-Green workflows, Red-team and Green-team development, and of course GTD methods when you’re with new colleagues and their perspectives.

Regarding task and time management

My workflow centers on the README.md, software usage patterns and documentation, Sphinx, Oxygen, and Pandoc documentation, literate programming, org-mode, and Emacs.

I use the zed editor, PyCharm, Emacs and vi, tmux, and the bash shell for my development environment and I focus heavily on commit messsages, gitflow, rebase/merge/squash source tree design, and I use plain text and org-mode to create and manage my TODO lists and organize information in a Pandoc compatible way.

My task and time management largely revolves in Atlassian and Github kanban and issue tracking systems. I also can use Emacs functionality to perform clock-ins on tasks and git to manage versions of documentation and code, in source trees, to perform time estimates and prototype cost estimation.

I am flexible regarding your task and time tracking and coding requirements speicified by your org chart and PM guidelines.

Software for backend and server code vs UI and UX

I use Rmarkdown and Python for most of my direct data science stack. I use Python SQLAlchemy, Flask, and Rust ORMs and RDBMS technologies to create normalized data structures during ETL. My experience in scale-up and cloud deployment was largely driven by internal protocols and reporting, lift-and-shift deployments, cloud-native or vendor-specific cloud stacks such as AWS, GCP, and Azure. My ETL code is mostly Python, numpy, CUDA, and/or rust where I get the time to develop robustly and comfortably at my knowledge of static type function signatures and handling types robustly with GPT4.0-o1-mini in zed or Claude Sonnet 3.5+ mobile to assist with code when needed.

I use minimal software stacks and don’t do much UI development, but I’m no stranger to Javascript and CSS frameworks. I don’t use Vue.js or Next or Nuxt or MEAN or MERN in most of my app programming. I’m just not a front end guy, I like systems that allow me to look at large sets of variables in a flexible way w.r.t. number of samples and necessary EDA and diagnostic outputs.

I’m a backend programmer and ETL and Data Science are my most accomplished skillset in terms of what I can do. But often, you’ll want a ‘full-stack developer’ in the classical sense too.

Closing remarks on team skills

With five years in industry bioinformatics and software engineering teams I have expertise in essential knowledge-economy skills of time-management, project management, public speaking, and the technical accumen needed to deliver value for your team.

I have some knowledge:

With deep and well-rounded expertise in molecular biology, genetics, data analytics, and statistics, I have affected several teams and their publications, screening methods, and more. My team oriented style begins with a fundamentals first approach to discussing expertimental or analytical concerns with the Principal Investigator. When artifacts or biophysical aspects of assay design require special treatment, my backgorund in chemistry, biology, mathematics, and data analytics allows me to quickly integrate suggestions from team members into the analytical process, such as filtering bad leads or integrating additional knowledge for specific cases within large datasets.

Contact

Do you want to connect?

If you have a research question or you would like to discuss wet-bench, software, or bioinformatics please let me know.

If you are a recruiter please provide a location, time-frame to hire, and a full job description as plain-text in an email to my gmail.

If you are an interviewer and would like to schedule a phone or zoom interview, please copy and paste the following text into your email.

name: Jane Doe
email: jane.doe@example.com
company: Example dot com
department: Data engineering
subject: I'd like to contact you about the following opportunity
date: Date (- of opportunity)
time: time of interview
description: A description of the position or opportunity you'd like to disclose to me.
question: Key questions I should address in my response 
kpi: What are your indicators of whether or not this is successful, like a successful interview shedule by a certain date. A fee range you'd like to remain within. What makes our relationship successful and how may I discuss details more

Contact me

Please direct business and research related inquiries to my personal email addresses found on my CV/resume and website.

mralston.development@gmail.com

Please use my business gmail address for general inquiry.

For inquiry about opportunities, grant details please email me at my bioinformatics and coding gmail address: professional.bio.coder@gmail.com

For collaboration and or questions about research

Please use my professional.bio.coder@gmail.com gmail address.

Testimonials

When asked for references, I’ve received the following from former managers.

Anonymous

Whatever you need, big guy.

Anonymous, former boss and mentor

Of course. Any time. You don’t even need to ask.