Available for collaborations & speaking

Luis Aguilera

Computational Biologist · Research Associate
Department of Biochemistry & Molecular Genetics, University of Colorado Anschutz Medical Campus

I develop open-source computational pipelines for live-cell single-molecule microscopy, stochastic modeling of gene expression, and bioinformatics, helping researchers extract quantitative insights from complex imaging and sequencing data.

Research focus
Single-molecule microscopy Live-cell imaging Gene expression modeling Stochastic biophysics Machine learning for biology Bioinformatics NGS & ctDNA Antibody design
Aurora, Colorado · USA PhD, Biomedical Engineering & Physics
01

Featured Projects

MicroLive demo video
Featured · Published 2026

MicroLive

A complete image processing toolkit for quantifying live-cell single-molecule microscopy. PyQt5-based GUI integrating Cellpose segmentation, TrackPy particle tracking, Big-FISH spot detection, and custom ML classifiers, from image loading to publication-ready analysis.

Bioinformatics Advances Python PyQt5 Microscopy Cellpose TrackPy
FISH cell segmentation
Research Tool

FISH Processing

Automated pipeline for Fluorescence In Situ Hybridization (FISH) image analysis. Uses Cellpose for cell segmentation and BIG-FISH (FISH-quant v2) for spot detection, counting, and intensity quantification across multiple color channels.

Python Jupyter FISH Cellpose Big-FISH Colab Ready
NGS variant calling pipeline overview
Bioinformatics Pipeline

NGS Biomarker Discovery Toolkit

NGS variant calling and digital PCR assay design for circulating tumor DNA analysis. Includes a production Nextflow pipeline for somatic variant detection (LoFreq, SnpEff, gnomAD filtering), automated ddPCR primer design, and droplet partitioning simulation for rare mutation detection.

Python Nextflow ctDNA Variant Calling ddPCR HPC Ready
rSNAPed simulated cell
Simulation Library

rSNAPed

RNA Sequence to NAscent Protein Experiment Designer. A library to simulate single-molecule gene expression experiments, generate simulated intensity translation spots, and test machine learning and computational pipelines.

Python Gene Expression Stochastic Models Colab Ready
6EQUJ5 game trailer
Creative · Game

6EQUJ5

A Python terminal-based deep-space receiver game. You are a rogue engineer operating from an abandoned analog radio observatory, scanning the sky along the hydrogen line and engaging in AI-driven dialogue with alien civilizations. Each has survived what you are currently facing: an Artificial Superintelligence. Inspired by the real 1977 Wow! signal.

Science Fiction Python Ollama / AI SETI Terminal Art
02

Research & Publications

2026

UTag, a cysteine-free thermostable tagging system for tracking single mRNA translation live

Aguilera LU, Chen S, Sears RM, Yarbro J, DeRoo J, Ogg HA, Geiss BJ, Stasevich TJ, Snow CD, Zhao N.
bioRxiv (Preprint)
2026

MicroLive: An Image Processing Toolkit for Quantifying Live-cell Single-Molecule Microscopy

Aguilera LU, Raymond WS, Sears RM, Nowling NL, Munsky B, Zhao N.
Bioinformatics Advances
2025

Methods in quantitative biology: from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expression

Aguilera LU, Weber LM, Ron E, King CR, Öcal K, Popinga A, Cook J, May MP, Raymond WS, Fox ZR, et al.
Physical Biology
2024

Sequential design of single-cell experiments to identify discrete stochastic models for gene expression

Cook J, Ron E, Svetlov D, Aguilera LU, Munsky B.
IEEE Conference on Decision and Control (CDC)
2023

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

Raymond WS, Ghaffari S, Aguilera LU, et al.
Frontiers in Cell and Developmental Biology
2020

Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells

Koch A, Aguilera LU, Morisaki T, Munsky B, Stasevich TJ.
Nature Structural & Molecular Biology
2019

Computational design and interpretation of live-cell, single-RNA translation experiments

Aguilera LU, Raymond W, Fox ZR, May M, Djokic E, Morisaki T, Stasevich TJ, Munsky B.
PLoS Computational Biology
2019

Live-cell single RNA imaging reveals bursts of translational frameshifting

Lyon K, Aguilera LU, Morisaki T, Munsky B, Stasevich TJ.
Molecular Cell

View full publication list on Google Scholar

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About

I am a Research Associate in the Department of Biochemistry and Molecular Genetics at the University of Colorado Anschutz Medical Campus. My work sits at the intersection of computational biology, biophysics, and software engineering, building tools and models that let researchers extract quantitative insights from single-molecule microscopy data.

My research combines live-cell imaging, stochastic modeling of gene expression, and machine-learning-driven image analysis. I develop open-source pipelines that automate everything from cell segmentation to particle tracking to translation dynamics quantification.

With a background spanning Mexico, Germany, and the United States, I am committed to inclusive mentorship and making quantitative biology accessible to diverse communities of students and researchers.

4+
Open-source tools
16
Publications
5+
Years teaching
3
Countries lived
04

Teaching & Mentorship

UQ-Bio Summer School

Co-founder and lead organizer of the Undergraduate Quantitative Biology (UQ-Bio) Summer School, an intensive program introducing students to computational modeling, microscopy analysis, and stochastic gene expression. Curriculum published in Physical Biology. The school emphasizes hands-on Python-based learning and is designed to be inclusive and accessible to students from diverse backgrounds.

UQ-Bio Website

Let's connect.

Open to collaborations, speaking invitations, and opportunities in computational biology and bioinformatics.