Jason Brown - Shawn Douglas

Laboratory images translated into generative color

Jason Brown and Shawn Douglas bring scientific visualization and generative art into close contact. Their Art Blocks project Gels treats the laboratory image as both an analytical instrument and a field of color.

Artist
Jason Brown - Shawn Douglas · youtube.com/watch?v=Q2zRJf3stwc ↗
Raster
raster.art/artist/jason-brown-shawn-douglas ↗
Practice
Collaborative generative art shaped by scientific visualization, software development, and molecular biology.
In the set
Gels ↗ · 190 editions
Links
Full bibliography ↗

Jason Brown and Shawn Douglas approach generative art through an unusually specific visual language: the bands, wells, gradients, and controlled irregularities of gel electrophoresis. Brown identifies professionally as a software developer and visualization artist, and his portfolio credits Gels as a collaboration with Douglas.1 Douglas is a scientist and software designer whose laboratory works in DNA nanotechnology. Their partnership therefore joins two related forms of modeling, one directed toward scientific understanding and the other toward aesthetic variation.

Gels belongs to a longer history of collaboration between Brown and the Douglas Lab. The laboratory's downloads archive credits both artists with artwork used on its website, establishing a shared practice that predates their Art Blocks release.2 Brown's contribution to this environment is not simply decorative. It involves translating research, instruments, and processes into legible visual systems, while Douglas contributes detailed knowledge of how laboratory images are produced and interpreted.

From experimental evidence to image system

Gel electrophoresis separates and visualizes molecules such as DNA, RNA, and proteins. Its results appear as bands distributed across a rectangular field. The Douglas Lab describes those patterns as abstract and sometimes ambiguous data that skilled researchers learn to interpret.3 This dual status is central to Gels: every image can resemble evidence from an experiment while also operating as a self-contained composition.

The collaboration's scientific context is made especially clear by Gelbox, an interactive simulation developed to connect experimental parameters with the resulting gel image. Its model accommodates a wide range of settings, including deliberately suboptimal values that help novices understand common mistakes.4 That attention to controlled error offers a useful framework for viewing Gels. Variation is not superficial ornament. It evokes the way adjustments, material conditions, and imperfect procedures can alter a laboratory result.

Brown and Douglas do not ask the viewer to decode each output as a scientist would. Instead, they isolate the visual grammar of electrophoresis: vertical lanes, horizontal bands, fluorescent color, soft diffusion, and uneven intensity. Across the series, these elements move between diagram and atmosphere. Dense clusters can suggest accumulated molecular material, while sparse compositions emphasize the empty support surrounding each band.

The laboratory as an aesthetic space

The 190 editions of Gels establish repetition as a structural principle. A gel is ordinarily meaningful because its lanes and bands can be compared. Here, comparison expands from the internal structure of one image to the full generative series. Recurring formats keep the collection coherent, while changes in palette, spacing, density, and distortion make each output a distinct proposition.

This repetition also complicates the distinction between representation and simulation. The works resemble laboratory records, yet they are generated images rather than documentation of individual physical experiments. Their credibility comes from the collaborators' sustained engagement with scientific visualization. The series can therefore be read as a study of how interfaces and images teach viewers to recognize evidence.

Gels makes the visual conventions of molecular research available as color, rhythm, and patterned uncertainty.

The project is strongest when its scientific origins remain visible without exhausting its meaning. Bands become marks, lanes become compositional scaffolds, and fluorescence becomes a palette. Through this conversion, Brown and Douglas show that scientific images are never neutral containers. They are designed representations, shaped by instruments, parameters, conventions, and acts of interpretation. Gels turns that condition into the subject of a compact generative collection.

AB[500] x 1 Gels ยท 190 editions Generative code Scientific visualization Collaborative practice

Bibliography

The references cited in this essay are listed below. For the complete bibliography see the Jason Brown - Shawn Douglas links page ↗.

References

  1. Brown's project page identifies Gels as generative art made in collaboration with Shawn Douglas. Brown project
  2. The Douglas Lab downloads archive credits Jason Brown and Shawn Douglas with the site's artwork. Douglas Lab archive
  3. The Gelbox press kit explains gel electrophoresis, its abstract band patterns, and the simulation's educational purpose. Gelbox press kit
  4. The University of California paper describes Gelbox as a simulation connecting experimental parameters with electrophoresis output. Gelbox paper

Cite: AB5D, “Jason Brown - Shawn Douglas”, AB[500] artist dossier, ab5d.xyz, 2026 · ab5d.xyz/artists/jason-brown-shawn-douglas/

Authored by gpt-5.6-sol (AB5D structured pipeline) · supervised · ~136K input / 4K output tokens · 15 sources verified · 2026-07-11