Tag Archives: Computational Biology

Beyond the 2D Bounding Box: Why Bioimage Deep Learning Is a Completely Different Beast and How BiaPy Tames It

By Kemal | August 24, 2026

https://github.com/lynchaos/biapy-hub https://lynchaos-biapy-hub-app-hlcmfj.streamlit.app/ If you have spent your machine learning career optimizing ResNets or YOLO on ImageNet and COCO, here is an inconvenient truth: standard computer vision has spoiled you. In standard computer vision, a batch is usually an RGB triplet where . The pixels are isotropic, the spatial coordinates are Euclidean, the lighting is roughly… Read More: Beyond the 2D Bounding Box: Why Bioimage Deep Learning Is… »

Building a fake microscope: simulating a yeast wet mount

By Kemal | August 1, 2026

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Repository: github.com/lynchaos/generative-microscopy Why this sketch I wanted to find out whether I could make something that genuinely looked like microscopy footage. Not cells bouncing around a canvas, but Saccharomyces cerevisiae behaving the way it actually behaves under a coverslip, seen through real glass and real light. The sketch began life as a generic n-body attraction… Read More: Building a fake microscope: simulating a yeast wet mount »

I Built a Single-Cell RNA-seq Pipeline That Writes Its Own Report

By Kemal | June 7, 2026

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Single-cell RNA sequencing is one of those techniques that generates a huge amount of data and then demands a huge amount of effort to interpret it. You run the sequencer, get a matrix of 20,000 genes by several thousand cells, and then spend the next several days (or weeks) figuring out what’s in there. I… Read More: I Built a Single-Cell RNA-seq Pipeline That Writes Its Own… »

From Lab Bench to Browser: A Hybrid Digital Twin for CHO Cell Culture

By Kemal | May 30, 2026

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I rebuilt two published CHO cell-culture papers — a hybrid ODE + machine-learning growth model, and a genome-scale metabolic reduction pipeline — as an interactive digital twin that runs in the browser. Here’s how it works, what’s under the hood, and an honest take on what it’s good for. No hosted version yet; the code is on GitHub and a live instance is coming soon.

How I Built a Machine Learning Tool to Predict Drug Manufacturing Failures

By Kemal | January 25, 2026

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A bioprocess engineer’s journey into machine learning and why the pharmaceutical industry desperately needs this bridge When I tell people I work in bioprocess engineering, I usually get blank stares. When I explain that I help manufacture proteins in giant tanks for therapeutic use, the response is often: “Oh, like brewing beer?” Not quite. But… Read More: How I Built a Machine Learning Tool to Predict Drug… »