Part 5 of 5. Four posts of reasons are enough. This one is about what it looks like when you actually use the thing, and about the name, which people ask about more often than they ask about normalization. Fair enough. One small note first. The command examples below use the usual command line options,… Read More: Using SimurgArray, and the bird behind the name »
Part 4 of 5. Right now SimurgArray lives in a private repository on my own Git server. It has a license, a changelog, a user guide, wheels, a Docker image and a version number that just became 2.0.0. In other words, it looks public. It is not, yet. Publishing code is easy. Publishing it responsibly… Read More: SimurgArray going public: what it takes, and a calendar »
Part 3 of 5. “Benefit to humanity” is a big phrase for a tool that mostly reads binary files. I will try to keep this post the right size. SimurgArray will not cure anything. What it can do is lower a few barriers that currently decide who gets to do genetics research and how much… Read More: SimurgArray: What good could it do? »
An end-to-end rare-disease variant triage platform: a Nextflow pipeline, three execution backends behind one API call, Terraform for two cloud tracks, and a phenotype-driven ranking measured against 10,178 published cases. Including the model metric that collapsed to exactly random once I removed the feature doing all the work.
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… »
A Raspberry Pi Zero 2 W paired with a Sense HAT V2 runs a fully self-contained, edge-native machine learning weather station with no cloud, GPU, or heavy ML frameworks. The system uses pure NumPy implementations of Recursive Least Squares, Kalman filtering, conformal prediction, and drift detection, staying under 150 MB RAM. The station continuously updates… Read More: I turned a Raspberry Pi into a tiny weather intelligence… »
A reproducible, cloud-scale reanalysis of five peer-reviewed studies on cellular aging, reprogramming, and rejuvenation, and an honest account of what survived contact with a shared pipeline.
A Python CLI tool that strips background noise from any video file using ML denoisers — while copying the video stream byte-for-byte. A 6 GB 4K file processes in minutes instead of hours.
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… »
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.