Latch.bio

#Overview

Latch.bio is a bioinformatics data platform built around sequencing and analysis pipelines, with model inference and fine-tuning folded directly into those workflows. It is strongest when structure prediction or genomic language-model fine-tuning needs to sit alongside data management rather than run in isolation — so predictions and trained models land next to the sequencing data that produced them. Look here when you want hosted structure prediction and genomic-model fine-tuning inside a broader data pipeline.

#What you can run on Latch.bio

Latch.bio runs AlphaFold 2 for turnkey protein structure prediction: submit a sequence and get a predicted structure without configuring the pipeline yourself. For genomics it supports fine-tuning of Evo, a genomic language model, so you can adapt a DNA foundation model to your own sequencing data. Beyond these, the platform is extensible — arbitrary models and analysis pipelines can be registered and run through a Python SDK, letting teams bring their own tools into the same environment. Model weights are not distributed by Latch.bio; the emphasis is hosted execution and fine-tuning against your data.

#Running and fine-tuning models on Latch.bio

Access is through hosted execution inside the platform. AlphaFold 2 is available as a turnkey inference workflow for protein structure, while Evo is offered for genomic-language-model fine-tuning against your own sequences. The Python SDK is the extensibility layer: it lets computational teams register custom models and pipelines and run them next to their sequencing data. This fit suits labs and bioinformatics groups that want structure prediction and genomic-model fine-tuning integrated into data-heavy, reproducible pipelines rather than as one-off scripts.