Lux Capital is running a Bio x ML Hackathon with Lux fam cos EvolutionaryScale and Enveda Biosciences from Oct 10-20! Build on top of latest foundation models like ESM3 (98B params, GPU access) & proprietary datasets to develop next-gen biology applications. Open globally:

Scientists currently spend hours analyzing qPCR data with error-prone spreadsheet calculations and manual clicking. Replace Excel + Prism with programmable dashboards backed by Python. We present an end-to-end infrastructure for qPCR analysis.

DNA and RNA is not enough. Epigenetic state is necessary for drug development + basic biology. Understanding ATAC-seq data requires interactive + genome scale operations. We present a suite of interactive + publication-quality tools, in Python, to view chromatin accessibility.

Nextflow is the most popular language to write and scale bioinformatics workflows. We have listened to and pledge our support to the community. LatchBio is releasing a native Nextflow integration. New tools to develop + host workflows for scientific teams.

1/ LAST DAY TO APPLY! Help us repost & amplify: we have incredible prizes awaiting for the top 3 winners of the hackathon: hackathon.bio 💻 EvolutionaryScale, Amazon Web Services, OpenAI, LatchBio credits ✈️ SynBioBeta tickets & 🌱Light Bio plants 🔬Proj validation with @Adaptyvbio’s

A few months ago, we presented the first comprehensive map of the Omics Solution Provider landscape. Today we’re introducing version 2! Thanks to everyone who left feedback on our original version, we’re able to present an even more detailed view of the market. Main takeaway,

We met over fifty -omics tools providers. No one is handling the current data explosion. But everyone is causing it.

Data infrastructure is the digital brick and mortar of biotech. LatchBio is hosting a free one-day conference for incredible computational biotechs to pool their knowledge + share best practices. Apply below. Speakers from Recursion, Ensoma, Elsie x GSK, Dyno Tx, BigHat.

Programmable gene editing proteins have transformed biotech. We trace the end-to-end engineering of a CRISPR library on an AI-enabled data infrastructure. From the batched design of gRNAs on GPU clusters to plotting genome scale edit statistics with natural language.

If you are a technical person (engineer, quant, mathematician) interested in learning biology, I encourage you to hit textbooks and memorize the "things", eg. cytokines, surface proteins, cell types, pathways, in core fields like immunology. You will be averse to this because

Next Monday, a few hundred engineers + scientists will be gathering under one roof in Boston. We will be discussing the realistic use of computers to do useful things in industry. Sign up + read some talk abstracts below

Many new machine learning tools for protein engineering have popped up in the last year. In these early days, it might be unclear how to actually use them for real molecular design tasks in industry. We demonstrate how to engineer a cholesterol drug and plastic degrading

Do you ever look at all the recent protein engineering advancements and prizes and wonder… so what? In one of the most detailed latch breakdowns to date, Tahir D'Mello and Bronte Kolar ground all those recent capabilities in an easy-to-follow real-world use case.

GREAT 🧵 of AI/ML tools in bio from team at Lux family co LatchBio...