Interested in the interface of cutting-edge ML, product management, and biotech data factories? We're hiring someone to lead product vision, roadmap, and execution for our ML Platform insitro, working with Tom Stocky jobs.lever.co/Insitro/6f0996…

Thrilled to finally share a new partnership we've been very excited about insitro, where we'll be deploying an ML-powered multi-modal search tool to help accelerate the work of researchers accessing Genomics England datasets: businesswire.com/news/home/2022…

Data Science workflows at insitro: using redun on AWS Batch and AWS Glue Part 1: aws.amazon.com/blogs/hpc/data… Part 2: aws.amazon.com/blogs/hpc/how-…

I have always enjoyed my conversations with the smart folks at insitro. In this post, Matt Rasmussen talks about their data science workflows that run on AWS Batch. aws.amazon.com/blogs/hpc/data…

I was today years old when I found out that Dirichlet was co-advised by Poisson, Fourier, and Gauss. Dream team or Nightmare team for advising?

Enjoyed attending #NHSGenomics2022 this week, especially hearing from Daphne Koller, Professor Dame Sue Hill and Amanda Pritchard. Exciting to see all the clinical genomics innovations from NHS Genomic Medicine Service.

Thrilled to be speaking at National Cancer Institute summit on AI Approaches for cancer research, sharing some of our team's recent work on using learned embeddings for multi-modal clinical data inference. Register for free here: events.cancer.gov/aiwg/ai_imperf…

Excited to see Dave Deriso’s DTW library released - I got to test an early version of this for aligning functional genomic data several years ago, and was blown away by the speed improvements compared to conventional DTW.

Had a lot of fun sharing some of our team’s work using multi-modal ML in Oncology and Metabolism at the EMBL-EBI summit yesterday:

Excited to see this work from insitro colleagues out in the wild, highlighting potential pitfalls of conducting GWAS on traits that are ratios (eg, BMI, waist-hip, etc). biorxiv.org/content/10.110…

(1/3) insitro is excited to share our paper “EmbedGEM: A Framework to Evaluate the Utility of Embeddings for Genetic Discovery,” focusing on assessing the use of ML-derived embeddings for genetic discovery using heritability & relevance to specific diseases.