Crunch Lab Secures $5 Million to Enhance AI Intelligence Layer for Decentralized Systems Crunch Lab has successfully raised $5 million in a funding round aimed at enhancing AI intelligence for decentralized systems. This investment will facilitate rapid growth in various enterprises.

Crunch Lab Secures $5 Million to Enhance AI Intelligence Layer for Decentralized Systems #United_States #New_York #Galaxy_Ventures #Crunch_Lab #CrunchDAO

Leaderboard for the autoimmune disease challenge #3. There are two accepted submissions: "enzo / hello" [which I assume is a hello-world-type submission test] and "mute-david / myceliboot" [which is my submission]

#CrunchDAO I appear to be the only person who has submitted a valid non-test submission to the server so far. Maybe others have had similar problems with local testing and getting the output format correct.

I need to review 3 other submissions; so hopefully others will submit before the deadline.

#CrunchDAO After boostrapping, the most consistently-differentiating gene was MGAM2:

"Predicted to enable alpha-1,4-glucosidase activity.... Diseases associated with MGAM2 include Anal Canal Squamous Cell Carcinoma and Sucrase-Isomaltase Deficiency, Congenital."

Seems like a reasonable pick.

#CrunchDAO Top gene for dysplasia vs non-dysplasia by a basic non-bootstrapped chi-squared test (OLFM4):

"The encoded protein is an antiapoptotic factor that promotes tumor growth and is an extracellular matrix glycoprotein that facilitates cell adhesion."

I'll call that a sanity-check pass.

This #CrunchDAO thingy is frustrating me because I'm unfamiliar with using Python for single cell analysis. If I had the data in R, I'd be able to process and summarise it in an hour or so.

I want something that functions like tapply(countData, status, sum), and am currently doing a double for-loop