Solving ageing from home with computational approaches | Prof Joao Pedro de Magalhaes

[@biogerontology7646]

26:00 re-watch and also look up guilt by association analysis.

[@biogerontology7646]

31:40 drugs and bioinformatics. Network pharmacology.

[@biogerontology7646]

33:50 machine learning

[@faradaycool4058]

Good work...reading from scripts

[@SombreEirenarch]

I always thought there was no well-regulated pathway of aging, and that it isn't quite a controlled process. While that might still be true, Pedro makes a very good point on how it *is* after all possible to crack the code (or codes) of aging even though aging itself might not be a straightforward pathway or process. After all, machine learning algorithms can see patterns where human minds cannot.

[@immortalityIMT]

Not to mention mutation rates correlation to lifespan

[@sandybayes]

It sounds like the field of biology needs to adopt an engineering perspective to help to understand how the components fit and work together and which components do not, Engineering models may serve to be helpful in determining relationships and roles os aging related genes and other influencers..I think it would make sense to create a team that includes several disciplines including engineering. Obviously more perspectives are needed to crack the aging code.

[@sandybayes]

I wonder if tesla's DoJo computer system would be useful in data analysis. I know it's more adapted for computer teaching/learning so may not be applicable.. I'm unsure what NeuroLink has in terms of computer data analysis. I just know that Elon Musk is adept at data analysis for all his businesses,