Machine Learning from Big Bad Data in Medicine and Biology of Aging

In this seminar I will briefly review some success stories of Machine Learning applied to bio-medical domain up to date and speculate on what it will take to enable a much more substantial progress. I will specifically discuss Biology of Aging – the field which remains most promising and most fraudulent over the thousands of years in history of medical sciences. I will present my own work and suggest where theoretical approaches and modeling can make a big difference in a search for anti-aging and rejuvenating interventions.

More information:

 A recent interview with Longevity Technology on Radically Open Science platform

    https://www.longevity.technology/a-better-model-organism-for-testing-antiaging-drugs/

An interview with Llifespan.io on the state of aging science, Peshkin’s approaches and Machine Learning for Biology of Aging

     https://www.lifespan.io/news/an-interview-with-dr-leonid-peshkin/

   A 3 min video on Daphnia as a novel model organism for aging:

     https://vimeo.com/386647406

A preprint on Smart Tanks platform
     https://www.biorxiv.org/content/10.1101/2021.05.30.446339v1

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IHES Covid-19 regulations:

– all the participants who will attend the event in person will have to keep their mask on in indoor spaces
and where the social distancing is not possible;
– speakers will be free to wear their mask or not at the moment of their talk if they feel more comfortable
without it;
– Up to 25 persons in the conference room, every participant will be asked to be able to provide a health pass
– Over 25 persons in the conference room, every participant will be asked to provide a health pass which will
be checked at the entrance of the conference room.

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