Cynthia Kenyon: Experiments that hint of longer lives

AI applied to understanding the hidden relationships linking epigentics and extending human lifespan via algorithmically engineered diet, nutrition and longevity genomics: The precedent: Laura Deming: Making a business out of fighting the ills of aging link Cynthia Kenyon: Experiments that hint of longer lives (Cynthia now works at Google's Calico Labs) ▶ this video Now connect this: Nutrigenomics, Epigenetics, and Stress Tolerance link Now combine with: What is Epigenetics? with Nessa Carey The last 10mins are very important, in particular minute 35:06 link Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span - Blei DM1, Franks K, Jordan MI, Mian IS. - link Combining the worlds variants of pattern recogition, machine learning and AI with data associated to epigentic and standard genomic experiments and information, we should be able to discover hidden relationships that will enable advancement in extending human lifespan. Revenue is something we'll need to focus on and that may come in the form of consumer applications that algorithmically engineer their epigenome with data from companies like 23andMe, Navigenics, Ubiome etc. connected to Nutrigenomics including plant compounds, phytochemicals mapped all the way to the consumer through foods connected to apps connected shopping and recipe experiences. Finally connect to CRISPR and Gene Therapy Jennifer Doudna, inventor of CRISPR: We can now edit o

Were almost near the starting line with research and companies like Human Longevity, CalicoLabs(Google,Genentech), GenoPharmix, Buck Institute, SENS Foundation and this: Cynthia Kenyon: Experiments that hint of longer ▶ this video Epigentics and extending human lifespan: link

See: ▶ this video and link To name some of the top roadblocks: - Cellular garbage collection - Inner-workings of Mitochondria and cell death/apoptosis at the wrong time. - DNA repair genes - Telomerase production/use Analyzing genomic pathways associated to these is key. Understanding why the expression of genes varies or decreases/increases at the wrong time is also key. Being able to use Cogntive computing/biomicry/AI/Machine Learning etc to analyze the hidden connections and relationships between phytochemicals, genes, proteins, pathways and environment is the next frontier. We're working on it and could certainly use additional crowdsourcing approaches.

link link link link link See also: ▶ this video and link To name some of the top roadblocks: - Cellular garbage collection - Inner-workings of Mitochondria and cell death/apoptosis at the wrong time. - DNA repair genes - Telomerase production/use Analyzing genomic pathways associated to these is key. Understanding why the expression of genes varies or decreases/increases at the wrong time is also key. Being able to use Cogntive computing/biomicry/AI/Machine Learning etc to analyze the hidden connections and relationships between phytochemicals, genes, proteins, pathways and environment is the next frontier. We're working on it and could certainly use additional crowdsourcing approaches.