What I'm wondering about the different approaches is if they could receive bigger breakthroughs by sharing / crowdsourcing their issues and getting a wider attraction / reach. E.g. sometimes the answers to a problem lie in another industry
Like e.g. the fold.it game helped decyphering the crystal structure of an AIDS causing virus in 10 days, while scientists were battling it for 15 years
https://www.youtube.com/watch?v=V48M5j-6zdE
and
https://www.youtube.com/watch?v=jbYgza4NNk8
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.
With statistical inference and probability, a system can provide a number of answers to questions. A crowdsourcing component can be used to rate the answers the system provides thereby allowing the system to learn via feedback loops.
Apply this to Life Sciences, molecular biology, genomics/proteomics and we may have a system intelligent enough to produce new hypothesis in the area of life extension research or a system intelligent enough to combine two pieces of knowledge to come up with something new, a discovery or series of discoveries.
I have some other ideas too, look me up at biomimic@gmail.com if you want to collaborate on these.