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.
This also has a lot to do with content summarization, for example, take a look at the "fifty shades text generator" and http://genopharmix.com/TuataraSum/
Many things can be learned from what's inside Google, Apple, IBM patents. Learn from what inside patents. It's a great way to spark ideas as opposed to going in blind.
I would include recommendation systems based on 'human generated lists'. See: http://www.google.com/patents/US8108417 I have developed these and they are far more powerful and relevant to the subjective user tastes involved with light-weight approaches related to collaborative filtering. An ensemble approach is absolutely the best while also keeping in mind that one user might think they've struck gold in terms of a result while another may not - recommendation systems are highly subjective. However, we had 50mil MAUs and 250mil searches every month and found out that there are ways to get around that. Some are psychological, for example, some users do not want to be 'told' or recommended something by someone else much less an algorithm - they would rather 'Discover' something. This depends on the product context. Is the product space related to music, shoes, books, dates etc. Labeling your recommendations as 'discoveries' works better in some cases, it depends on the user context and the product context.
Everything is a recommendation engine. Mimicking the way humans recommend things to other humans/friends is the ultimate way to build algorithms and architecture for recommendation systems.
One more thing, never forget to include a great spellchecking system, it's icing on the cake here.
Of course we do. It's also a must. It's a requirement for any progress related to space travel and in relation to populating other planets. It's amazing that this is and still is, a question. The real question here is - does life have meaning or not?