A low hurdle to entry along with the ability to iterate rapidly is key to taking on problems & creating solutions. What do these solutions look like in genomics and why can hackers lead the way? Fig 1 shows something very similar to social interaction maps one comes across at places like Facebook.
The map above is of individual gene relationships where an algorithm began with 12 seed genes that previous experiments have shown to play a role in Alzheimer’s disease. These seeds were compared with 185 new candidate genes from regions deemed susceptible to carrying Alzheimer’s genes. From here, both experimental and computational data was combined to generate Fig 1, which the authors dubbed AD-PIN (Alzheimer’s Disease Protein Interaction Network).
What we learn by simply tracking genes already known to play a role in Alzheimer’s is the discovery of new regions of genetic code that are also participating in the expression of related functions, in this case those being affected by the disease, such as memory. In Fig 2 we see that between seeds this algorithm produced 7 high confidence interaction results, of which 3 were in common with previous studies. In addition to almost 200 new interactions, which can each lead to new therapies, blockbuster drugs and better understanding of the disease itself.
Many software developers have extensive experience and interest in dealing with large data sets, finding correlations and creating meaningful solutions. However, much of our generation has had little exposure to these problems. Often resulting in the bandwagon effect, as one recent article put it “the latest fucking location fucking based fucking mobile fucking app.” Progress has often been linked to literacy, from books to programming, being able to read and write in life-code just might be the next stage.