A few days back, we asked “We Have Six Interesting Bioinformatics Puzzles, Any Takers?” and a number of you contacted us. We finally managed to write up the biological part and email you the first puzzle, along with a list of others. Please get in touch, if you have not received the mail yet.
What are we trying to achieve?
The purpose of these puzzles
In recent years, many smart computer scientists entered the field of bioinformatics, being attracted by NGS large-data problems. Due to lack of exposure to biology, they tend to focus on a set of mainstream questions, such as k-mer counting, genome assembly, transcriptome assembly, etc. On the other hand, biologists have many interesting questions, but addressing them needs a bit of introduction to biology. Moreover, many of those subproblems experience the same scalability issues as genome assembly or transcriptome assembly due to nextgen sequencing.
Lack of knowledge of biology is not an insurmountable difficulty and the puzzles are designed to help computer scientists go over that barrier. Each puzzle is designed to answer a biological question that is likely un-addressed in the era of NGS. We took time to explain the biological context and anticipate that once the reader makes some effort in understanding it, he will find the bioinformatics part relatively easy to solve.
We believe the outcome of this effort will be something publishable, but even if it is not, the exposure will help readers find closely related publishable questions in related areas. It is important to be exposed to as many fun problems like these as possible so that when the reader has a new computational tool, he can easily port it to answer a non-mainstream question.
Why are they called ‘puzzles’?
We believe each problem is fairly easy to solve after the biological part is understood. No guarantees however.
With these puzzles, we are also planning to try a new publishing model. In this, we will quickly solve the puzzles, ask some scientists to openly review the work and then post the paper+review in arxiv or bioRxiv.