The rate of growth of biological data is tremendous and is going to accelerate even more as sequencing, collection and storage of data becomes cheaper. An interesting comparison is between rates of biological data growth and the number of bioinformaticians capable of processing/analyzing the data (see above). Even more importantly, who will connect all the dots and make biological sense of this?
Many researchers have no other option but to dump their research in the lap of a bioinformatician (or a team) and wait for results. However, bioinformaticians rarely deliver sufficient results right away, there are many variables and lots of the variability has to do with data generation and experiment planning…
So what is the solution? Sometimes the researchers need to have the right tools to “play around” with their own data. We are in a new age where all researchers must have the fundamentals of data analysis not only in theory but also in practice. Not only is this becoming possible, it is becoming critical so that the time and money spent on research generate deeper biological understanding.
From our experience, learning to use a “batch effects” reduction or PCA analysis “button” in a visual interface is easier for a researcher that collected the samples than for a bioinformatician to know everything about the biological problem that is being studied. So many times showing analysis results yields a familiar “oh, I know what happened!” from the researcher.
That is why our team is building a bioinformatics platform that will explain the principles for any researcher while doing the analysis itself. We hope to make a change in how data is being handled, analyzed and interpreted. Our goal is to provide every scientist, researcher and student with tools that will yield reliable, reproducible and meaningful results. One of the ways we see this becoming a reality is through a simple, clear and logical user interface,where every algorithm is explained with practical examples and references to publications.