The embrace of modern scientific research during the past century by most members of society has been enviable. Most people now understand the value of conducting high-quality scientific research, and how science can improve their everyday lives. Biology funding, for example, in many major countries have generally followed an ever-increasing trend over the past century. Many universities and biotech companies now employ and conduct biological research on an ever-expanding scale.
In conjunction with this expanded interest in biological and biomedical research, with the general aim of improving people's health, also comes some new issues to handle. Since the number of people currently employed in performing biological research has much expanded, for example, the amount of people required to properly train young, new scientists to a highly competent level is unfortunately still lacking. Since being trained as a biology scientist requires a high amount of dedication, time, and effort, many new scientists simply have not been afforded such attention by their more accomplished supervisors or experienced scientists. This inadequate training, of course, is not just limited to biology, but across the spectrum of the sciences, including physics, chemistry, geology, astronomy, or computer science. In biology, it is especially acute due to the complicated nature of the science that is often unpredictable even with the best of mathematical formulas, computers, or algorithms. Hence, a lot of time, energy, and resources are wasted when performing biological experiments since there is a lot of guesswork involved.
One simple way to quickly and easily overcome this inefficiency when conducting biological experiments it therefore to apply a more established method that is generally known to work when conducting experiments in a field as complex as biology. Taking a systemmatic approach when performing biological experiments is therefore one such established method.
Taking a systemmatic approach means to go through each of the possible variables, and just sequentially try them out. Perhaps the most famous and pivotal of these experiments came with the highly-anticipated Human Genome Project, completed in the last decade or two. In the Human Genome Project, for example, people sequence each gene in the human body in turn so that the entire human genome is essentially sequenced. The data generated is highly useful for subsequent gene or protein sequence analysis. Therefore, instead of randomly choosing genes to sequence, which may inadvertently be replicated unknowingly by scientists who may not be collaborating with each other, this comprehensive approach also minimizes a lot of resource overlap. This experimental approach of sequencing the entire genome with the Human Genome Project has also been applied successfully to other genomes such as the mouse genome, genomes of other model animals, and of microorganisms.
My recent idea proposed on the Human Structome Project also attempts to tackle biological experiments on a more systemmatic scale. Recent proteomic advances can also be used. These proteomics systems can incorporate tandem MS/MS mass spectrometry by sequencing all known proteins in a physiological mixture, such as a tryptic digest from a brain homogenate for example, which would give much information about the composition of all the proteins in the particular sample studied.
Of course, these projects don't need to be conducted on a super large scale. For example, when I was in graduate school, we were looking for interaction partners for my protein. We tried numerous proteins, that didn't work. After many failed attempts, we finally decided that we could systemmatically try other classes of macromolecules (since there were only essentially 3 other classes of macromolecules besides proteins). For example, we could try lipids, and we could try carbohydrates. We finally found that the protein that I studied was a lectin, binding to carbohydrates.
Taking a systemmatic approach to performing experiments during biology research is therefore a good way to systemmatically solve many outstanding biology problems. Other methods of scientific discovery such as surrendipitous discovery by random chance, would still be necessary. Nevertheless, this type of a systemmatic approach would often save much time, and speed up the scientific discovery process in biology research, and thus be a major tool for biological scientists in their arsenal of methods to understand the biological universe in which we are all immersed.
