Why Is Bioinformatics Important In Genetic Research?

Genomics is a branch of genetics that studies large scale changes in genomes of organisms. Genomics and its subfield of transcriptomics, which studies genome-wide changes in the RNA that is transcribed from DNA, studies many genes are once. Genomics may also involve reading and aligning very long sequences of DNA or RNA. Analyzing and interpreting such large-scale, complex data requires the help of computers. The human mind, superb as it is, is incapable of handling this much information. Bioinformatics is a hybrid field that brings together the knowledge of biology and the knowledge of information science, which is a sub-field of computer science.

Genomes of organisms are very large. The human genome is estimated to have three billion base pairs that contain about 25,000 genes. For comparison, the fruit fly is estimated to have 165 billion base pairs that contain 13,000 genes. Additionally, a subfield of genomics called transcriptomics studies which genes, among the tens of thousands in an organism, are turned on or off at a given time, across multiple time points, and multiple experimental conditions at each time point. In other words, "omics" data contain vast amounts of information that the human mind cannot grasp without the help of computational methods in bioinformatics.

Bioinformatics is important to genetic research because genetic data has a context. The context is biology. Life forms have certain rules of behavior. The same applies to tissues and cells, genes and proteins. They interact in certain ways and regulate each other in certain ways. The large-scale, complex data that is generated in genomics wouldn't make sense without the contextual knowledge of how life forms work. The data generated by genomics might be analyzed by the same methods used by engineers and physicists who study financials markets and fiber optics, but analyzing the data in a way that makes sense requires knowledge of biology. Thus, bioinformatics became an invaluable hybrid field of knowledge.

Number crunching is a way of saying that one is doing calculations. Bioinformatics is able to crunch tens of thousands of numbers in a few minutes, depending on how fast the computer can process information. Omics research uses computers to run algorithms — mathematical calculations — on a large scale in order to find patterns in large data sets. Common algorithms include functions like hierarchical clustering (See Reference 3) and principal component analysis. Both are techniques to find relationships between samples that have many factors in them. This is similar to determining if certain ethnicities are more common between two sections in a phone book: last names that start with an A versus last names that start with a B.

Bioinformatics has made it possible to study how a system that has thousands of moving parts behaves at the level of all the parts moving at once. It is like watching a flock of birds fly in unison or a school of fish swim in unison. Previously, geneticists only studied one gene at a time. Though that approach still has an incredibly amount of merit and will continue to do so, bioinformatics has allowed for new discoveries to be made. Systems biology is an approach to studying a biological system by quantifying multiple moving parts, like studying the collective speed of different pockets of birds that are flying as one large, swerving flock.