We are all encouraged to live a healthy lifestyle to avoid potentially life-threatening diseases. Exercising and good dietary habits make a big difference in maintaining our health.
However, for some diseases, our cells carry important information that can alter this equation. It is estimated that the cells in our body have about 30 thousand genes. The information they encode tells each cell how to behave within our body.
For example, a particular gene might determine the eye color of a person; another gene might tell a cell that it should become heart tissue; and yet another could be in charge of producing insulin in our body. However, sometimes these genes can be mutated, causing the gene to be either nonfunctional or functioning with a different behavior. These mutations have been found to cause some of the most challenging diseases.
“Personalized Medicine” is a nascent field that tailors diagnosis and treatment to a patient by analyzing their clinical and genomic information. This is where bioinformaticians are assisting clinicians to achieve better diagnosis, treatments and clinical outcomes. Computer algorithms are a crucial part in this process, since human researchers cannot process the vast amount of information and interactions in the genomic data.
Algorithms can take into consideration a wide range of variables, including clinical signs and symptoms, laboratory data, and information from the DNA, such as the functioning of genes. They combine this information from a wide selection of people to come up with a model that can predict reasonably well the presence of a given disease. The rationale for this is to allow computers to ‘learn from past experiences’, and progressively gather data to improve upon their decisions.