Machine Learning in BioScience

The Horizons of application of engineering applied to Biosciences is expanding regularly. Interdisciplinary sciences are moving ahead by applying basics of physics, computing sciences and mathematics to living systems. The more we move deeper into the understanding of living systems, the closer we are to understanding the mysteries of life.

The miracle of machine learning can be applied to predict a lot of biological phenomena- chiefly that in genetic engineering. We know by default that evolution was a process that took place by chance, and with the knowledge of machine learning applied to Genetics, we can replicate that.

Machine learning involves the use of algorithms to program the computer to learn on its own. This property can be successfully used to predict genomic mutations and their related diseases in humans. It can also be used to predict stable mutations, which would lead to evolution- which otherwise won’t be feasible to be predicted in a real life time scale since evolutionary processes occur over periods of billions of years.

With machine learning, we can make the computers work on random crossing overs, and predict the results accordingly. If by chance factor, any one of the crossings over products become genetically more stable, it would result in the formation of a stable chromosome, and hence would result in the evolution of a new progeny.

Another very important aspect could be the detection of genetic mutations, and hence aiding in treatment. This could be a great prospect, since genetic disorders often go untreated, and it causes havoc often. If corrected and repaired, the patient may revert back to original conditions. Machine learning can detect unknown genetic aberrations and repair them as and according to needs.

Other than genetic uses, another possible use could be in that of Immunology. Tuberculosis is one particular disease, where, the varieties of antigens produced are different from patient to patient, meaning that a wide variety of antigens are being produced from one particular bacterium. It is hence impossible to create a specific vaccine, because of this variety in immunogens. Machine learning can intervene here and can help design antibodies specific to each antigen, by learning and adapting itself to the technology. Incurable diseases can be absolutely cured, and this would be a remarkable discovery.

The application of machine learning can be vast in Biology related systems only that we need to recognize the potential of the problem that we are facing, and the plausible solutions after application of this advanced technology.

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