Big Data

Machine Learning in Bioinformatics


Bioinformatics is a field of study that utilizes data science techniques to solve problems relative to biology, and more directly, the makeup of the human organism. In the past year, bioinformatics have been responsible for many advances in the fight against COVID-19. A silver lining of the pandemic is the amount of biological data the science community is able to gather, ultimately helping with preparation for future coronaviruses, and predictive analytics regarding information about how the disease was spread.

Utilizing a sector of artificial intelligence known as machine learning, data analysts working in bioinformatics are able to analyze enormous groupings of data that are provided by artificial intelligence that notices patterns and “learns” how a given virus (or other organism) works, ultimately providing information on how that organism may mutate or otherwise change. Relative to the COVID-19 virus, this machine learning has helped create vaccines that are expected to also work against mutations of the virus, as well as advances in preventative measures, both pharmaceutically, and physically.

Here is a look at 3 other ways bioinformatics and machine learning are working together to advance industries.

Bioimaging Analysis

Image analysis techniques in many fields have been greatly increased by artificial intelligence and data management, including healthcare and law enforcement. Bioimaging is a means of non-invasive imaging that aims to “interfere as little as possible with life processes.” It uses light, ultrasound, x-rays, magnetic resonance, and more to create the images, and as more an more data can be collected and shared, the information these bioimages provide can be submitted to memory and ultimately, via machine learning, can determine patterns in cellular processes, and generate images of what the next steps in the lifecycle of these organisms may be.


Proteins are similar to genes, in the sense that they are small organisms that are essential for life. Proteomics is the study of these proteins on a grand scale. In a given organism, a proteome is the name given to the entire set of proteins in that organism. The “grand scale” is referencing the part of the science that ties proteins from different organisms together, commonly used for preventative medicine.

With machine learning, the protein structure of organisms can be predicted as the organisms age, and the function of the proteins as they evolve, can also be predicted via artificial intelligence. The more data available on a given protein, the more comprehensive the machine learning is. Thus, there is a push within the proteomics community to share data.


Even though the lifespan of a human won’t be able to witness any evolution within their own species, it is something that is still occurring in human beings every single day. Where threats used to be cold, fire, or perhaps a lack of food, now one could perceive something like screen time as a threat to human health, and evolution relative to technology is slowly but surely occurring. Thanks to bioinformatics, predicting what kinds of evolution will occur in the human race is much, much easier, as a small sample set from the “now” can have its property changes predicted literally millions of years in the future. If you wanted the best estimate at what the human race will look like in 250,000 years, bioinformatics is a great bet.

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