Machine learning has been used in various fields and businesses. Same has been implied ton the immunity system. Our immune response is more or less a machine-learning problem where in our body acts as a computer. With the aid of machine learning technologies, somewhat similar analysis has come to the surface.
As we know, the knowledge of immune system has helped the humans to know more about the immunity and the various diseases that the human body is capable to catch of. However it is indeed a very tough and near to impossible task to get to the core of immunity manually. With the advancement in technology, and the ability of machines to work wonders in the field of medical science and health care has made the tables turn.
The possibility of detection of carcinogenic traits have been brought in by the same.
The advancement for genomic techniques has helped in increasing the understanding of various diseases. A major challenge that existed in the previous times was to identify the responsible parasite and host. But, now, that gap has been bridged. Biologist and technological experts have come together to create machines to put out protein interaction networks between the parasite and the host. This makes the detection of the virus or bacteria far more easy hence enabling to detect which disease it is.
These data mining technologies have several characteristics like learning interaction with the environment. This allows them to have a better outlook with the internal systems. Secondly, they have a great memory, now, obviously, being a machine it is able to remember and recall the environment it interacts with. And the experiences that it deals with. The feature that follows this is it’s adaptivity. It’s ability to response to stimuli and understand the occurrences and respond to the stimuli accordingly. AIS has also been helpful in detecting patterns of viruses and hence helped in preventing the pathways of the virus to re enter.
With the help of these, various ability of cloning has become possible. We are able to understand complex behaviors of the immune system, including it’s way of working and division of labour.
Adaptive biologists came up with trackers for immune receptors. They focused on building relationship between receptors and antigens. And all of this was happening through these new built technology.
Roughly, each human genome is around 200GB and according to the experts, the informational content is way beyond human understanding and comprehension. Therefore, there was a definite need for artificial intelligence and data analysis. There are genetically programmed receptors that state various machine learning programmes.
Microsoft is one company that has established a firm name in this field. It uses algorithms that are or have been adapted for natural translation of the genomic information.
There is no doubt that humans have taken the immune system’s research to nother level manually, but. The stepping in of machine learning technologies have revolutionised the understanding, detection and adaptivity of it.