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AI Could Crack The Biological Language of Cancer and Alzheimer’s


Scientists have found, powerful algorithms used by Amazon, Facebook, and Netflix can ‘predict’ the biological language of cancer and neurodegenerative diseases like — Alzheimer’s.

Big data produced during decades of research was fed into a computer language model to see if AI can make further advanced discoveries than humans.

St John’s College, University of Cambridge, discovered the machine-learning technology could decipher the ‘biological language’ of cancer, Alzheimer’s, and other neurodegenerative diseases.

Their study has been published on April 8, 2021, in the scientific journal PNAS.

“Bringing machine-learning technology into research into neurodegenerative diseases and cancer is an absolute game-changer. Ultimately, the aim will be to use AI to develop targeted drugs to dramatically ease symptoms or to prevent dementia from happening at all.”

Every time Facebook suggests someone befriend or Netflix recommends a series to watch, Every time Netflix recommends a series to watch or Facebook suggests someone befriend, the platforms are using powerful machine-learning algorithms to make profoundly educated guesses about what people will do next.

Voice assistants like — Google, Alexa, and Siri can even recognize individual people and instantly ‘talk’ back to you.

Dr. Kadi Liis Saar, first author of the paper and a Research Fellow at St John’s College, used similar machine-learning technology to train a large-scale language model to see what happens when something goes wrong with proteins inside the body to cause disease.

“The human body is home to 1000s and 1000s of proteins and scientists don’t yet know the function of many of them. We asked for a neural network-based language model to learn the language of proteins,” She said.

“We specifically asked the program to learn the language of shapeshifting biomolecular condensates – droplets of proteins found in cells – that scientists really need to understand to crack the language of biological function and malfunction that cause cancer and neurodegenerative diseases like Alzheimer’s. We found it could learn, without being explicitly told, what scientists have already discovered about the language of proteins over decades of research.”

Proteins are huge, complex molecules that play numerous critical roles in the body. They do most of the work in cells and are required for the structure, function, and regulation of the body’s tissues and organs – antibodies, for instance, are a protein that functions to ensure the body.

Alzheimer’s, Huntington’s and Parkinson’s diseases are 3 of the most common neurodegenerative diseases, yet researchers accept there are a few hundred.

In Alzheimer’s disease, which affects fifty million individuals around the world, proteins go rogue, form clumps, and kill healthy nerve cells. A healthy brain has a quality control system that effectively disposes of these potentially dangerous masses of proteins, known as aggregates.

Researchers currently think that some disordered proteins also form liquid-like droplets of proteins called condensates that don’t have a membrane and merge freely with each other. Unlike protein aggregates which are irreversible, protein condensates can form and reform and are often compared to blobs of shapeshifting wax in lava lamps.

Professor Knowles said: “Protein condensates have recently attracted a lot of attention in the scientific world because they control key events in the cell such as gene expression – how our DNA is converted into proteins – and protein synthesis – how the cells make proteins.

“Any defects connected with these protein droplets can lead to diseases such as cancer. This is why bringing natural language processing technology into research into the molecular origins of protein malfunction is vital if we want to be able to correct the grammatical mistakes inside cells that cause disease.”

Dr. Saar said: “We fed the algorithm all of the data held on the known proteins so it could learn and predict the language of proteins in the same way these models learn about human language and how WhatsApp knows how to suggest words for you to use.

“Then we were able to ask it about the specific grammar that leads only some proteins to form condensates inside cells. It is a very challenging problem and unlocking it will help us learn the rules of the language of disease.”

Machine-learning technology is developing at a rapid pace due to the growing availability of data, increased computing power, and technical advances which have created more powerful algorithms.

Further use of machine learning could transform future cancer and neurodegenerative disease research. Discoveries could be made beyond what scientists currently already know and speculate about diseases and potentially even beyond what the human brain can understand without the help of machine learning.

Dr. Saar explained: “Machine-learning can be free of the limitations of what researchers think are the targets for scientific exploration and it will mean new connections will be found that we have not even conceived of yet. It is really very exciting indeed.”

The network developed has now been made freely available to researchers around the world to enable advances to be worked on by more scientists.


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