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  • Computational biology has boosted the progress of biology.

  • In less than a year, we have succeeded in understanding much of the biology of the Covid-19 virus.

  • Cell reprogramming and synthetic biology - two fields of computational biology - could allow science to cure diseases like Alzheimer's, osteoporosis or even to create blood.

Imagine that computers could create blood, transform fat cells into bone to cure osteoporosis, or even create a cell from scratch to give it a mission in our body.

This idea sounds crazy, but it could come true.

Computational (or digital) biology has made a technological leap in recent years, thanks to advances in artificial intelligence in particular, making it possible to envision things considered science fiction not so long ago.

Before getting to the heart of the matter, let's come back to this discipline which mixes computer programming and knowledge of living things.

Whenever a biology researcher needs tools to help him, computational biology provides him with models or software that will speed up his research.

In recent years, the understanding of living things has taken a turn.

AI makes unexpected things possible

Before the advent of high throughput sequencing in 2010, it took years and millions of dollars to sequence the genome of a new species.

For ten years or so, it has been possible to do this in a very short time and for a modest sum.

"This applies to the SARS-CoV-2 coronavirus," explains Hélène Touzet, research director at the CNRS.

In less than a year, we succeeded in establishing the genome of the virus and from there to understand much of its biology.

And artificial intelligence - more precisely machine learning - is no stranger to all of this.

Biology today is capable of producing much more observational data, in particular thanks to high-throughput sequencing.

And we know: the more data there is to feed the AI, the more efficient it is.

“It's like with facial recognition, once you've shown the machine a lot of faces, it will be able to distinguish a man from a woman, young from old, etc.

», Points out Martin Weigt, researcher in the department of computational and quantitative biology at the University Pierre and Marie Curie.

In biology, it's the same principle.

From observation, she will be able to predict rules and deduce behaviors.

Let's imagine: “I have to do a billion tests and each test takes two weeks, that's impossible,” points out Martin Weigt.

Now I do my computational biology analysis and [through modeling] say there are a hundred that might have a good probability of success.

Instead of a billion tests, I do 100 tests, and out of the 100, there are 10 that work ”.

If we understand how the processes work, we can consider reprogramming them.

Changing the mission of a cell

For now, computational biology is still moving forward a bit in the dark.

“If you imagine that a cell is a big bag full of molecules, then we know everything.

But the cell is not a bag of molecules, explains Martin Weigt.

The molecules interact with each other, one is a regulator of the other, and the other influences three others… We can only understand the cell if we have a vision of the collective behavior of all the components ”.

We already know a lot, but there is still a long way to go.

We know, for example, that it is possible to change the function of a cell.

In 2012, Shinya Yamanaka received the Nobel Prize for having successfully transformed a differentiated adult cell, skin for example, into an undifferentiated cell, or embryonic stem cell.

"We are looking for a set of genes to be disrupted which will make it possible to destabilize the cell so that it changes its mission," describes Loïc Paulevé, CNRS researcher in computational biology.

Depending on the conversions we want to make, we are still looking for the right cocktails of genes ”.

And computational biology is helping out in that area.

“We are developing programs that try to behave like cells,” continues the researcher.

Instead of doing real experiments, which require time and money, we experiment on the computer to suggest cocktails to then try in the laboratory ”.

The machine acts as a guide for researchers.

She is virtually looking for models and when there is one that works, you just have to try it out for real.

Because in the end, it is experience that will give the answer.

In the future, these technologies could make it possible to treat osteoporosis or Alzheimer's disease, for example, "by stimulating new brain cells", as Microsoft explains, very active on the subject through its Station B laboratory. could imagine generating new cells that the aging body can no longer produce or, in agriculture, making trees produce more fruit.

A future without disease

Is a future without disease and without famine possible?

Medicine and the food industry are in any case two privileged fields of application of computational biology.

“GMOs are a little the first signs of reprogramming, observes Loïc Paulevé.

When we do cell reprogramming, we encourage cells to take on the functions that interest us.

We can have finer control, without necessarily genetically modifying.

"

Find the Future (s) section here

The real step in the future is that of synthetic biology.

This branch of computational biology seeks to create a biological system from A to Z. "We are going to program a cell from zero", specifies the researcher.

“Instead of starting from existing cells, we are going to start from a cell that we built from a first program.

We will look at how it behaves and we will refine, details Loïc Paulevé.

There is still a lot of progress to be made from a computer and artificial intelligence point of view to build reliable models.

"

Ultimately, we could imagine introducing a cell into the body to search for pathologies and make a diagnosis.

Its mission could be to go and kill another, in the case of cancer, for example.

Illnesses will then only be a distant memory (well, maybe not tomorrow either).

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