Cienciaes.com: Bio in silico. | Science Podcast

2021-02-25 18:58:56

The computerization of biology and the generation of artificial life within a computer already has a long history. Jorge Laborda wrote on this subject two decades ago and, he said then, that biology and mathematics do not seem to get along. At least not as well as chemistry and physics do with them. However, advances in knowledge in computing and biology have led to a more intense interaction between biology, mathematics and computing, thanks to which many interesting properties of systems have been simulated, such as the origin of life, the functioning of of neural networks, aspects of embryogenesis, etc. However, the advances in the interaction between biology and informatics, although they have opened up a deep knowledge in many fields, in others, the expectations are still far from being fulfilled and proof of this is in the difficulties we have to face situations such as the pandemic. current.

Here is a small sample of what Jorge Laborda wrote two decades ago:

“Apart from the fascination of being able to simulate some aspects of the complexity of living things on a computer, the importance of this discipline is its capacity for virtual experimentation and also its power of prediction. We cannot design a real experiment on the evolution of species, because it would take millions of years, but we can do it on a computer. The results of these simulation experiments allow us to draw conclusions or formulate hypotheses about the functioning of living systems that would otherwise have been impossible. This subject is so fascinating that years ago it was shown that, in a universe of artificial life, made up of the so-called cellular automata, computers could be built capable, in turn, of simulating the very system that had created them.

Where computers and mathematics have to lend a hand to molecular biologists is undoubtedly in understanding genetic networks. Helping us from the analogy with an engine, in it the parts interact with each other, generating what we could call mechanical or electromechanical networks. In the same way that an engine is made up of devices that work independently of each other, but integrate as a whole, biologists are confident that the same is true of genes. These, it is believed, interact in subgroups thus originating the various mechanisms that make up the cell and the organism. We hope that these individual mechanisms can be studied separately from each other, which will greatly facilitate the understanding of how living things work, which would otherwise be impossible.

This suggests that these genetic networks that integrate individual biological mechanisms do indeed exist and may be discovered, analyzed and simulated in the future. On the other hand, it adds a very important factor: the power of prediction. Physics has been characterized by this particularity, but not biology. Many physical models predicted the existence of phenomena or particles that were later verified experimentally. Biology is now heading down that path as well.”

Now, two decades later, it is true that there have been important developments for the understanding of genetic networks and what has come to be called the “interactome”, that is, the interactions between proteins that are produced by genes, and progress continues in this matter. However, if advances in bioinformatics had been as intense as previously thought, it is clear that the genetic networks that make up all systems in living cells would have been dissected and perhaps understood today. These are the same genetic networks and mechanisms that viruses use to reproduce, therefore it would have been desirable that bioinformatics could have acquired enough knowledge to intervene effectively in the genetic networks that viruses, such as the new coronavirus SARS-Cov-2, used to cause death, pain and poverty. Thus, it would have been possible to intervene on these networks and prevent their reproduction or transmission, or at least through rapidly designed drugs or other methods.

Works by Jorge Laborda.

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