Thursday, January 14, 2021

 Hugh Duffy

Mr. Ippolito 

AP Biology

1/14/2021


Briggs, Helen. “One of Biology's Biggest Mysteries 'Largely Solved' by AI.” BBC News, BBC, 30 Nov. 2020, www.bbc.com/news/science-environment-55133972. 


Recently, an A.I. called AlphaFold accomplished something that was previously thought to be impossible. In labs, mapping proteins can be a long, painful process. This generally takes years to complete, and requires manual labor. With AlphaFold technology, the A.I. can map proteins at speeds far faster than humans. AlphaFold is so smart, that it actually teaches itself how to better map proteins, while mapping proteins. It is comparable to Tesla auto-driving vehicles, which collect data while driving autonomously. This data is sent to the headquarters, where the algorithm is adjusted and automatically updated. With this same technology being applied to scientific research, specifically biology, medicine can develop at rates we’ve never seen before. In the case of AlphaFold, being able to map a protein is just a day and can help scientists rapidly develop vaccines. Additionally, this mapping technology can help scientists develop artificial proteins, which would help those who have protein deficiencies. Mapping proteins can be extremely useful when fighting against new infectious diseases like Covid-19. “One example is Covid-19, where scientists have been studying how the spike protein on the surface of the Sars-CoV-2 virus interacts with receptors in human cells.” (Briggs 2)


I thought this article was well written, however it felt rushed and lacking in information. There really wasn’t anything that explained how AlphaFold was developed, or how it maps proteins to begin with. This article would have benefitted from more extensive research. Briggs mentions how scientists have yet to study how AlphaFold interacts with proteins that have bonded to other macromolecules, so this could be a possibility as to why the article lacks information. The technology is just too new. Overall, this article was very intriguing, and poses the question of what the future holds for A.I. in biology. 


1 comment:

  1. Angelinna Faisca
    Current Event #11


    Briggs, Helen. “One of Biology's Biggest Mysteries 'Largely Solved' by AI.” BBC News, BBC, 30 Nov. 2020, www.bbc.com/news/science-environment-55133972.

    https://bronxvilleapbiology.blogspot.com

    Hugh's review of Helen Briggs’ article was really informative in the way he gave details about this AI. First off, he starts off by giving examples of how long the process of mapping proteins can take, starting off with saying that mapping proteins can take years and takes a ton of hours to complete via humans, as it requires manual labor. Hugh also compares the collection of data as this A.I. maps proteins, as comparable to the Tesla car, which collects data as it drives around. Hugh then goes on to say that with the help of the A.I mapping proteins within the time span of a day, this can deeply affect the way vaccines are made and how fast they can be developed. Lastly, he finishes with saying how revolutionary the speed of mapping proteins can be with new A.I’s because with the speed that proteins are equipped, A.I’s can also produce artificial proteins that could help people with protein deficiencies, overall, this new A.I system can prove beneficial for future science.


    Hugh did a nice job explaining the article, but I think that he ended the first paragraph abruptly, with just a quote, and didn’t quite finish what he was explaining throughout the whole paragraph and I think that it just ruins the whole vibe of what Hugh was explaining. Other than that, I think he was very upfront about what he was talking about in the article and gave a good review of the main points that the article was focusing on and trying to convey towards the reader.

    This article was of importance to learn about because it gives a look into the breakthrough technology that will allow for new vaccines for common diseases, potentially finding proteins that could be used as place holders, and using this technology to help with experiments as well that have to do with proteins that would take scientists a long time compared to this new A.I.

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