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Wannabe a biologist? Better study math and computing, not Selfish Gene defense 400

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From msmash at Slashdot:

In the middle of a discussion about the pros and cons of statins, Sir Rory Collins, the head of clinical trials at Oxford University, noted that If you want a career in medicine these days you’re better off studying mathematics or computing than biology. More.

From Tom Feilden at BBC, a key issue is information science and cancer:

So why cancer? The answer can be summed up in two words: big data. What Dr Sottoriva brings to the fight against cancer is the expertise in mathematical modelling needed to mine the vast treasure trove of data the information revolution has brought to medicine.

“The exciting thing is that we can apply all the new analytical techniques we’ve developed in physics to biology,” he says.

“So we have all these new quantitative technologies that allow us to process an enormous amount of data, and all of a sudden we can start to apply that to implement the paradigm of physics in biology.” More.

Of course, always a fly in the ointment, right? There’s also the risk of “datageddon”:

The Professor of Science and Society at Arizona State University, Daniel Sarewitz, warns of “datageddon” – over-enthusiastic researchers risking being set adrift on a sea of irrelevant information.

“If mouse models are like looking for your keys under the streetlamp, big data is like looking for your keys all over the world just because you can,” says Professor Sarewitz.

See also: What to expect from the Royal Society’s public evolution summit November 7-9

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5 Replies to “Wannabe a biologist? Better study math and computing, not Selfish Gene defense 400

  1. 1
    Bob O'H says:

    Of course, one can study both: the Selfish Gene concept was developed mathematically.

    Anyone wanting to work in biology should really study both maths and biology. Or make sure you work with someone from the other end.

  2. 2
    bornagain77 says:

    I seriously don’t think Darwinists should EVER talk about mathematics since,,,
    #1 they do not even pay attention to what their own mathematics from population genetics is telling them about the inadequacies of their own theory
    #2 Darwinists have no rigid mathematical basis to test against, as other overarching theories of science have, so as to qualify their theory as a science instead of a pseudo-science
    #3 The applicability of mathematics is itself a ‘miracle’ that is inexplicable to the materialistic presuppositions of Darwinists

    Notes:

    #1

    the mathematics of population genetics is not kind to Darwinian claims in the least. Three devastating problems are revealed by population genetics. The Waiting Time problem, Natural selection is ineffective, and perception of reality itself is shown to become illusory. (July 2016)
    http://www.uncommondescent.com.....ent-613650

    #2

    “On the other hand, I disagree that Darwin’s theory is as `solid as any explanation in science.; Disagree? I regard the claim as preposterous. Quantum electrodynamics is accurate to thirteen or so decimal places; so, too, general relativity. A leaf trembling in the wrong way would suffice to shatter either theory. What can Darwinian theory offer in comparison?”
    – Berlinski, D., “A Scientific Scandal?: David Berlinski & Critics,” Commentary, July 8, 2003

    The main reason that Darwinian theory can offer nothing in comparison to quantum electrodynamics or general relativity is because it has no demarcation criteria based in mathematics to make it a testable theory like quantum electrodynamics and general relativity have a demarcation criteria based in math so as to make them testable and potentially falsifiable.

    Deeper into the Royal Society Evolution Paradigm Shift Meeting – 02/08/2016
    Suzan Mazur: Peter Saunders in his interview comments to me said that neo-Darwinism is not a theory, it’s a paradigm and the reason it’s not a theory is that it’s not falsifiable.
    http://www.huffingtonpost.com/.....84812.html
    Peter Saunders is Co-Director, Institute of Science in Society, London; Emeritus professor of Applied Mathematics, King’s College London.
    Peter Saunders has been applying mathematics in biology for over 40 years, in microbiology and physiology as well as in development and evolution. He has been a critic of neo-Darwinism for almost as long.

    read more here
    http://www.uncommondescent.com.....ent-614313

    #3

    The Unreasonable Effectiveness of Mathematics in the Natural Sciences – Eugene Wigner – 1960
    Excerpt: ,,certainly it is hard to believe that our reasoning power was brought, by Darwin’s process of natural selection, to the perfection which it seems to possess.,,,
    It is difficult to avoid the impression that a miracle confronts us here, quite comparable in its striking nature to the miracle that the human mind can string a thousand arguments together without getting itself into contradictions, or to the two miracles of the existence of laws of nature and of the human mind’s capacity to divine them.,,,
    The miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve. We should be grateful for it and hope that it will remain valid in future research and that it will extend, for better or for worse, to our pleasure, even though perhaps also to our bafflement, to wide branches of learning.
    http://www.dartmouth.edu/~matc.....igner.html

    “You find it strange that I consider the comprehensibility of the world (to the extent that we are authorized to speak of such a comprehensibility) as a miracle or as an eternal mystery. Well, a priori, one should expect a chaotic world, which cannot be grasped by the mind in any way .. the kind of order created by Newton’s theory of gravitation, for example, is wholly different. Even if a man proposes the axioms of the theory, the success of such a project presupposes a high degree of ordering of the objective world, and this could not be expected a priori. That is the ‘miracle’ which is constantly reinforced as our knowledge expands.”
    Albert Einstein – Letters to Solovine – New York, Philosophical Library, 1987

    “Either mathematics is too big for the human mind, or the human mind is more than a machine.”
    Kurt Gödel As quoted in Topoi : The Categorial Analysis of Logic (1979) by Robert Goldblatt, p. 13

    Mathematics and Physics – A Happy Coincidence? – William Lane Craig – video
    https://www.youtube.com/watch?v=BF25AA4dgGg

    1. If God did not exist the applicability of mathematics would be a happy coincidence.
    2. The applicability of mathematics is not a happy coincidence.
    3. Therefore, God exists.

  3. 3

    bornagain @ 2: You need to start your own speaking tour. Masterful.

  4. 4
    gpuccio says:

    Bob O’H:

    “Anyone wanting to work in biology should really study both maths and biology.”

    For once, I perfectly agree with you!

    And it’s not only math, but also methodology, information theory, programming, and so on.

    Of course, not every biologist can study all of that, but it is important that key figures, in particular bioinformaticians, be available for most research.

    That is true for medicine, too.

    “Or make sure you work with someone from the other end.”

    OK, but in my experience that does not always work well. There will always be the need of people who have a good education in both fields, otherwise proper communication can often be a problem.

  5. 5
    Dionisio says:

    gpuccio:
    “There will always be the need of people who have a good education in both fields, otherwise proper communication can often be a problem.”
    Agree. It’s like a translator between professionals who speak different languages and see things from different angles.
    Interdisciplinary research teams are becoming common these days. A while back News posted a reference to an Italian computer scientist who works at a cancer research center at a US university.
    But even biologists from different specialties may have differences in the areas they know well.

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