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Lembot_0003@lemmy.zip ⁨3⁩ ⁨weeks⁩ ago

• PM_ME_VINTAGE_30S@lemmy.sdf.org ⁨3⁩ ⁨weeks⁩ ago

  Humans are animals, and humans invented programming. Therefore, programming is applied biology.

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  • Lembot_0003@lemmy.zip ⁨3⁩ ⁨weeks⁩ ago

    Descart: What is an excellent time to be long dead and therefore not need to even think about this logical abomination of a sentence!

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• jol@discuss.tchncs.de ⁨3⁩ ⁨weeks⁩ ago

  Science researchers and students often spend a lot of their time doing statistical analysis, including using programming for that.

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• Peanutbjelly@sopuli.xyz ⁨3⁩ ⁨weeks⁩ ago

  Bayesian analysis of complex intelligent systems via friston’s free energy principle and active inference? Or machine learning?

  Personally love the stuff circling Michael Levin at tufts university. I could also imagine there’s a lot of unique model building in different biological/ecological niches.

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• Midnitte@beehaw.org ⁨3⁩ ⁨weeks⁩ ago

  lm(turtle_gender ~ temp, data = data_frame)

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  • friendly_ghost@beehaw.org ⁨3⁩ ⁨weeks⁩ ago

    The turtles are not safe from Python

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• propter_hog@hexbear.net ⁨3⁩ ⁨weeks⁩ ago

  Computational biology and ecology are a huge part of those fields. I work at a research lab (in computer science) and one of our sister labs is dedicated to environmental stuff and has mostly biologists and ecologists employed at it; a large part of the research they do involves supercomputing somehow, so we tend to partner with them a lot. As an example, modeling population growth or decline due to a change in the population’s environment is one such use of computing and statistics in biology and ecology.

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• rustydrd@sh.itjust.works ⁨3⁩ ⁨weeks⁩ ago

  Probably Python and R for statistical analysis, which is common nowadays in most empirical sciences.

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