Tag Archives: biology

Hydra Video! Links and comic, too

I just posted a Video about Hydra and Humanized Organisms. A long, strange train of thought resulted in this comic, too. Art credit goes to Snowman – I love it.

I got to thinking about humanized organisms while I was reading about hydra. Hydra make good models to study the biology of aging because they seem to be immortal: they don’t seem to age at all. If we knew how they accomplished it, it might help us understand how to slow aging. How do we know that they don’t age?

Prof. Daniel Martinez observed groups of hydra for years. He carefully fed them and kept them in separate tubes. Each one was observed making buds – little baby hydra – but the old hydra was put into a fresh tube alone every time. The researchers waited for any of them to get old and die… and none did. Well, maybe they didn’t wait long enough? We can only compare them to other creatures in the same weight class.

Longevity tracks body size and time to first offspring. So orcas (weight 1 million grams, first offspring at 25 years) live far longer than voles (weight 10 grams, first offspring within a few weeks of birth). Hydra weigh in at a fraction of a gram and have their first offspring a few days after being born. But they are still alive and reproducing for years, thousands of times longer than the trend would predict.

What allows hydra to accomplish this? How do they regenerate? What’s special about their stem cells that they don’t deplete? Can we study hydra in a way that’s relevant to human longevity?

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MATLab and Biology

I made a bold prediction today. I predicted that Biology, as a discipline, would adopt MATLab as its computing environment. That may have been overstating things, but still, here’s why I think so:


1. Marketing: There are plenty of development environments out there. I’m looking at this from the perspective of a non-programmer. And non-programmers think in terms of “what program do I have to buy to do this?”

Anybody can code in a text editor in C and compile with a free compiler. But it’s not a complete development environment with a box, a price tag, and a user-friendly GUI. Biologists won’t use it. In terms of a packaged development environment, there’s MS Visual Studio, Mathematica, MATLab, Maple, Mathcad and some Open Source projects like SAGE.

2. Function Library. I’ve played with all of those but Maple. In terms of large, pre-made scientific funciton libraries, Mathematica and MATLab come out ahead. And they have a similar learning curve.

3. Math. Mathematica definitely has its advantages. But I don’t think that biologists think in terms of solving boundary value problems symbolically. They think more in terms of Finite Element simulations. Discrete math. That leans toward MATLab.

4. Social network. I suspect that the biologists will turn to their biochemist, chemist and engineer friends for adivce on computing, and they will hear MATLab overwhelmingly. I doubt they will go to
the physicists and mathematicians, where they might hear more about Mathematica.

OK, so MATLab’s the way of the future… what can you do with MATLab?

You can do everything that Excel does (including much nicer graphing options). Plus you can analyze images, spectra, or any other data. Most importantly, when you’ve gone to all that trouble, you can apply it as a loop to other inputs.

Take this for instance. Say you have a fluorescence image of cells. You go to all the trouble of figuring out three data values from that image. Maybe you measure cell count, average cell area, average cell fluorescence brightness. The trouble is that you probably have 100 images. Or you would like to in order to have a publishable result. That will take forever. If you “train” your PC to do that with MATLab, you can just run the program on a whole directory of images and have it spit the results out as an Excel file (if you insist on using Excel). Or a nice graph (it will look better if MATLab makes it).Or you can make a little GUI for your friends. I worked out how to do that in about 3 hours. Next time, 15 minutes.

Quantification is the future, and it is now.