Ask HN: Getting started in biology with a software background

The trick is interpreting it and putting it into context. A paper will report the results of one specific experiment, and it’s very rarely exactly what you want. Understanding how a result will generalize to other conditions is tricky, even for experts: there are tons of weird feedback loops, unusual dynamics, and other traps for the unwary (plus badly designed experiments and the occasional legit Type I error). For example, doubling the amount of a substance almost never doubles its effect, and in some cases, the effects aren’t even monotonic: ~75% alcohol, for example, is a much better disinfectant than 50 or 100%.

With time—-and lots of paper-reading, you do eventually develop a sense for what factors might matter and how you could check.

Exact

1) The use of materials is totally different

Computer programming is a stuf that uses reciclable electricity and "eating your own dog food" kind programs, cheap to produce or free to copy, easily available and in many cases free except by the hardware (Hardware that can be hired, "clouded" or increased gradually).

You don't need to pay a dime for using R, C, Perl or Python and you can obtain the four, ready to use in your computer in less than a half hour. If you need a microscope, there is not an equivalent open source stuff replacement available.

In Biology the matherials will be sold to you only in packages of 10 Kg each pigment, with a caducity date, even when you would need to mix just 10 grams of each one. The spendable one-use only stuff is not free and the price for a single kit is incredible. You will pay it in any case because is indispensable for validating your work and you plan to use 500 of those kits the next year so you are a captive client from this company (that could decide to stop selling you if you try a way to lower the price, and will sue you if you try to copy the formula and make the product by yourself).

2) Documentation is not free and obtaining it is time consuming

In computer programming, you dont need to spent weeks to be delivered to you, or plan a travel to Peru to collect samples of a plant virus. You don't need to spend days just to reach the documentation navigating a miriad of closed or pay per viewed journals, at 50 dollars to peek in each paper.

You can expect to learn something and use it for years. Fortran is still there. You can program automatically your computer to make a hundred of safety copies each working day. In biology you can not clone your amazonian beetles collection, is unique and will be atacked and reduced to dust by real bugs from day one if you do not protect it.

3) There is not an obvious, linear path to success

Errors are random events that you can't always control

In biology you will lose eight months of your research because your samples travelling from Swedden to Madrid end somehow stuck in a Lithuanian airport for ten days and now are defrozen and unusable. You needed this research to assure the new funds and keep running, and now you have three months to obtain new samples, redo and fix it.

You can lose years chasing a dead end or be superseeded by a genius in some part of the planet that discovered the same as you first, or a different and better way to do it.

4) You don't just buy a lab and hire a team to create "something" nice.

Unless you are in the bussiness of teaching science you design the lab according of the exact product what you are trying to create. Any machine that you ordered and will not use enough frequently later is a hole in your presupuest. Any timed out kitt that you bought in excess quantity is your money ending in the dumpster bin.

You need to hire somebody familiar with what "hardware" is trendy and works and what machines are outdated since ten years even if you see it in each faculty and in propaganda.

Is a hamster wheel. Your skills are valuable only while you are running. If you stop, your huge time and money investment loses their value gradually, and if you stop for too much time (getting pregnant, suffering an accident or having small kids) you are out of the game. Thus, for many researchers cheap work is better than none.

And there are the stupid artificial constrains, a damocles sword in the shape of a clock. Scientist work is related with Universities schedule. They can expect to be hired mainly at the beginning of the year or in summer, hired for the next year. If you miss the train you will need to wait for another year.

Scientists are expected also by society to produce X discoveries at the interval of age Y and have a limited time for that. This is really idiot. Would be like expecting Leonardo painting the Monna lisa in three years maximum (and exactly between 27 and 29 yo), or stop painting.

And there is also a huge vanity factor. To be associated with an university or big brand even if you just make the coffee there, is good for the ego and help constructing your identity and selling you better later.

None of those have any relationship with what science really is, a method to solve problems, of course