bioinformatics, genomes, biology etc. "I don't mean to sound angry and cynical, but I am, so that's how it comes across"

Cats, dogs and bioinformatics

So I’m at PAG, a pre-meeting meeting organised by a US-EU taskforce, and Ewan Birney gave a keynote where he introduced the idea of cats and dogs in science.  Here is a very brief summary (paraphrasing Ewan):

  • Cats – fiercely independent, they do their own thing and couldn’t care less what the other cats are up to, as long as the other cats don’t encroach on their territory
  • Dogs – pack animals, there is a hierarchy but ultimately all of the dogs follow the pack and do what’s best for the group, rather than what’s best for the individual

Ewan’s point was that in science, most PI’s are like cats; and that this is not a bad thing, and has served science very well.  PIs need to think outside of the box, they need to be competitive and go their own way, they are independent thinkers.  Science selects for cats, certainly when it comes to research leaders.  However, Ewan also then went on to say that, in large consortia such as ENCODE, it’s best if everyone is a dog – even if usually you’re a cat.  In large consortia, cats need to behave like dogs.  Cats need to recognise they are cats and curb their behaviour.

I wanted to extend the analogy into bioinformatics, and I would posit that most bioinformaticians are cats, and this leads to the horrendous duplication of effort that plagues our field.  We’re drowning in aligners (and probably assemblers), most of which provide only a small improvement on existing techniques on very specific types of data; we create new things when developing existing things would be better; we don’t follow the pack, we strike out on our own – even to the point of re-implementing stuff in a different language just because we didn’t like the original one.

The thing is, there’s a time to be a cat, and there’s a time to be a dog; figuring out which to be and when can be difficult, but it’s essential we do so if we don’t waste yet more time contributing to the “1% club” (where your new shiny algorithm is 1% better than an existing algorithm).



  1. Two thoughts Mick:

    1 – if we want to tackle complex problems we will need to work like “dogs” – the “cat” world doesn’t scale (we are running out of low-hanging fruits that can be collected by a single-minded “cat”).

    2 – Bioinformaticians are scientists so no surprise they behave like “cats”. The “horrendous duplication of effort” is not a unique feature of bioinformatics – how many *seq protocols have been published for instance? (but of course I would agree with your view given my point 1).

  2. Indeed, your example of *seq is very relevant, as it shows that science itself (publishing, funding) rewards cat-behaviour and selects against dogs. Inventing a new -seq is the modern equivalent of inventing a new -ome.

  3. Interesting analogy. There’s also a recent article in PLOS Biology (http://dx.doi.org/10.1371/journal.pbio.1001744) that casts scientists working in high-throughput fields (genomics, but could also be applied to bioinformatics) into different stereotypes. In this analogy ‘cats’ are replaced by ‘hermits’, but there are more fun stereotypes … it’s worth (and fun) reading!

    The final message acknowledges that we are not 100% cats or dogs but that our scientific personalities are actually made by a mixture of these stereotypes: “Be aware of your own personal tendencies toward these potentially damaging behaviors” 🙂

    Enjoy the reading!



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