Bioinformatics Conference Pro Tip

Can we all agree already to skip the “Why research on cancer is useful” introduction slide from now on?

If your talk lasts 25 minutes and goes into the minutiae of protein-protein interactions with regard to oncogenic pathways, maybe spending half of it convincing an audience of biologists and bioinformaticians that cancer is a bad thing that needs curing is not the best use of presentation time.

Filed under: Bioinfo, Quickies


  1. All you need is to introduce them to the famous “lazy programmer paradigm” that states “do just once what can be done more”, aka “factorise your code, dude!”

    If the conference starts with “cancer is baaaad”, then we can skip it on.

    Still, if I remember correctly my dear Ph.D. comics’ ‘Tales From the Road’ , there is no such thing as cure against cancer. So, maybe you still managed to misunderstand this introduction slide after all…


  2. Pied: let me translate it to a domain closer to you: imagine if every computer science presentations you attended started by a 3-slide reminder on why using computers instead of paper-and-pencil is beneficial to research… Actually, my analogy is flawed: the use of cancer research is probably even more obvious to anybody with a pulse.
    My call for agreement is also purely rhetorical: the problem essentially stems from bad presentation skills and a bit of laziness (so much easier to skip straight from Wikipedia-style generic cancer stats… on to pages filled with equations).

    Also, I am pretty hopeful that, by now, I would know that there isn’t such a thing as “a” cure for cancer (in the way PhD Comics was trying to mock). But there are definitely cures for [some forms of] cancer (and research thereon).
    There are also strong similarities between oncogenic pathways and other biological features across all types of cancers (otherwise we wouldn’t call them all “cancer”, now would we). Since this is bioinformatics and super-fundamental-level research, you can therefore talk about “cancer cure”, insofar as you see work around near-generic cancer cell features.

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