The tools for a modern lab

Many of the faculty at the Integrated Mathematical Oncology department refer to their groups as labs (Jacob Scott’s Theory Division is one of the exceptions). This is not strange since we work in a research institute in which the vast majority of the researchers are experimentalists and where the term lab is the standard way to refer to the space/equipment as well as the people working with them. As mathematical oncologists though, and as corny as this will sound, the only strength we have is the people in the group and not the fancy machines or sophisticated techniques we might have.

But that does not mean that we do not use tools and that these tools are not very important for our work. An interdisciplinary multi-site group is a possibility nowadays but only when certain types of tools are used which is why our group is now using:

  1. Slack for internal communication: prettier than IRC, faster than email, fancier than a messenger and more multiplatform that Apple Messages or Google Hangouts would be. Perfect? not entirely: we would be more comfortable with a less propietary system, maybe a Telegram with more group collaboration options.
  2. Dropbox/OneDrive/GoogleDrive (yes, 3 of them): because that is where our grants/papers/simulation results live.
  3. Github for code: just trying to get more used to this. Usually code is developed by one person per project so we do not have the same incentives to use Github as larger groups where code is owned by more than one person. But in the interest of transparency and being open acess this is how we intend to share work with the rest of the community.
  4. Python: to play with the data coming from our models. A lot of us are still more comfortable using Mathematica or Matlab but these are not opensource so that even if we shared the code many people would not be able to do much with it.
  5. Twitter: the social network of choice for many scientists. You will find many of us on Google’s G+ too.
  6. Skype for when not all the clever people can be in the same room.
  7. Blackboards. Old school but invaluable if all the clever people are in the same room.

Other important but not mandatory tools include:

  1. Evernote: Because not everything we produce is code, a grant or paper draft.
  2. Overleaf: The best way to work on a manuscript those times in which we can get away not using MS Word.

Things we tend not to use? Phone/Fax/Pony express/Carrier pigeons.

Suggestions? The idea is to have a core set of tools that allow us to collaborate and that everybody is happy using. The last is an important point: we are reaching a stage in which people are constantly asked to create more accounts and install new applications that do not talk to each other.

Update (13th Dec 2015): Following Jacob Scott’s advice I have added the links to the various services we use.

10 thoughts on “The tools for a modern lab

  1. Nice post David 🙂 As far as im is concerned, I use slack but prefer gitter.im, less integrations but less of a walled garden. Just a thought 🙂

    I’ve never gotten around to using evernote (tried a couple of times): perhaps I’m missing out…

    • I hear some people just use standard/off-the-shelve IRC 🙂
      Wish I had thought about it before I asked everybody in the group to sign up for slack!

      • My main problem with Slack so far is that it’s more a tool for well established groups than for academic collaborations where you need to talk with a lot of people in different projects but those people are not part of your group.
        In any case we use slack in Pint of Science so there’s the advantage of sticking to one tool only.

  2. This is a great post, David!

    Perhaps add ImageJ for image processing, and its large ecosystem of plugins?

    Regarding Matlab, Octave can use most of the codes, so it’s “closed sourcedeness” isn’t quite as bad a problem there as it used to be. I think of matlab as a well-supported specification as much as a specific software implementation.

    But we’re also trying to move our lab away from matlab and more towards scipy, etc. (Although python can surprise and cause bugs if you’re not careful, like treating floats as ints and giving weird results.) Down the road, we’re very keenly watching Julialang. Already has XML parsing, some parallelization, etc. We might shift MultiCellDS data processing in that direction, down the road.

  3. I am not sure of whether to include imageJ in the ‘must-have’ list since it’s more a nice tool to have (like Evernote) than a necessity for every member of the group. Most of the tools in that list include communication/collaboration.
    I agree with Octave as a nice replacement for Matlab although I think Jan showed that it’s a fair bit slower than Matlab (https://computecancer.wordpress.com/2015/09/26/java-c-matlab-or-python-for-cellular-automatons-speed-comparison/).

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