Tag: collaboration

Large scale, open neuroscience is a work-in-progress

The International Brain Lab (IBL) project has an outstanding team of PIs, covering both theory and experiments. The measurements themselves are interesting, and can lead to important insights. However, what is most distinctive is the organization of the project. The experimental labs will all train mice to perform the same task, and each lab will

Pre-preprint: blogging a project

SLAB is trying something new with one project in the lab. Prior to drafting a preprint, we’re blogging the project and sharing the results and analysis. We invite anyone to comment on the work.

Allen Institute’s Brain Observatory data set

The Allen Institute has released the first set of data from their Brain Observatory project. Many of you already know about this, but I wanted to post about it to encourage people to take a bit of time to check out the data set themselves. They have a github page with materials that can help

Slack software for labs

Slack is very useful team coordination software. It’s been such a help in my own lab, that I suspect that given a properly configured Slack account, I could simultaneously run GE, Google, Intel, and the US Federal Government. It’s easy to dismiss Slack. To a large extent, it’s basically a bunch of chat rooms. I

Ufora – easy parallel computing in Python

It’s still early days, but this looks impressively good. Ufora might be one of the easiest-to-try ways to use parallel computing. With just a couple of lines of code, you can run your existing Python code on aws or another worker system.

Remote, web-based analysis

Jeremy Freeman and his lab are developing tools for analyzing data using a workflow that is fundamentally more scalable not only in terms of computing power and data set size, but also in collaboration and sharing. The one-person, one-machine approach to data analysis can be highly efficient, but collaboration and scaling up computational power can

NES – NeuroMat – browser-based data collection

NES, from NeuroMat, is an open-source tool to manage clinical data gathered in hospitals and research institutions. Here’s their github link. More info from the lab.

Software Carpentry teaching programming and data management to scientists

Software Carpentry teaches scientists how to program and use open source tools to manage their data and make their life easier. They’re focussed specifically on software tools, rather than types of analysis, and so what they teach is pretty general. They started in 1998 and are currently part of the Mozilla Foundation. They hold bootcamps,

PubPeer browser plugins for PubMed

PubPeer has released browser plugins that add a line to PubMed results if there are comments on PubPeer for those publications. It looks like the example above. The install took less than 10 seconds. More on PubPeer

Protocols.io – 3 days left

As Labrigger mentioned earlier this week, ZappyLab is running a Kickstarter campaign to jump start their crowd-sourced protocol repository, Protocols.io. Perhaps the most attractive reward they’re offering for pledging are the Black Russian Espresso cookies, made with vodka and Kahlua. The idea of Protocols.io is to mitigate the tendency for every lab to reinvent the

ZappyLab Kickstarter: 1 week left!

This is exactly up the alley of what Labrigger is interested in supporting. There’s just one week left in their Kickstarter campaign. As of this writing, 300 people have contributed $30,000. With one final push this last week, they’ll meet their goal. They want to crowd source experimental protocols to increase efficiency and productivity. This

Giant Brain Discussion

Carson Chow’s blog announced: There is an epic discussion on the Connectionist mailing list right now. He followed up with his two cents entitled “(Lack of) Progress in neuroscience”. It’s an on-going, vibrant discussion on topics including big data & theory in neuroscience. His posts had a link to how to join the mailing list,

Plotly (plot.ly) for collaborative data visualization and analysis

It could be described as a GoogleDocs-type app for data analysis. But that would be a lazy description. Import your data, code up the analysis and visualization, and then share with collaborators who can view, modify, and contribute. They have APIs for Python, MATLAB, R, Julia, Perl, Ruby, and Arduino (import directly from hardware– example

Wakari Bundles – standardized Python for sharing code

I’ve been using Spyder recently for a MATLAB-like Python development environment (thanks for the tip, xcorr!). For python development within a browser window, I’ve used Wakari a bit. Now they have Bundles, which make it easier to share code with others because it takes care of all of the dependencies, and makes sure other people

Online Scientific Python: Wakari

If you like Python, want to analyze data online, and are interested in a standardized environment that can be easily shared, read on: Continuum Analytics is offering a new beta: Wakari. You can register to try it out! If you’re an academic frustrated by setting up computing environments and annoyed that your colleagues can’t easily