[Update: A little bird pointed out I didn’t have a link to the actual Portal blog. That has been remedied along with a link to the Portal Project website for those who’d like more info on the project] A couple weeks ago, I posted about the new data paper from my long-term field site, the Portal Project.
This post follows on from “Getting Started”. In the lab we use IgorPRO for pretty much everything. We have many analysis routines that run in Igor, we have scripts for processing microscope metadata etc, and we use it for generating all figures for our papers. Even so, people in the lab engage with it to varying extents. The main battle is that the use of Excel is pretty ubiquitous.
Something that has driven me nuts for a while is the bug in FIJI/ImageJ when making montages of image stacks. This post is about a solution to this problem. What’s a montage? You have a stack of images and you want to array them in m rows by n columns. This is useful for showing a gallery of each frame in a movie or to separate the channels in a multichannel image.
This is the story behind “Comparing process-based and constraint-based approaches for modeling macroecological patterns” by my former PhD student Xiao Xiao, James O’Dwyer, and myself. Background I was on sabbatical in the fall of 2013 and was doing a lot of reading, and I reread “An integrative framework for stochastic, size-structured community assembly” by James O’Dwyer, Jessica Green, and colleagues.
Data Science is all the rage these days. But this current craze focuses on a particular kind of data analysis. I conducted an informal poll as an icebreaker at a recent data science party, and most of the people I talked to said that it wasn’t data science if it didn’t include machine learning. Companies in all industries have been hiring “quants” to do statistical modeling. Even in the humanities, “distant reading” is a growing trend.
It is with great glee that I can announce the latest release of the Portal Project Database. For those of you who just want to go play with the data – here’s the link to the Data Paper we just published in Ecology. But I would encourage you to read on, as there is more data-related news below. But first, a story. As some of you know, I manage a long-term ecological study: the Portal Project.
More on the theme of “The Digital Cell”: using quantitative, computational approaches in cell biology. So you want to get started? Well, the short version of this post is: Programming I make no claim to be a computer wizard. My first taste of programming was the same as anyone who went to school in the UK in the 1980s: BBC Basic.
The future of cell biology, even for small labs, is quantitative and computational. What does this mean and what should it look like? My group is not there yet, but in this post I’ll describe where we are heading. The graphic below shows my current view of the ideal workflow for my lab.
If you are a cell biologist, you will have noticed the change in emphasis in our field. At one time, cell biology papers were – in the main – qualitative . Micrographs of “representative cells”, western blots of a “typical experiment”… This descriptive style gave way to more quantitative approaches, converting observations into numbers that could be objectively assessed.
Today I saw a tweet from Manuel Théry (an Associate Ed at Mol Biol Cell ). Which said that he heard that the Editor-in-Chief of MBoC, David Drubin shops for interesting preprints on bioRxiv to encourage the authors to submit to MBoC.