This is a quick post describing how to install the pymba package on Windows. Basically, you have to install the AVT Vimba package (v. 1.3+), Python 2.7.x and the pymba package.
Showing others the data you gained during an experiment is crucial for the scientific grasp. Generating easy beautiful graphs enables you to show your great data to the community in seconds rather than hours. With Python, Matplotlib, Seaborn and Pandas you have the right tools at hand. Here I show you how to use them.
The brandnew OpenCV master version 3 has a lot of advantages. First to mention is the accessibility of the XiAPI parameters. Because XIMEA is still not supported by default in OpenCV, I provide you here the necessary files as a zip file.
Screening the progeny of your model system of interest is one of the most common tasks in genetic engineering. Fast screening methods allow you a high-throughput and less effort. Using the HotSHOT protocol, you can gain PCR-ready genomic DNA out of various tissues.
For data analysis, I aimed to save every figure generated by Pandas. Having several conditions and parameters, I grouped a Pandas DataFrame according to conditions and plotted the histograms of my parameters. However, saving each condition histogram figure was a little bit tricky. Here’s how I solved it.
I recently found a decent camera for my behavior experiments. It was very important for me, that the camera supports LabVIEW and Python, ideally via OpenCV. Another important feature was the usage of USB 3 instead of Firewire or GigE, because of ease of use and availability in standart computers. At the same time, OpenCV is a powerful tool to do comprehensive image processing and analysis. And, even more important, it is available thorugh a Python interface, enabling me to develop fast, efficient and cost-effective tools to investigate zebrafish behavior. Here I am describing how to use Python, OpenCV and the XIMEA cam together.
As everyone knows, there are plenty of Python libraries. A good overview and at the same time unofficial Windows binaries one can find on Christoph Gohlke’s website. Here, I describe what Python libraries I do use and for what reason and purpose. My main focus is on Data Analysis, Computer Vision and Graphical User Interfaces. In general, I use either Notepad++ or Python(x,y) or just Spyder (included in Python(x,y) or Anaconda) with IPython as an IDE. Recently, I discovered the Jupyter notebooks recommended by a colleague of mine, and try to use it now more regularily.
A common issue is finding a primer to sequence your region of interest somewhere in a vector. And the easiest thing is using already existing primers from your sequencing service. But looking for each primer in your plasmid file? No. Here, I am going to show you how to implement easy all standard sequencing primers of your sequencing service of choice to the wonderful, free plasmid editor ApE using a simple python script.
Being a researcher is nowadays not the easiest thing. Being on a limited contract, having the saying “publish or perish” in mind, pressure is not low. Even juniors like I am, if you want to play with the big ones, one has to be good. Well, being good is not easy as it probably sounds. “Being good” is kind of connected to publications, impact of publications is connected to your research outcome, and your research outcome is not finally independent of luck. Or even worse, you compete during your research with a couple of other research groups around the globe. Some are faster, some have more money, all what you can think of.
So what I am talking about here? This is not an introduction to a programming language, isn’t it? Hm, yes it is. In my opinion the ability to program your own piece of software is essential in this (research) environment and puts you into a better position.
Where do we need software? The easy answer is: everywhere. You are faced in daily life with gained data and its analysis. The good thing is: research is all about gaining data and analyze them, so the pool of available software is huge. However, finding the right one is not always easy. And what can happen is that you may have to pay for it. And many times, you only need one aspect of a software. This is where I want to make my point. My intention is not to compete with powerful, commercial software. My aim is to enhance your workflows. Therefore, I totally encourage you looking for small (free) webtools such as portrayed in my webtools post and store them in your favorites to smarten your workflows. And if you found one, stick to it. For all the rest, take a closer look here.
Saving money in a molecular biology lab is not always easy. First of all, you may have established, kind of good working protocols which do what you want. Mostly. However, I am presenting here some protocols or let‘s say workflow ideas reducing the chance of doing errors, raising your time efficiancy and reduce costs per reaction/experiment. Probably 99% of all researchers already know all the „tips“ or „ideas“; however, the remaining one percent gets here access to knowledge, which they should be faced with. And probably the 99% of „yes, I know“ fraction can (re)learn something.