Our paper entitled "Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes" has been accepted for publication in Springer Nature's Journal of Biological Engineering. With rapid advances in flow cytometry, particularly with respect to high-throughput data acquisition, minimum sample preparation, and more parameters per cell, a massive, high-dimensional datasets are produced which demands novel computational techniques for actionable insights.
Abhishek Dhoble successfully defended his PhD dissertation entitled, "A novel flow cytometry based methodology for rapid, high throughput characterization of microbiome dynamics in anaerobic systems". We congratulate Dr. Abhishek Dhoble on this important milestone! An abstract for his dissertation follows:
Farhan Syed successfully defended his thesis entitled, "Development of an Automated System for Extraction and Quantification of Soybean Cyst Nematode (SCN) Eggs and Cysts" and will graduate with a Master of Science in Technical Systems Management from the Department of Agricultural and Biological Engineering.
This project is closely related to the soybean cyst nematode extractor we are currently testing. The abstract for his thesis follows.
Following is a brief slide deck for your consideration as you prepare your thesis / dissertation for submission to the Graduate College. As the Department Format Checker, it is my responsibility to ensure that your document meets the expected standards for format. Please review the slides to get a sense of how I may contribute to getting your document ready for submission.
We use a number of collaboration tools including software version control (git), cloud based documents (e.g. Google Drive) and a Synology-based file server and sync tool called CloudStation (Roughly equivalent to Dropbox / Box etc). While CloudStation works very easily, it is a little tricky to set up. Following are step by step instructions on how to set up a shared folder on CloudStation. The intended audiences for this article are both my lab members, as well as others looking for instructions on working with CloudStation.
After a couple years of tinkering, we finally have a working prototype of the Soybean Cyst Nematode Egg Extraction System, or our SCNExtractor for short. The following video shows the operation cycle of the SCNExtractor. We built this prototype as a two-channel system. The entire cycle consists of approximately four minutes, from sample loading to egg retrieval. Once the eggs are retreived from the sample collection funnels, they are stained and imaged. Computer vision then enables automatic egg counting.
Congratulations Nico for defending your thesis entitled, "Towards Bioengineered Ecosystems: Three Studies in Invasion Biology".
Dr. Bhalerao and graduate student Farhan Syed were among the first recipients of the Illinois Proof of Concept award. The OTM has a page describing the award. We are thrilled to benefit from it - stay tuned for more information on our upcoming soil testing device.