The videos you have made on PUMA are incredible and I can only guess to the effort you have taken in making PUMA and in making and editing the videos. I am surprised that you have not reached a wider audience. I have learnt a lot of microscopy basics from your videos but am afraid of taking on the challenge of making PUMA as it seems quite complex. I use fluorescence microscopes and am familiar with fluorescence imaging systems used in next generation DNA sequencing equipment but these imaging systems seem to have a simpler hardware user interface. An example is the ECHO convertible microscope, and the the EVOS systems from Thermo Fisher. The hardware is better integrated; Illumination (most often expanded beam lasers, for better monochromaticity), objectives (often water immersion for better NA), integrated camera and a display monitor make up these systems. And most folks use Python for analysis rather than C due to the extensive libraries and integration with std analysis software such as Image J.
Thanks. I don't have experience with DNA sequencing but it sounds like you are describing a very specific single job system (for micro-imaging DNA fluo bands in gels?) so using those things makes sense whereas to use them for general or other applications in microscopy might not be optimum. I have designed and built some histo lab equipment from scratch before (a custom tissue processor and an automated decalcification system) and I wrote the interfaces for those things in Python because they mostly required robotic hardware interfacing and a GUI rather than heavy maths on large datasets but I turn to C for advanced custom novel mathematical modelling and image processing since C is my native (programming) language, my novel algorithms are not implemented in any standard library or software package and the speed of C is essential for some of my more complex algorithms on large 3D datasets. I think some examples in my future videos will illustrate that. Of course, C is not the only language such things can be implemented in!
I watched twice the video, paused and searched for the details, I learned a lot, about programing and things who is margaret hamilton (uknown for me till know), great video
Looking forward to the future lessons
Wow, I didn´t expected that you will cover so many aspects, great, a lot a new stuff!
Thanks.
The videos you have made on PUMA are incredible and I can only guess to the effort you have taken in making PUMA and in making and editing the videos. I am surprised that you have not reached a wider audience. I have learnt a lot of microscopy basics from your videos but am afraid of taking on the challenge of making PUMA as it seems quite complex. I use fluorescence microscopes and am familiar with fluorescence imaging systems used in next generation DNA sequencing equipment but these imaging systems seem to have a simpler hardware user interface. An example is the ECHO convertible microscope, and the the EVOS systems from Thermo Fisher. The hardware is better integrated; Illumination (most often expanded beam lasers, for better monochromaticity), objectives (often water immersion for better NA), integrated camera and a display monitor make up these systems. And most folks use Python for analysis rather than C due to the extensive libraries and integration with std analysis software such as Image J.
Thanks. I don't have experience with DNA sequencing but it sounds like you are describing a very specific single job system (for micro-imaging DNA fluo bands in gels?) so using those things makes sense whereas to use them for general or other applications in microscopy might not be optimum. I have designed and built some histo lab equipment from scratch before (a custom tissue processor and an automated decalcification system) and I wrote the interfaces for those things in Python because they mostly required robotic hardware interfacing and a GUI rather than heavy maths on large datasets but I turn to C for advanced custom novel mathematical modelling and image processing since C is my native (programming) language, my novel algorithms are not implemented in any standard library or software package and the speed of C is essential for some of my more complex algorithms on large 3D datasets. I think some examples in my future videos will illustrate that. Of course, C is not the only language such things can be implemented in!
I watched twice the video, paused and searched for the details, I learned a lot, about programing and things who is margaret hamilton (uknown for me till know), great video
Thanks. A lot more to come!