Comments (3)
I would recommend to follow the example from
https://github.com/mjoppich/pIMZ/blob/master/examples/IMZMLprocess.theo_weights.ipynb
since this is the most documented one (and the one we are currently working with, too). Bear in mind that pIMZ is still in active development - but we're glad you're interested in it!
Since you installed pIMZ with pip, you can simply use
from pIMZ.regions import SpectraRegion, ProteinWeights
The cIMZ library is compiled during the build process and should not worry you ;)
from pimz.
You mean regarding how data acquisition works?
Neumann, E. K., Djambazova, K. V., Caprioli, R. M., & Spraggins, J. M. (2020). Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine. Journal of the American Society for Mass Spectrometry. https://doi.org/10.1021/jasms.0c00232
Otherwise, what I found quite an interesting read regarding ML in IMS:
Verbeeck, N., Caprioli, R. M., & Van de Plas, R. (2019). Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry. Mass Spectrometry Reviews. https://doi.org/10.1002/mas.21602
As already mentioned, pIMZ is still in active development. We are currently improving our clustering techniques, but the basic stuff is already there.
What makes any development quite hard is the availability of (good) datasets. There are, unfortunately, not many :\
from pimz.
Thanks for sharing the example.
Just asking as a beginner in MSI, are there resources that explain the procedures from data/imaging perspective?
from pimz.
Related Issues (5)
- Couldn't install pIMZ following the instructions HOT 7
- ValueError: operands could not be broadcast together with remapped shapes [original->remapped]: (2,2) and requested shape (1,2) HOT 2
- Why exclude 0 values in `_get_median_spectrum` and also add `startedLog` with median values of all channels/z axis of regions HOT 3
- General m/z distribution. HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from pimz.