Question
Asked 11th Mar, 2021
Why some substructures of the radius 2 do not show up in Morgan fingerprints?
I am using RDkit to generate the morgan fingerprints. Radius was chosen to be 2. Take valine as an example, the dictionary contains bit information shows (atom index, radius) pair.
We have all the substructures of all atomes with radius 0 as fingerprints, and all the substructures of all the atoms with radius 1 as fingerprints. But there are only a few substructures with radius 2 as fingerprints. Why so few?
Similar questions and discussions
Is Scientia Global a predatory scientific publisher?
I received an unsolicited email from Scientia Global and I can't tell if they are a predatory publisher of scientific journal articles or news articles or if they are legit.
"Dear Dr. April Robin Martinig,
I hope you do not mind me emailing you directly, I thought it would be the easiest way to make first contact. If you have time for a short discussion I was hoping to speak with you about your research and our interest to feature your work in an upcoming issue of our science communication publication, Scientia.
I will run you through this in more detail when we talk. But to give you a very quick insight into Scientia and the style in which we publish, I have attached a few example articles from research groups we have recently worked with. I have attached these as HTML files to reduce the size, but I can send PDF versions if you would prefer.
You may also view one of our recent full publications here: https://www.scientia.global/scientia-issue-132/
Please let me know if you might have 10 minutes for a short phone call and advise when would be a good time and day for you to discuss further?
I look forward to talking soon.
Kind regards,
Paris Allen"
Related Publications
Objective:
To visualize the encoding capability of magnetic resonance fingerprinting (MRF) dictionaries.
Materials and methods:
High-dimensional MRF dictionaries were simulated and embedded into a lower-dimensional space using t-distributed stochastic neighbor embedding (t-SNE). The embeddings were visualized via colors as a surrogate for locati...
Purpose
To develop a reproducible and fast method to reconstruct MR fingerprinting arterial spin labeling (MRF‐ASL) perfusion maps using deep learning.
Method
A fully connected neural network, denoted as DeepMARS, was trained using simulation data and added Gaussian noise. Two MRF‐ASL models were used to generate the simulation data, specifically...
Quantitative parameter maps obtained from Magnetic Resonance Fingerprinting (MRF) are sensitive to B1+ inhomogeneities. In principle, one could reduce this dependency by using a dictionary with an additional B1+ dimension. However, if the dictionary entries are not well distinguishable, the simultaneous pattern matching of three parameters (T1, T2,...