A novel probabilistic generator for large-scale gene association networks
<h4>Motivation</h4> Gene expression data provide an opportunity for reverse-engineering gene-gene associations using network inference methods. However, it is difficult to assess the performance of these methods because the true underlying network is unknown in real data. Current benchma...
Saved in:
Main Authors: | Tyler Grimes, Somnath Datta |
---|---|
Format: | article |
Language: | EN |
Published: |
Public Library of Science (PLoS)
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/86ffeeb6adbd4e4a92b3d3d0711f5c2f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A novel probabilistic generator for large-scale gene association networks.
by: Tyler Grimes, et al.
Published: (2021) -
Synthetic data generation with probabilistic Bayesian Networks
by: Grigoriy Gogoshin, et al.
Published: (2021) -
optPBN: an optimisation toolbox for probabilistic Boolean networks.
by: Panuwat Trairatphisan, et al.
Published: (2014) -
Probabilistic diffusion tractography reveals improvement of structural network in musicians.
by: Jianfu Li, et al.
Published: (2014) -
The generative capacity of probabilistic protein sequence models
by: Francisco McGee, et al.
Published: (2021)