An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1155/2021/5573740

https://doi.org/10.1155/2021/5573740

Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning

Cited by: 10
Author(s): Simon Wein, Gustavo Deco, Ana Maria Tomé, Markus Goldhacker, Wilhelm M. Malloni, Mark W. Greenlee, Elmar Lang
Published: about 4 years ago

Software Mentions 7

cran: node2vec
Algorithmic Framework for Representational Learning on Graphs
Papers that mentioned: 104
Very Likely Science (85)
cran: word2vec
Distributed Representations of Words
Papers that mentioned: 413
Very Likely Science (90)
pypi: ephypype
Python package providing pipelines for electrophysiological (EEG/MEG) data within nipype framework.
Papers that mentioned: 1
Very Likely Science (65)
pypi: graphpype
Graph analysis for neuropycon (using nipype, and ephypype); based on previous packages dmgraphanalysis and then dmgraphanalysis_nodes and graphpype
Papers that mentioned: 1
Very Likely Science (75)
pypi: node2vec
Implementation of the node2vec algorithm
Papers that mentioned: 104
Very Likely Science (100)
pypi: tvc_benchmarker
tvc_benchmarker is a package that compares different time-varying functoinal connectivity methods against eachother (neuroimaging/fmri).
Papers that mentioned: 2
Very Likely Science (85)
pypi: word2vec
Wrapper for Google word2vec
Papers that mentioned: 413
Very Likely Science (85)