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Papers: 10.1186/s13321-020-00447-2

https://doi.org/10.1186/s13321-020-00447-2

DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques

Cited by: 54
Author(s): Maha A. Thafar, Rawan S. Olayan, Haitham Ashoor, Somayah Albaradei, Vladimir B. Bajic, Xin Gao, Takashi Gojobori, Magbubah Essack
Published: about 5 years ago

Software Mentions 6

bioconductor: ChemmineR
Cheminformatics Toolkit for R
Papers that mentioned: 39
Very Likely Science (100)
bioconductor: KEGGREST
Client-side REST access to the Kyoto Encyclopedia of Genes and Genomes (KEGG)
Papers that mentioned: 75
Very Likely Science (90)
cran: node2vec
Algorithmic Framework for Representational Learning on Graphs
Papers that mentioned: 104
Very Likely Science (85)
pypi: imbalanced-learn
Toolbox for imbalanced dataset in machine learning.
Papers that mentioned: 38
Very Likely Science (100)
pypi: node2vec
Implementation of the node2vec algorithm
Papers that mentioned: 104
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)