recipe eden

The Explicit Decomposition with Neighborhoods (EDeN) is a decompositional kernel based on the Neighborhood Subgraph Pairwise Distance Kernel (NSPDK) that can be used to induce an explicit feature representation for graphs. This in turn allows the adoption of machine learning algorithm to perform supervised and unsupervised learning task in a scalable way (e.g. using fast stochastic gradient descent methods in classification and approximate neighborhood queries in clustering).






package eden

(downloads) docker_eden


2.0-2, 2.0-1, 2.0-0, 1.1-0

Depends biopython

Depends cvxopt

Depends dill

Depends esmre

Depends joblib

Depends matplotlib

Depends muscle

Depends networkx


Depends numpy

Depends openbabel

Depends pandas

Depends pybedtools

Depends python


Depends python-graphviz

Depends rdkit

Depends reportlab

Depends requests

Depends rnashapes

Depends scikit-learn


Depends scipy


Depends weblogo



With an activated Bioconda channel (see 2. Set up channels), install with:

conda install eden

and update with:

conda update eden

or use the docker container:

docker pull<tag>

(see eden/tags for valid values for <tag>)