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).

Homepage

https://github.com/fabriziocosta/EDeN

License

MIT

Recipe

/eden/meta.yaml

package eden

(downloads) docker_eden

Versions

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

<=1.10

Depends numpy

Depends openbabel

Depends pandas

Depends pybedtools

Depends python

>=2.7,<2.8.0a0

Depends python-graphviz

Depends rdkit

Depends reportlab

Depends requests

Depends rnashapes

Depends scikit-learn

>=0.17.0

Depends scipy

>=0.14.0

Depends weblogo

Requirements

Installation

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 quay.io/biocontainers/eden:<tag>

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