recipe medusa-data-fusion

Medusa is an approach to detect size-k modules of objects that, taken together, appear most significant to another set of objects. It builds on collective matrix factorization to derive different semantics, and it formulates the growing of the modules as a submodular optimization program.

Homepage

https://github.com/marinkaz/medusa

License

GPLv3

Recipe

/medusa-data-fusion/meta.yaml

package medusa-data-fusion

(downloads) docker_medusa-data-fusion

Versions

0.1-30.1-20.1-0

Depends
Required By

Installation

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

conda install medusa-data-fusion

and update with:

conda update medusa-data-fusion

or use the docker container:

docker pull quay.io/biocontainers/medusa-data-fusion:<tag>

(see medusa-data-fusion/tags for valid values for <tag>)