Package: biokeen
BioKEEN (Biological KnowlEdge EmbeddiNgs) is a package for training and evaluating biological knowledge graph
embeddings built onPyKEEN.Because we use PyKEEN as the underlying software package, implementations of 10 knowledge graph embedding models are
currently available for BioKEEN. Furthermore, BioKEEN can be run intraining modein which users provide their own set
of hyper-parameter values, or inhyper-parameter optimization modeto find suitable hyper-parameter values from set
of user defined values.Through the integration of theBio2BEL[2]software numerous biomedical databases are
directly accessible within BioKEEN.BioKEEN can also be run without having experience in programing by using its interactive command line interface that can
be started with the command “biokeen” from a terminal.Share Your Experimental ArtifactsYou can share you trained KGE models along the other experimental artifacts through theKEEN-Model-Zoo.TutorialsA brief tutorial on how to get started with BioKEEN is availablehere.Further tutorials are can be found in thenotebooks directoryand in ourdocumentation.CitationIf you find BioKEEN useful in your work, please consider citing:[1]Ali, M.,et al.(2019).BioKEEN: A library for learning and evaluating biological knowledge graph embeddings.Bioinformatics, btz117.Note: ComPath has been updated, for this reason we have uploaded the dataset version that we have used for
our experiments:datasetInstallationTo install biokeen, Python 3.6+ is required, and we recommend to install it on Linux or Mac OS systems.
Please run following command:$pipinstallgit+https://github.com/SmartDataAnalytics/BioKEEN.gitAlternatively, it can be installed from the source for development with:$gitclonehttps://github.com/SmartDataAnalytics/BioKEEN.gitbiokeen$cdbiokeen$pipinstall-e.ContributingContributions, whether filing an issue, making a pull request, or forking, are appreciated.
SeeCONTRIBUTING.rstfor more
information on getting involved.CLI UsageTo show BioKEEN’s available commands, please run following command:biokeenStarting the Training/HPO Pipeline - Set Up Your Experiment within 60 secondsTo configure an experiment via the CLI, please run following command:biokeenstartTo start BioKEEN with an existing configuration file, please run the following command:biokeenstart-f/path/to/config.jsonStarting the Prediction PipelineTo make prediction based on a trained model, please run following command:biokeenpredict-m/path/to/model/directory-d/path/to/data/directorywhere the value for the argument-mis the directory containing the model, in more detail following files must be
contained in the directory:configuration.jsonentities_to_embeddings.jsonrelations_to_embeddings.jsontrained_model.pklThese files are created automatically created after model is trained (and evaluated) and exported in your
specified output directory.The value for the argument-dis the directory containing the data for which inference should be applied, and it
needs to contain following files:entities.tsvrelations.tsvwhereentities.tsvcontains all entities of interest, and relations.tsv all relations. Both files should contain
should contain a single column containing all the entities/relations. Based on these files, PyKEEN will create all
triple permutations, and computes the predictions for them, and saves them in data directory
inpredictions.tsv.Summarize the Results of All ExperimentsTo summarize the results of all experiments, please run following command:biokeensummarize-d/path/to/experiments/directory-o/path/to/output/file.csvGetting Bio2BEL DataTo download and structure the data from aBio2BELrepository, run:biokeendataget<name>Where<name>can be any repository name in Bio2BEL such ashippie,mirtarbase.References[2]Hoyt, C.,et al.(2019).Integration of Structured Biological Data Sources using Biological Expression Language.bioRxiv, 631812.