Annotations

Taverna is used by various tools and projects for the association of metadata with data (annotation). These include: - Automatic Functional Annotation in a distributed Web service Environment(AFAWE) - annotation of plant genes with their functionality - Interactive genome annotation pipeline - automatic and manual annotation of genes - TaWeka - associating biological data with calculated functionality

In addition, Taverna makes use of the semantic annotation that has been specified for the services provided by the MOBY consortium.

Taverna has also been used for the identification of mismatches and possible annotations in workflows by the iSPIDER project.

AFAWE

The Max Planck Institute for Plant Breeding Research in Cologne, Germany have developed the Automatic Functional Annotation in a distributed Web Service Environment (AFAWE). AFAWE is a tool for the automatic functional annotation of new genes in plants and other organisms. The annotation involves the running of several Web services, and also the execution of a Taverna workflow.

The annotation workflow is available on myExperiment.

Publications

The paper Protein function prediction and annotation in an integrated environment powered by web services (AFAWE) by Joecker et al describes the concepts and implementation of AFAWE.

Annotation of genomes

A collaboration between Tom Oinn from the myGrid team and Anders Lanzen, Svenn Helge Grindhaug and Pal Puntervoll from the University of Bergen, Norway, has produced an interactive genome annotation pipeline.

Sequencing, characterising and annotating a genome are the first steps to understanding its function. Important stages in this include gene prediction, comparative genomics and function prediction of genes and gene products. With workflows all of these stages can be automate, requiring little human interaction. However, manual inspection can be required at certain points in the process.

Publications

Articles and papers about the success of Taverna for genome annotation are available on-line.

TaWeka

Luna De Ferrari from the Computational Systems Biology & Bioinformatics group at the University of Edinburgh has developed TaWeka,

a rapid prototyping tool for biological classifiers.

TaWeka uses Taverna workflows to store data retrieved from webservices, e.g. queries of biological data, into a database. Weka is then used to run machine learning experiments on the data in order to evaluate and improve biological classification functions.

Publications

A poster TaWeka: from biological web services to data mining by De Ferrara and Goryanin describes the purpose and implementation of TaWeka.

Adoption by the Moby consortium

The Moby project develops a system for interoperability between biological data hosts and analytical services. Their relationship with Taverna is multiple:

Publications

The paper Interoperability with Moby 1.0—It’s better than sharing your toothbrush! by the Moby consortium gives an overview of Moby and their activities.