About

Browsing the knowledge base with BioKB

This website is the front-end of BioKB platform, a pipeline which, by exploiting text mining and semantic technologies, helps researchers easily access semantic content of thousands of abstracts and full text articles. The text mining component analyzes the articles content and extracts relations between a wide variety of concepts, extending the scope from proteins, chemicals and pathologies to biological processes and molecular functions. Extracted knowledge is stored in a knowledge base publicly available for both, human and machine access, via this web application and SPARQL endpoint.

Cite as:

Biryukov, M., Groues, V., Satagopam, V., & Schneider, R. (2018)
BioKB-Text Mining and Semantic Technologies for Biomedical Content Discovery

Curating facts from BioKB relations

From the relations extracted by the text-mining pipeline we are now able to curate facts in the form of SBML models. Moreover, these models can be annotated with the sentences from the BioKB knowledge base. To begin curating facts, please, register and contact us.

Cite as:

Vega, Carlos; Grouès, Valentin; Ostaszewski, Marek; Schneider, Reinhard; & Satagopam, Venkata. (2020).
BioKC: a collaborative platform for systems biology model curation and annotation.

Other works:

Workshop BioNetVisA from the 19th European Conference on Computational Biology (ECCB2020)
Vega, Carlos; Grouès, Valentin; Ostaszewski, Marek; Satagopam, Venkata; & Schneider, Reinhard. (2020).
BioKC: a platform for quality controlled curation and annotation of systems biology models.

People

This is a project of the Bioinformatics Core research group from the Luxembourg Centre for Systems Biomedicine, in the University of Luxembourg.

We would like to acknowledge Valentin Devassine for his work with end to end testing and Christos Kyriazis for his contributions to the unit tests.

Under construction

Coming soon

The BioKB platform and BioKC system are under active development. Upcoming features include:

  • A REST API
  • Support for different kinds of annotations in BioKC
  • Stable identifiers for fact via identifiers.org

Credits

Some of the web libraries used in this project include: Bootstrap, Vue, JQuery, select2, lodash, dataTables, yadcf, anno.js etc.

Special thanks to VSM team (Steven Vercruysse) for the support with vsm-box.