About Leafdata

LEAFDATA is a manually curated literature database. Statements are collected from 'Results' sections of full text primary publications. Our main interest is leaf growth and development therefore we select research papers describing altered leaf phenotypes or analyzing genes that were previously identified as important regulators of leaf formation. The development of this resource follows our successful efforts establishing our own manual annotation method described in
Szakonyi et al. 2015. LEAFDATA currently hosts 15721 text fragments organized by information type.

The LEAFDATA resource initiated in the framework of AGRON-OMICS project European Commission 6th Framework Programme project (Grant number LSHG-CT-2006-037704). During this period, we developed the comprehensive LeafKnowtator framework to annotate scientific literature using the Protégé suite and Knowtator plugin. We cataloged information in the KnownLeaf relational database from 283 articles yielding 9,947 individual statements as an international effort with the participation of six research groups from five countries.

Unlike most databases collecting information about gene functions, KnowLeaf links molecular and genetic data to phenotype statements. Furthermore, we developed automatized tools to detect inaccuracies in the database, performed several rounds of quality evaluations, and improved the consistency of our data. The LeafKnowtator and KnownLeaf structures allowed us to visualize our annotations in Cytoscape and to merge our literature database with other large-scale datasets. The resulting KnownLeaf database is a unique systems biology tool that addresses relevant biological questions in the field of Arabidopsis leaf growth by revealing new associations between genes and discovering novel gene functions.

"As a next step, this searchable database was developed for public access. In addition, the paper library was extended to 435 manuscripts"

Dr. Dóra Szakonyi