Kuan Y. Chang

TL;DR: Gramene replaces the existing AceDB database 'RiceGenes' with a relational database based on Oracle, which aims to use the rice genetic, physical and sequence maps as fundamental organizing units, to provide a common denominator for moving from one crop grass to another and to serve as a portal for interconnecting with other web-based crop grass resources.

TL;DR: A brief overview of the search tools available to the plant research community in Gramene is presented, making extensive use of controlled vocabularies to describe specific biological attributes in ways that permit users to query those domains and make comparisons across taxonomic groups.

TL;DR: The physicochemical model aided with aggregation and secondary structural features reaches 90% accuracy and 0.79 Matthew's correlation coefficient, which exceeds the previous models and suggests that aggregation could be an important feature for identifying antiviral peptides.

TL;DR: A Database of Anti-Microbial peptides (ADAM), which contains 7,007 unique sequences and 759 structures, is presented to systematically establish comprehensive associations between AMP sequences and structures through structural folds and to provide an easy access to view their relationships.

TL;DR: Gramene is populating and curating Gramene with annotated rice genomic sequence data and associated biological information including molecular markers, mutants, phenotypes, polymorphisms and Quantitative Trait Loci in order to support queries across various data sets as well as across external databases.