@article{26,
  keywords = {Database Management Systems, Databases, Genetic, Genome, Plant, Genomics, Internet, Oryza sativa, Plant Proteins, Quantitative Trait Loci, Stress, Physiological, User-Computer Interface},
  author = {Shuchi Smita and Sangram Lenka and Amit Katiyar and Pankaj Jaiswal and Justin Preece and Kailash Bansal},
  title = {QlicRice: a web interface for abiotic stress responsive QTL and loci interaction channels in rice.},
  abstract = {The QlicRice database is designed to host publicly accessible, abiotic stress responsive quantitative trait loci (QTLs) in rice (Oryza sativa) and their corresponding sequenced gene loci. It provides a platform for the data mining of abiotic stress responsive QTLs, as well as browsing and annotating associated traits, their location on a sequenced genome, mapped expressed sequence tags (ESTs) and tissue and growth stage-specific expressions on the whole genome. Information on QTLs related to abiotic stresses and their corresponding loci from a genomic perspective has not yet been integrated on an accessible, user-friendly platform. QlicRice offers client-responsive architecture to retrieve meaningful biological information--integrated and named 'Qlic Search'--embedded in a query phrase autocomplete feature, coupled with multiple search options that include trait names, genes and QTL IDs. A comprehensive physical and genetic map and vital statistics have been provided in a graphical manner for deciphering the position of QTLs on different chromosomes. A convenient and intuitive user interface have been designed to help users retrieve associations to agronomically important QTLs on abiotic stress response in rice. Database URL: http://nabg.iasri.res.in:8080/qlic-rice/.},
  year = {2011},
  journal = {Database : the journal of biological databases and curation},
  volume = {2011},
  pages = {bar037},
  month = {2011},
  issn = {1758-0463},
  doi = {10.1093/database/bar037},
  language = {eng},
}