Learn to use Saccharomyces Genome Database (SGD), a collection of data and tools for genetic and proteomic analyses of the bakers' or budding yeast, Saccharomyces cerevisiae. As the first eukaryotic genome to be fully sequenced, Saccharomyces cerevisiae, has a unique history. Yeast is a widely used model organism for molecular biology, genetics and genomics analysis and this resource contains a tremendous amount of knowledge with extensive depth. Learn how to use this resource, so you too can effectively use the tools and mine the voluminous data available in this database.
You will learn:
This tutorial is a part of the tutorial group Model organisms. You might find the other tutorials in the group interesting:
TAIR: The Arabidopsis Information Resource
PhenomicDB: Phenotypes database
WormBase: Molecular and genetic information on Caenorhabditis elegans and related species
FlyBase: A resource for the genes, genome and molecular biology of Drosophila melanogaster and related species.
Mouse Genome Informatics (MGI): The Mouse Genome Informatics resource provides data, tools, and analyses for the mouse model organism.
Rat Genome Database (RGD): Rat Genome Database
ZFIN: The Zebrafish Information Network
Gramene: A resource on rice and other grass genomes
Genome Databases (euk) : Genomic databases or repositories primarily aimed at eukaryotic organisms. Some may contain prokaryotic data as well.
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Recent BioMed Central research articles citing this resource
Meijnen Jean-Paul et al., Polygenic analysis and targeted improvement of the complex trait of high acetic acid tolerance in the yeast Saccharomyces cerevisiae. Biotechnology for Biofuels (2016) doi:10.1186/s13068-015-0421-x
Yuan Huili et al., A network based covariance test for detecting multivariate eQTL in saccharomyces cerevisiae. BMC Systems Biology (2016) doi:10.1186/s12918-015-0245-0
Chen Lujia et al., Learning a hierarchical representation of the yeast transcriptomic machinery using an autoencoder model. BMC Bioinformatics (2016) doi:10.1186/s12859-015-0852-1
Xiao Xiong et al., Speech dereverberation for enhancement and recognition using dynamic features constrained deep neural networks and feature adaptation. EURASIP Journal on Advances in Signal Processing (2016) doi:10.1186/s13634-015-0300-4
Taha Kamal et al., Predicting the functions of a protein from its ability to associate with other molecules Knowledge-based analysis. BMC Bioinformatics (2016) doi:10.1186/s12859-016-0882-3