Tutorial and training materials

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:

  • to navigate the SGD site, locate Basic and Advanced Search options, and use the site map to access additional search tools
  • to perform the two Basic SGD Quick and Text Search types and understand the displays
  • to navigate the SGD Locus Page and access data from a variety of tools, tabs, and links
  • to investigate many related resources associated with SGD


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

WormBase: molecular and genetic information on Caenorhabditis elegans and related species

PhenomicDB: Phenotypes database

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

Wang Zhen et al., Genome-wide analysis of the R2R3-MYB transcription factor genes in Chinese cabbage ( Brassica rapa ssp. pekinensis ) reveals their stress and hormone responsive patterns. BMC Genomics (2015) doi:10.1186/s12864-015-1216-y

Bet Anne et al., The HIV-1 Antisense Protein (ASP) induces CD8 T cell responses during chronic infection. Retrovirology (2015) doi:10.1186/s12977-015-0135-y

Gu Muxin et al., H2A.Z marks antisense promoters and has positive effects on antisense transcript levels in budding yeast. BMC Genomics (2015) doi:10.1186/s12864-015-1247-4

Najafabadi M Maryam et al., Deep learning applications and challenges in big data analytics. Journal of Big Data (2015) doi:10.1186/s40537-014-0007-7

Peng Jiajie et al., Measuring semantic similarities by combining gene ontology annotations and gene co-function networks Knowledge-based analysis. BMC Bioinformatics (2015) doi:10.1186/s12859-015-0474-7