Learn to use the UCSC Genome Browser with this free tutorial, sponsored by UCSC Genome Bioinformatics Group. The UCSC Genome Browser provides a way to examine the data from many genomes, with extensive annotation tracks for various data types including known genes, predicted genes, SNPs, comparative multi-species analysis and much more. This introductory tutorial focuses on the foundation and framework for the organization and display of the data, and basic text and sequence searches. This tutorial, which is the first in a series of three tutorials on the UCSC Genome Browser, will get you on your way to expertly navigating this vital tool for genomic research.
You will learn:
This tutorial is a part of the tutorial group UCSC Tutorials. You might find the other tutorials in the group interesting:
ENCODE Foundations: ENCyclopedia of DNA Elements
UCSC Genome Browser: The Additional Tools: Additional tools at the UCSC Genome Browser
UCSC Genome Browser: Custom Tracks and Table Browser: UCSC Genome Browser advanced topics
UCSC Archaeal Genome Browser: Provides you with many research and analysis tools that can be used to examine the genomes of more than 50 microbial species from the domain archaea.
ENCODE Data at UCSC: ENCODE Data at UCSC
Algorithms and Analysis : This category contains various tools that may help perform analysis of different genomics data types. This may include sequence alignment, large-scale or complex queries, motif finding, or comparative assessments.
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
Ruble L. Cara et al., Genomic structure and expression of the human serotonin 2A receptor gene ( HTR2A ) locus: identification of novel HTR2A and antisense ( HTR2A-AS1 ) exons. BMC Genetics (2016) doi:10.1186/s12863-015-0325-6
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Watson M. Christopher et al., Enhanced diagnostic yield in Meckel-Gruber and Joubert syndrome through exome sequencing supplemented with split-read mapping Clinical-Molecular Genetics and Cytogenetics. BMC Medical Genetics (2016) doi:10.1186/s12881-015-0265-z
Kumar Sunil et al., Predicting transcription factor site occupancy using DNA sequence intrinsic and cell-type specific chromatin features. BMC Bioinformatics (2016) doi:10.1186/s12859-015-0846-z
An Yu et al., Genome-wide copy number variant analysis for congenital ventricular septal defects in Chinese Han population. BMC Medical Genomics (2016) doi:10.1186/s12920-015-0163-4