Skip to main content

Genome Browser

On June 22, 2000, UCSC and the other members of the International Human Genome Project consortium completed the first working draft of the human genome assembly, forever ensuring free public access to the genome and the information it contains. A few weeks later, on July 7, 2000, the newly assembled genome was released on the web at http://genome.ucsc.edu, along with the initial prototype of a graphical viewing tool, the UCSC Genome Browser. In the ensuing years, the website has grown to include a broad collection of vertebrate and model organism assemblies and annotations, along with a large suite of tools for viewing, analyzing and downloading data. 

Tools provided on Genome Browser:
  • Genome Browser
    interactively visualize genomic data
  • BLAT
    rapidly align sequences to the genome
  • Table Browser
    download data from the Genome Browser database
  • Variant Annotation Integrator
    get functional effect predictions for variant calls
  • Data Integrator
    combine data sources from the Genome Browser database
  • Gene Sorter
    find genes that are similar by expression and other metrics
  • Genome Browser in a Box (GBiB)
    run the Genome Browser on your laptop or server
  • In-Silico PCR
    rapidly align PCR primer pairs to the genome
  • LiftOver
    convert genome coordinates between assemblies
  • VisiGene
    interactively view in situ images of mouse and frog 
     
    The following tools and utilities created by the UCSC Genome Browser Group are available for public use:
    • Batch Coordinate Conversion (liftOver) - converts genome coordinates and genome annotation files between assemblies. The current version supports both forward and reverse conversions, as well as conversions between selected species.
    • DNA Duster - removes formatting characters and other non-sequence-related characters from an input sequence. Offers several configuration options for the output format, including translated protein.
    • Protein Duster - removes formatting characters and other non-sequence-related characters from an input sequence. Offers several configuration options for the output format.
    • Phylogenetic Tree PNG Maker - creates a PNG image from the phylogenetic tree specification given. Offers several configuration options for branch lengths, normalized lengths, branch labels, legend etc.
    • Executable and Source Code Downloads - executable and source code downloads of the Genome Browser, Blat and liftOver.
     

Comments

Most Viewed Post

How to keep chain ID / IDs in GROMACS?

In GROMACS , while converting pdb file (monomer or multimer) into .gro file, it do not preserve the chain ID information. Due to the lack of chain ID information, pdb file retrieved from .gro file at any stage of the simulation has missing chain IDs and pdb file can not be visualized properly in PYMOL / RASMOL . There are two ways to convert .gro file into .pdb Lets say your protein name is xyz.pdb 1] gmx editconf -f xyz.gro -o xyz.pdb 2] gmx trjconv -f  xyz.gro -o xyz.pdb -s xyz.tpr Only ' trjconv ' will retrieve the chain ID information for all the chains. and not ' editconf '. If you have monomer protein and wish to assign any chain ID then following command will be of your interest: gmx editconf -f xyz.gro -o xyz.pdb -label [ chain-ID ]

Python : Turtle tree

Turtle module can be used to draw some very nice patterns in Python. Following are some examples with code. ==================== import turtle import random t = turtle.Turtle( shape = "circle" ) t.lt( 90 ) lv = 14 l = 120 s = 30 t.color( 'indigo' ) t.width(lv) t.penup() t.bk(l) t.pendown() t.fd(l) def draw_tree ( l , level ): width = t.width() # save the current pen width t.width(width * 3.0 / 4.0 ) # narrow the pen width l = 3.0 / 4.0 * l #t.color(R,G,B) #provide the RGB numbers t.color(random.random(), random.random(), random.random()) t.lt(s) t.fd(l) if level < lv: draw_tree(l, level + 1 ) t.color(random.random(), random.random(), random.random()) t.bk(l) t.rt( 2 * s) t.fd(l) if level < lv: draw_tree(l, level + 1 ) t.color(random.random(), random.random(), random.random()) t.bk(l) t.lt(s) t.width(width) # restore the previous pen width t.speed( "fastest" ) draw_tree(l, 5 ) turtle.done() ===========...

How to use MODELLER to build DIMER homology model with ligand?

How to use MODELLER to build DIMER homology model with ligand? Procedure:     Get Fasta sequence from UNIPROT database.     Predict sequence alignment from HHPRED     Prepare INPUT files for MODELLER     model-dimer.py (Click to download) ############### from modeller import * from modeller.automodel import * #from modeller import soap_protein_od env = environ() env.io.hetatm = True a = automodel(env, alnfile='TvLDH-1bdm.ali',               knowns='1bdm',               sequence='TvLDH',               assess_methods=(assess.DOPE,                            ...

Plagarism Checker

Plagiarism is a serious academic misconduct. Whether you are a student writing a college essay, a teacher reviewing a student’s submission, or just someone who works extensively with content, it is important to ensure that the content is not plagiarized. Following are some resources to check Plagiarism. http://www.plagscan.com https://www.plagramme.com/   http://www.plagiarisma.net/fr/# http://www.scanmyessay.com http://www.plagtracker.com http://www.duplichecker.com http://www.smallseotools.com/plagiarism-checker http://www.plagium.com/fr/detecteurdeplagiat http://www.paperrater.com/plagiarism_checker http://www.copyleaks.com http://www.plagiarismchecker.com http://www.quetext.com http://plagiarismdetector.net http://www.solidseotools.com/plagiarism-checker http://www.dustball.com/cs/plagiarism.checker http://www.articlechecker.com http://www.plagiarismcheck.org

Homology model validation

Homology model can be validated in multiple ways. Here you will find useful description on how to validate your homology model. Web-servers: UCLA-DOE LAB — SAVES : The Structure Analysis and Verification Server ( New Link ) This metaserver runs 6 programs for checking and validating protein structures during and after model refinement. PROCHECK : Checks the stereochemical quality of a protein structure by analyzing residue-by-residue geometry and overall structure geometry. WHAT_CHECK : Derived from a subset of protein verification tools from the WHATIF program (Vriend, 1990), this does extensive checking of many sterochemical parameters of the residues in the model.   ERRAT : Analyzes the statistics of non-bonded interactions between different atom types and plots the value of the error function versus position of a 9-residue sliding window, calculated by a comparison with statistics from highly refined structures.   VERIFY_3D : Determines the ...

Science News

Enter your email address:

PhD Vacancy Bioinformatics

PhD Vacancy Chemoinformatics