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Gene Chips (DNA Microarrays)
DNA Microarrays
Large-Scale Gene Expression and Microarray Links and Resources
MicroArray related activities at the EBI
Listing of DNA microarray links
Vivian Cheung's group
Microarrays.Org
GRID IT: Resources for Microarray Technology
DNA Microarrays
Microarray & Data Analysis
Gene Chips (DNA Microarrays)
Here are the basics on DNA microarray technology and a list of academic
and industrial links related to this exciting new technology.
DNA Microarrays
Here are some interesting web sites and papers which will introduce you
to one of the more exciting technological beakthroughs in genomics --
DNA microarrays. This site is far from a comprehensive listing, but it
may be a good place to start.
Large-Scale Gene Expression and Microarray Links and Resources
This site is a collection of web resources and pointers to information
on large-scale gene expression studies, and especially microarray
technologies. The links included are biased towards the development and
applications of informatics and bioinformatics for these technologies.
MicroArray related activities at the EBI
These pages are a jumping point to activities at the European
Bioinformatics Institute that focus on microarrays, the gene expression
data that results from them, the issues revolving around the immense
influx of this data, and of course the analysis that one would like to
perform on it.
Listing of DNA microarray links
Vivian Cheung's group
The main focus of our lab is the development of Direct
Identical-by-Descent (IBD) Mapping. Direct IBD Mapping is a DNA
microarray-based mapping technique that allows isolation and mapping of
DNA fragments shared IBD between individuals. It unites two methods,
genomic mismatch scanning (GMS) and DNA microarray technology. GMS
allows physical isolation of IBD DNA fragments between two individuals.
If two individuals have inherited the disease gene(s) from a common
ancestor then the gene(s) should reside within the IBD regions shared
between them. Once isolated the genomic location of the DNA fragments
can be mapped by hybridization onto a DNA microarray that contains
mapped clones arranged in physical map order. By comparing the IBD maps
of sets of affected individuals, we can narrow the candidate gene
region(s).
Microarrays.Org
Welcome to microarrays.org, a new public source for microarraying
information, tools, and protocols.
GRID IT: Resources for Microarray Technology
Microarray & Data Analysis
This is a collection of papers with emphasis on analysis of microarray
(a.k.a. DNA chip) data. General reviews on microarry are occasionally
included. Analysis of gene network is also occasionally included.
However, papers on microarray technology itself are not usually in.
Papers emphasizing results of such analysis are also not in.
Gene Chip Microarray Protocol Websites
Lists of protocols.
Molecular Oncology and Development
Lists of protocols.
NCGR Gene Expression Databases, Analytical Tools
In the table are some of the tools, databases and other resources
that we have reviewed over the last few months.
Software for MicroArray Gene Expression Analysis
I have tested several PC based software packages for the analysis of
microarray data. All packages were demonstration versions with limited
file load/save/print capability and/or a time-limited license, except
ScanAlyze, Cluster and TreeView from Stanford University, which are
freeware. In some cases the lack of saving or printing out the results
made side by side comparison impracticable. Nevertheless the demos
allow an accurate assessment of the capabilities of each package.
GenEx
GenEx TM is a database that allows scientists working with any organism
to internally distribute and visualize gene expression data from
micro-arrays, Affymetrix chips, and related technologies. GenEx TM
allows researchers to publish both text and image files on the web in a
common format that is viewable by other scientists via any web browser.
Publishing is as easy as a right click from within GeneSpring TM.
GeneSpring TM users can also download any experiments published on GenEx
TM to their local desktop in order to leverage the knowledge from these
experiments in combination with there own. After an experiment has been
published, anyone with the correct URL and a web browser can view the
published experiments.
Microarray group at the University of Manchester
Software support for microarray expression analysis.
Gene Network Inference from Large-Scale Gene Expression Data
With the advent of the"Age of Genomics" an entirely new class of data
is emerging. Can we really expect to construct a detailed biochemical
model of, say, an entire yeast cell with some 6000 genes (only about
1000 of which were defined before sequencing started, and about 50% of
which are clearly related to other known genes), by analyzing each gene
and determining all the binding and reaction constants one by one?
Likewise, from the perspective of drug target identification for human
disease, we cannot realistically hope to characterize all the relevant
molecular interactions one-by-one as a requirement for building a
predictive disease model.
There is a need for methods that can handle this data in a global fashion, and that can analyze such large systems at some intermediate level, without going all the way down to the exact biochemical reactions. At the very least, such an analysis could help guide the traditional pharmacological and biochemical approaches towards those genes most worthy of attention among the thousands of newly discovered genes. Ideally, a sufficiently predictive and explanatory model at an intermediate level could obviate the need for an exact understanding of the system at the biochemical level.
Knowledge-based Analysis of Microarray Gene Expression Data Using Support Vector Machines
We introduce a new method of functionally classifying genes using gene
expression data from DNA microarray hybridization experiments. The
method is based on the theory of support vector machines. SVMs are
considered a supervised computer learning method because they exploit
prior knowledge of gene function to identify unknown genes of similar
function from expression data. SVMs avoid several problems associated
with unsupervised clustering methods such as hierarchical clustering
methods and self organizing maps. SVMs have many mathematical features
that make them attractive for gene expression analysis, including their
flexibility in choosing a similarity function, sparseness of solution
when dealing with large data sets, the ability to handle large feature
spaces, and the ability to identify outliers. We test several SVMs that
use different similarity metrics, as well as some other supervised
learning methods, and find that the SVMs best identify sets of genes
with a common function using expression data. Finally, we use SVMs to
predict functional roles for uncharacterized yeast ORFs based on their
expression data.
Data Mining: Making Sense of Gene Expression Data
Worm Chip Directory
The full genome chips have been printed and are now being used for
experiments. These microarrays contain a spot for each gene, plus some
control spots.
Stanford Microarray Database (SMD)
SMD stores raw and normalized data from microarray experiments, as well
as their corresponding image files. In addition, SMD provides
interfaces for data retrieval, analysis and visualization.
ExpressDB
ExpressDB is a relational database containing yeast RNA expression data.
As of July, 1999 it contains 17.5 million pieces of information loaded
from 11 published and in-house expression studies. A manuscript
describing the database and the process of managing and analyzing
expression data has been submitted for publication.
EPODB
EpoDB (Erythropoiesis database) is a database of genes that relate to
vertebrate red blood cells. It includes DNA sequence, structural
features, protein information, gene expression information and
transcription factor binding sites.
The Gene Expression Database (GXD)
GXD integrates the many types of expression data and provides links to
other relevant resources to place the data into the larger biological
and analytical context. The time and space of gene expression is
described by a controlled Dictionary of Anatomical Terms that is part of
the Anatomy Database. For in situ expression assays, the textual
annotations in GXD are complemented by 2 images of original expression
data that are indexed via the terms from the dictionary.
Gene Expression Omnibus (GEO)
In order to support the public use and dissemination of gene expression
data, NCBI has launched the Gene Expression Omnibus. GEO is our effort
to build a gene expression data repository and online resource for the
retrieval of gene expression data from any organism or artificial
source. Gene expression data from multiple platforms, including spotted
microarray (microarray), high-density oligonucleotide array (HDA),
hybridization filter (filter) and serial analysis of gene expression
(SAGE) data, will be accepted, accessioned, and archived as a public
data set. A series of precomputed definitions and descriptions of the
data, as well as online tools for the interactive retrieval and analysis
of this expression data will follow shortly thereafter. It is
anticipated that this repository and resource will become operational
and ready for general submissions in Spring 2000.
The microarray project (uAP)
The Microarray Project is a collaborative research effort between
numerous intramural scientists in multiple Institutes and Divisions of
the National Institutes of Health (NIH), including the National Human
Genome Research Institute (NHGRI), National Center for Biotechnology
Information (NCBI), National Cancer Institute (NCI), National Institute
of Neurological Disorders and Stroke (NINDS), Biomedical Engineering and
Instrumentation Program (BEIP), Division of Computer Research and
Technology (DCRT) and many others.
ArrayDB
ArrayDB 2.1.03 is available in a BETA VERSION.
uArray Database (mAdb)
NCI/DCS uArray Center mAdb Gateway.
ChipDB: A Genome Expression Monitoring Database System
chipDB is a genome expression monitoring database system designed to
allow members of the Young Lab and the yeast research community to
analyze data produced by high-throughput expression monitoring
technologies such as Affymetrix gene chips.
The ArrayExpress Database
The EBI has discussed the possibility of establishing a public
repository for DNA microarray based gene expression data with many of
the major laboratories developing and using these technologies in Europe
and the USA.
Following these discussions, the European Bioinformatics Institute is committed to establishing a public repository for microarray based gene expression data, named ArrayExpress. Currently the EBI is establishing a pilot database containing microarray gene expression data that are available publicly.
RNA Abundance Database (RAD)
Slides for a talk explaining RAD.
GeneX: a Collaborative Internet Database and Toolset for Gene Expression Data
The National Center for Genome Resources and the Computational Genomics
Group at the University of California, Irvine are participating in the
GeneX project to provide an Internet-available repository of gene
expression data with an integrated toolset that will enable researchers
to analyze their data and compare them with other such data. The corpus
of such data will allow more confidence to be placed on the conclusions
reached in this analysis, as well as sharing the considerable cost of
generating these datasets.
Microarray analysis tool(MAT) software
A Microarray data management and analysis software has developed in
AECOM. The following is the data analysis flow chart.
GeneChipLIMS
GeneChip LIMS is a data handling, management, storage, and analysis
package for users who are generating large quantities of GeneChip probe
array data and require a data management solution. This client-server
solution can be integrated into an existing network to provide multiple
end users access to the system. Data is stored in a GATC Since we keep
standard database that can be accessed using the GeneChip Data Mining
Tool or third party vendor mining tools that are GATC-compliant.
LifeArray Software
LifeArray software is an enterprise-wide system that uses a relational
database to store expression data in a central repository. Powerful
query and viewer tools enable individual researchers to perform a
variety of analyses to more quickly identify relevant gene expression
patterns from millions of data points.
Spotfire Array Explorer
Spotfire Array Explorer enables Spotfire Pro users to access expression
data from GATC-compliant databases and to explore and analyze this
complex data in an interactive graphical manner to identify trends,
relationships, anomalies and outliers. Spotfire Pro is a desktop
application that uses the web and a highly interactive graphical
environment to accelerate the discovery process by allowing researchers
to access, analyze and explore complex multi-dimensional data from
disparate sources.
GenomXtools
GenomXtools Basic Sequence Analysis is a set of Visual Genomics
applications for mining bioinformatic data and generating BSML output.
Query Manager analyzes complex databases and creates BSML content for
the visualization of query results. GenomXtools are currently the only
applications available for creating BSML documents as data analysis
products. These tools complement our BSML document authoring and
editing applications.
Reslover
The Resolver system is a turnkey solution for storing,retrieving, and
analyzing large quantities of geneexpression data generated using cDNA
microarrays,oligonucleotide arrays, and other technologies.
Genetic Analysis Technology Consortium (GATC)
Molecular Dynamics and Affymetrix have formed the Genetic Analysis
Technology Consortium (GATC) in an attempt to standardize the rapidly
growing field of array-based genetic analysis, paving the way for the
more affordable and productive development of therapeutic, diagnostic
and disease management products. The consortium was created to provide
a unified technology platform to design, process, read and analyze
DNA-arrays. As a result of the GATC, researchers will benefit as probe
arrays, readers, reagents, and software and database architectures that
are GATC-compliant will be compatible, eliminating the need for
redundant equipment and software.
Gene Expression Markup Language (GEML)
An open-standard XML format for DNA microarray and gene expression data.
The Gene Expression Markup Language (GEML) is a file format for storing DNA microarray and gene expression data. GEML is an open-standard XML format which enables exchange of data between gene expression databases and analysis systems. GEML stores which data collection methodology was used, without making assumptions about the meaning of a measurement. This enables possible normalization, integration, and comparison of data across methodologies. GEML handles expression profile data and allows scan images and chip layouts (or"patterns") to be easily referenced and tracked. GEML is independent of any particular database schema.
Any Comments, Questions? Support@hgmp.mrc.ac.uk