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Research supplier
UCLA Technology Center for Genomics & Bioinformatics
UCLA Technology Center for Genomics & Bioinformatics is listed as an academic core research supplier in the Scientist.com network, with 1 site in 1 country.
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Services
What this research supplier says it provides, as listed in the Scientist.com network.
Type of company: Academic core
Biomarkers
- Genomics Genomic services including applications to DNA (*sanger sequencing, whole genome amplification, library screening, cloning, sub-cloning, and DNA isolation*) and RNA (*microRNA analysis, RNA isolation, qRT-PCR, mRNA...
Data Science/Bioinformatics
- In Silico Nucleic Acid Microarray Analysis Use software to visualize and evaluate gene activity in response to various stimuli.
- In Silico Protein Microarray Analysis Use software to visualize and evaluate protein function and expression on a large scale.
DNA & RNA
- Amplified Fragment Length Polymorphism Detection Detect DNA polymorphisms based upon restriction enzyme digestion and PCR.
- ATAC-seq ATAC-seq
- ChIP-Sequencing Use chromosome immunoprecipitation to identify DNA-protein binding sites in a genome.
- DNA Extraction Extract DNA from an original source.
- DNA Hydroxy Methylation Seq Use epigenetic services to analyze genome-wide DNA hydroxymethylation.
- Exome Sequencing Determine protein-coding nucleotide sequences in a DNA sample.
Show all 17 in DNA & RNA
- Expression Profiling Measure the the expression of thousands of genes at once to create a global picture of cellular function.
- Genomic DNA Purification Isolate genomic DNA from cells or tissue samples.
- Methylation Analysis Determine genomic methylation patterns and analyze methylation in tumors and treated samples.
- NGS: Next Generation Sequencing Sequence millions of template DNA molecules in parallel.
- qPCR Analysis Measure the accumulation of PCR products in real time.
- Quantitative RT PCR Use quantitative reverse transcription polymerase chain reaction to measure absolute and relative mRNA abundance.
- RNA Extraction Isolate total RNA or mRNA from cells or tissues
- RNA Sequencing Use Next Generation Sequencing techniques to Identify RNA transcripts, examine differential expression patterns and analyze splice variants.
- SNP Characterization Identify single nucleotide polymorphisms to make genetic associations, analyze disease SNPs and determine LOH.
- Whole Genome Bisulphite Seq Profile genome-wide DNA methylation.
- Whole Genome Sequencing Determine the entire genetic make-up of an organism.
Scientific Data Services
- In Silico Genomics/Transcriptomics Data Analysis Interpret DNA sequencing and microarray data.
Other services
- New Request
Where it operates
Sites by country, with the cities in each.
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United States 1 site
About this supplier
In the supplier's own words, as listed in the Scientist.com network.
For gene expression arrays, we offer differential two group and multigroup gene expression analysis, and identify statistically, differentially expressed genes between the different conditions the users are comparing, using statistical criteria appropriate for the dataset size. For typical two group comparisons, the repeats of each conditions are analyzed compared to identify differentially expressed genes by a fold change analysis and t-test criteria. Multiple testing, and a multiple testing correction is applied to the data, and a measure of false discovery determined by permutation...
Show the full description
For gene expression arrays, we offer differential two group and multigroup gene expression analysis, and identify statistically,
differentially expressed genes between the different conditions the users are comparing, using statistical criteria appropriate for the
dataset size.
For typical two group comparisons, the repeats of each conditions are analyzed compared to identify differentially expressed genes by a fold
change analysis and t-test criteria. Multiple testing, and a multiple testing correction is applied to the data, and a measure of false
discovery determined by permutation analysis. Microarray experiments simultaneously monitor expression levels of thousands of genes, giving
a large multiplicity issue which needs to be corrected. Further, genes that have low expression are more difficult to distinguish.
(If there are no replicates per condition (i.e. 2 samples, 1 condition each) a fold change analysis is used to generate the gene lists.
Replicates are recommended, in order to get statistical results.)
Genes are returned to the users in an excel spread sheet with gene symbol, fold change, and pvalue.
Heat maps are also provided to visualize the differentially expressed genes.
Differentially expressed genes are further analyzed for enriched biological themes and pathways using the GeneGo software package.
The genes can also be analyzed with the text-mining software Literature Lab, that analyzes lists of genes to determine associations
with biological and chemical terms from the literature.
For DNA microarrays, a copy number analysis is provided. Data are normalized, copy number is computed and segmented, and loss of
heterozygosity is calculated. Data are also visualized in order to see gains and losses across chromosomes.
- Website
- www.pathology.ucla.edu/tcgb
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