Sentences with phrase «microarray data»

The microarray data are available at http://www.ncbi.nlm.nih.gov/geo under the accession number GSE50674.

Microarray data from an experiment looking at oral - cancer development prompts a conversation in the Public Health Sciences lab of Dr. Chu Chen by (from left) Drs. Lue Ping Zhao, PHS investigator; Chun Cheng, PHS postdoctoral fellow; Chen and Eduardo Mendez of the University of Washington Department of Otolaryngology - Head and Neck Surgery.

«But a major limitation of cluster analysis,» he said, «is that it doesn't use information external to the microarray data - the kinds of things that are important in solving problems of biological interest.»

However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, and the suitability of these methods for single - cell transcriptomics has not been assessed.

Indeed, microarray data confirmed that amiodarone HCL - susceptible NSCs have significantly increased base - line expression of certain ion channels (Table 1, SLC2A1 and CLC1A).

Normalisation and statistical analysis of microarray data was performed in R using the Bioconductor packages Limma, Affy and BeadExplorer.

Researchers performed ES cell cultures, RNA preparations and validated microarray data: IA KA NB PYB MXD MG EK SL MR AR MPS MT. Results were discussed among all Consortium partners.

Our microarray data showed a number of genes in the TNFα pathway were highly expressed in amiodarone HCl - treated NSCs.

The current study included 3,215 RS participants who had both SNP microarray data and 3D MRI.

We analysed the microarray data for other genes that are differentially regulated in Slc6a14 − / − tumours compared with Slc6a14 + / + tumours.

Microarray data are available in the ArrayExpress database under accession number E-MTAB-2163.

Pollard earned a PhD in biostatistics from the University of California, Berkeley, where she developed statistical methods to analyze microarray data in cancer biology.

Principal components analysis of SNP microarray data was used to identify ancestry outliers.

Due to technical limitations, microarray data have issues regarding specificity, discrimination and sensitivity.

Koschmann, J., Bhar, A., Stegmaier, P., Kel, A. E. and Wingender, E. Upstream Analysis: An integrated promoter - pathway analysis approach to causal interpretation of microarray data.

Dr. Li's research interests focus on machine learning, bioinformatics, and statistical data mining in large scale data in biomedical research, such as next generation sequencing data (whole genome sequencing, RNA - seq, microarray data), in the file.

The microarray data (Gene Expression Omnibus accession No.

Furthermore, high ABL1 mRNA was associated with bone metastasis in a microarray data set reporting organ - specific metastasis (Fig. 1F)(18).

At Berkeley, she developed computationally intensive statistical methods for the analysis of microarray data with applications in cancer biology.

This demonstrates the usefulness of our approach for exploiting public microarray data to derive biologically meaningful associations between experimental factors.

The results, which will appear in the Journal of Microbiological Methods, make it clear that the methods used to isolate RNA can have a significant impact on the variability, trend, and accuracy of microarray data.

Comparison of their genomes, integrated with proteomic and microarray data, with the genomes of Plasmodium falciparum and Plasmodium yoelii revealed a conserved core of 4500 Plasmodium genes in the central regions of the 14 chromosomes and highlighted genes evolving rapidly because of stage - specific selective pressures.

All microarray data supporting the findings of this study have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (GEO) and are accessible through the GEO Series accession number GSE86885.

The microarray data were also used to validate the identity of the employed pericyte populations (Supplementary Fig. 1).

The microarray data with the description of the experimental design are deposited under GEO number GSE86885.

Gene Set Enrichment Analysis (GSEA) is a microarray data - mining technique used to determine whether there is coordinated differential expression or «enrichment» in a set of functionally related genes when comparing control and experimental samples [35].

SAM analysis was used to identify statistically significant changes in microarray data, and the bioinformatics programs GoMiner, Gene Set Enrichment Analysis (GSEA), and HiMAP were used to identify significant ontological categories and analyze the N - methyl - D - aspartate (NMDA) receptor interactome.

Microarray data sets for pluripotent cells (PC), EFTF - PC, EF, PNP, LE, and whole embryos (WE) are shown.

GeneTraffic is a bioinformatics server system for microarray data storage and analysis in Minimum Information about a Microarray Experiment (MIAME) compliant format [50].

GOMiner — To provide additional statistical stringency to the identification of potential targets, we then analyzed the data sets generated by the SAM - RS analysis of the microarray data for hypoxia - associated coregulation of multiple, functionally related genes.

For expression analysis in mice, we used microarray data as described above to select two internal control genes, cyclophilin B (Cphn2) and ribosomal protein S3 (Rps3).

Here, we identified genes controlling greening directly downstream of the GATAs by integrating data from RNA - sequencing and microarray data sets.

A: Sheltzer: I was analyzing some microarray data, and I reached the limit of what I knew how to do in terms of data analysis.

They have now used the tools of Social Network Analysis (SNA) to help them unravel the connections and identify the biomarkers present in patient genomic microarray data.

Statistician Ker - Chau Li has found a cubical generalization of the correlation function, which he has used to detect, automatically, candidates for three - way interactions of proteins using microarray data.

The study results challenge the current paradigm of microarray data analysis and suggest that the new method may improve identification of cancer - associated genes.

Jason: I was analyzing some microarray data, and I reached the limit of what I knew how to do, in terms of data analysis.

Lead authors of the study, Ivan P. Gorlov, Ph.D., Associate Professor of Community and Family Medicine and Christopher Amos, Ph.D., Professor of Community and Family Medicine and Director of the Center for Genomic Medicine described a new method to analyze microarray data.

The paper entitled, «How to get the most from microarray data: advice from reverse genomics,» was published online March 21, 2014 in BMC Genomics.

He had spent half of his graduate years working with one small DNA microarray data set, but Millennium Pharmaceuticals in nearby Cambridge was «printing microarrays to beat the band; they had hundreds.»

The Ogretmen laboratory screened previously reported microarray data sets of several human tumor tissues (metastatic head and neck squamous cell carcinoma, melanoma, and renal cell carcinoma) and showed that, in these samples, only the levels of CerS4 were significantly decreased.

The researchers analyzed microarray data of samples from German patients and from an IPF cohort of the Lung Tissue Research Consortium in the U.S.

The original microarray data are publicly available, he notes.

Therefore, before publication, large data sets (including microarray data, protein or DNA sequences, atomic coordinates or electron microscopy maps for molecular and macromolecular structures, and climate data) must be deposited in an approved database and an accession number or a specific access address must be included in the published paper.

Not exact matches

The panel can be used as a tool kit for screening and profiling of functional lncRNAs, or as an accurate quantification to validate functional lncRNAs in microarray or RNA - sequencing data.

In contrast, when the OncoFinder algorithm is applied to the data, a clear correlation between next generation sequencing and microarray gene expression datasets was seen.

Apart from science and engineering, bioinformatics is a vital tool in microarray analysis due to the vast amounts of data that are generated from a microarray experiment.

Microarrays allow researchers to acquire data about expression levels of thousands of genes at one fell swoop.

For instance, the National Center for Biotechnology Information's public repository of gene - expression data, GEO, now contains 392,000 microarray experiments.

The accumulation of adipose tissue macrophages in direct proportion to adipocyte size and body mass may explain the coordinated increase in expression of genes encoding macrophage markers observed in our microarray expression data.