Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mcl-1 is a key determinant of breast cancer cell survival [copy number]

ABSTRACT: Copy number profile of cultured Breast Cancer cell line measured by Affymetrix SNPs microarrays

ORGANISM(S): Homo sapiens

PROVIDER: GSE66070 | GEO | 2015/08/07

SECONDARY ACCESSION(S): PRJNA275814

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Mcl-1 is a key determinant of breast cancer cell survival [copy number]

Project description:Copy number profile of cultured Breast Cancer cell line measured by Affymetrix SNPs microarrays Whole genome copy number profile of 2 breast cancer cell lines were analyzed using Affymetrix SNP6.0 arrays

2015-08-07 | E-GEOD-66070 | biostudies-arrayexpress

Mcl-1 is a key determinant of breast cancer cell survival [expression]

Project description:mRNA expression profile of cultured Breast Cancer cell line measured by Affymetrix microarrays

2015-08-07 | GSE66071 | GEO

Mcl-1 is a key determinant of breast cancer cell survival [expression]

Project description:mRNA expression profile of cultured Breast Cancer cell line measured by Affymetrix microarrays Whole genome expression profile of 32 breast cancer cell lines were analyzed with 3 biological replicates.

2015-08-07 | E-GEOD-66071 | biostudies-arrayexpress

Mcl-1 is a key determinant of breast cancer cell survival

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2015-08-07 | E-GEOD-66072 | biostudies-arrayexpress

Mcl-1 is a key determinant of breast cancer cell survival

Project description:This SuperSeries is composed of the SubSeries listed below.

2015-08-07 | GSE66072 | GEO

Copy Number Variation data from non-trasformed human fibroblasts

Project description:The search for biomarkers to predict radiosensitivity is important not only to individualize radiotherapy of cancer patients but also to forecast radiation exposure risks. The aim of this study was to devise a machine learning method to stratify radiosensitivity and to investigate its association with copy number variations (CNVs) as markers of sensitivity to ionizing radiation. We used the Affymetrix CytoScan HD microarrays to for CNV estimation. Celluar radiosensitivity was measured by the clonogenic surviving fraction at 2 Gy (SF2).

2023-05-08 | GSE231621 | GEO

Copy Number Arrays

Project description:Copy Number Alterations arrays from 21 patients and 24 samples performed by Affymetrix 6.0, Agilent 1M and Oncoscan CNV platforms

| EGAD00010001581 | EGA

Copy number analysis of the murine platelet proteome spanning the complete abundance range

Project description:Knowledge of the identity and quantity of expressed proteins of a cell type is a prerequisite for a complete understanding of its molecular functions. Mass spectrometry (MS)-based proteomics has allowed the identification of the entire protein complement of yeast and the close-to-complete set of proteins expressed in mammalian cell lines. Using recent technological advances we here characterize the proteome of murine platelets, key actors in mediating hemostasis and thrombosis. We accurately measured the absolute protein concentrations of thirteen platelet proteins by SILAC-Protein Epitope Signature Tags (PrESTs) and used them as reference points to estimate the copy number of all proteins of the platelet proteome. To distinguish contaminants such as plasma or erythrocyte proteins from true platelet proteins, we monitored protein abundance profiles across multiple purification steps. In total, we absolutely quantified 4,400 platelet proteins, with estimated copy numbers ranging from less than ten to about a million per cell. Stoichiometries derived from our data correspond well with previous studies. Our study provides a close-to-complete reference map of platelet proteins, which will be useful to the community, for instance for interpreting mouse models of human platelets diseases.

2015-08-18 | PXD000747 | Pride

Genotype, haplotype and copy number variation in worldwide human populations.

Project description:Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis and public release of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with geographic distance from Africa, as expected under a serial founder effect for an out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected—including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas—the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations. Keywords: High Density SNP array

2008-02-05 | GSE10331 | GEO

Genetic Landscape of Copy Number Alterations in Gastric Cancer

Project description:Genome-wide DNA copy number profiling of gastric tumors and matched non-maligant samples. The affymetrix SNP6 array was used to obtain DNA copy number profiles in 193 gastric tumors and 98 matched gastric non-malignant samples.

2012-02-10 | GSE31168 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data