Feng Ge Similar Datasets
Project description:The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides was lacking. To this end, Akhilesh Pandey's lab reported a draft map of the human proteome based on high resolution Fourier transform mass spectrometry-based proteomics technology, which included an in-depth proteomic profiling of 30 histologically normal human samples including 17 adult tissues, 7 fetal tissues and 6 purified primary hematopoietic cells ( http://dx.doi.org/10.1038/nature13302 ). The profiling resulted in identification of proteins encoded by greater than 17,000 genes accounting for ~84% of the total annotated protein-coding genes in humans. This large human proteome catalog (available as an interactive web-based resource at http://www.humanproteomemap.org) complements available human genome and transcriptome data to accelerate biomedical research in health and disease. Pandey's lab and collaborators request that those considering use of this primary dataset for commercial purposes contact pandey@jhmi.edu. The full details of this study can be found in the PRIDE database: www.ebi.ac.uk/pride/archive/projects/PXD000561/. This ArrayExpress entry represents a top level summary of the metadata only which formed the basis of the reanalysis performed by Joyti Choudhary's team ( jc4@sanger.ac.uk ), results of which are presented in the Expression Atlas at EMBL-EBI : http://www.ebi.ac.uk/gxa/experiments/E-PROT-1.
2015-03-10 | E-PROT-1 | biostudies-arrayexpress
Project description:Mass-spectrometry-based draft of the Phaeodactylum proteome
2018-08-26 | PXD042775 |
Project description:Using mass spectrometry-based label-free quantitative (LFQ) proteomics analysis of in vitro differentiated murine Th17 and induced T regulatory (iTreg) cells. More than 4000 proteins covering almost all subcellular compartments were detected. Quantitative comparison of the protein expression profiles resulted in the identification of proteins specifically expressed in the Th17 and iTreg cells. Importantly, our combined analysis of proteome and gene expression data revealed protein expression changes that were not associated with changes at the transcriptional level.
2018-05-31 | GSE104152 | GEO
Project description:The investigation aims to profile the molecular dynamics of Rituximab treatment in cells. Specifically, primary B cells were treated with Rituximab, and sampled across 6 time points. Treated and untreated cells were processed to extract RNA and protein, that were subsequently used in high-throughput analysis of the transcriptome (RNA-Sequencing) and proteome (mass spectrometry).
2018-10-13 | GSE100441 | GEO
Project description:The investigation aims to profile the molecular dynamics of Everolimus treatment in cells. Specifically, a B-lymphoblast cells line was treated with Everolimus and sampled every half-hour over a 12 hour period. Treated and untreated cells were processed to extract RNA and protein that were subsequently used in high-throughput analysis of the transcriptome (RNA-Sequencing) and proteome (mass spectrometry).
2017-09-15 | GSE100359 | GEO
Project description:This ArrayExpress record contains meta-data and results of quantitative analysis of cell lines from the NCI-60 panel using pressure cycling technology (PCT) and SWATH-mass spectrometry. Each cell line was analyzed in duplicate. Raw data files are available at the EMBL-EBI protemics data archive (PRIDE) at accession PXD003539 (http://www.ebi.ac.uk/pride/archive/projects/PXD003539). Since the record here does not include the raw data files and hence there is no need to explicitly link individual replicate to a raw file, each sample is only listed once in the ArrayExpress samples table for clarity.
2017-01-27 | E-PROT-2 | biostudies-arrayexpress
Project description:Recent developments in genomic sequencing technology have enabled comprehensive transcriptome analyses of single cells. In contrast, single cell proteomics analyses have been restricted to targeted analyses, for example using flow cytometry with GFP fusions or mass cytometry. Here, we performed global absolute protein quantification of single Xenopus laevis eggs using mass spectrometry-based proteomics. We quantified over 5800 proteins, thus representing the largest single cell proteome that has been characterized to date. Absolute protein amounts in single eggs are highly comparable, thus indicating a tight regulation of global protein abundance. Comparison between the single-cell proteome and transcriptome reveal poor expression correlation. Finally, we identified 439 proteins that significantly change in abundance during early embryogenesis. Many of these proteins do not show regulation at the transcript level. Altogether, our data reveal that the transcriptome is a poor indicator of the proteome and that protein levels are tightly controlled in Xenopus leavis eggs. RNA-seq in Xenopus laevis of 5 replicates of both single eggs and single embryos.
2014-08-04 | E-GEOD-56586 | biostudies-arrayexpress
Project description:Technological advances have enabled the analysis of cellular protein and RNA levels with unprecedented depth and sensitivity, allowing for an unbiased re?evaluation of gene regulation during fundamental biological processes. Here, we have chronicled the dynamics of protein and mRNA expression levels across a minimally perturbed cell cycle in human myeloid leukemia cells using centrifugal elutriation combined with mass spectrometry?based proteomics and RNA?Seq, avoiding artificial synchronization procedures.
2014-10-23 | E-ERAD-336 | biostudies-arrayexpress
Project description:Mass spectrometry-based proteomic landscape of rice reveals a post-transcriptional regulatory role of N6-methyladenosine
| PRJNA954025 | ENA
Project description:The investigation aims to profile the molecular dynamics of Rituximab treatment in cells. Specifically, a B-lymphoblast cells line was treated with Rituximab, and sampled every hour over a 24hour period. Treated and untreated cells were processed to extract RNA and protein that were subsequently used in high-throughput analysis of the transcriptome (RNA-Sequencing) and proteome (mass spectrometry). We expect our approach not only to provide a unique reference dataset to the scientific community but to also act as a paradigm as an approach to identify novel transcriptome-proteome molecular markers utilized in mapping drug action pathways. We have identified specific expression at both the gene and protein levels and are inferring associations between the omics through the use of temporal pattern identification, thus defining time-varying networks. This study will provide the next steps in the development of reference dynamic omics data that may be used in creating integration models, with further applications in dynamic monitoring of samples in precision medicine implementation.
2017-09-15 | GSE89062 | GEO