Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

ABSTRACT: We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.

ORGANISM(S): Homo sapiens

PROVIDER: GSE247519 | GEO | 2024/05/06

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.

2022-12-05 | GSE219047 | GEO

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.

2022-05-18 | GSE201575 | GEO

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

| PRJNA1039282 | ENA

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

| PRJNA832249 | ENA

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

| PRJNA906702 | ENA

A Quantitative Method for Proteome Reallocation Using Minimal Regulatory Interventions

Project description:A Quantitative Method for Proteome Reallocation Using Minimal Regulatory Interventions

| PRJNA554797 | ENA

A Quantitative Method for Proteome Reallocation Using Minimal Regulatory Interventions

Project description:Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a novel approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximises the savings in cell resources. To this end, we categorized Transcription Factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of TFs that maximise the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.

2019-11-30 | GSE134335 | GEO

Proteome-wide effects of single gene perturbations in a eukaryotic cell

Project description:Eukaryotic gene expression is controlled at the transcriptional, translational and protein degradation level and its principles are starting to emerge. While transcriptional outcomes, which are commonly also used as a proxy for protein abundance, have been investigated on a larger scale, the study of translational output requires large-scale proteomics data. However, data for proteome alterations by systematic assessment of knockouts genome-wide is not available yet. We here determined the individual proteome changes for 3,308 non-essential genes in the yeast S. pombe (www.butterlab.org/SpProtQuant). We observed that genes with high proteome remodeling are predominantly involved in gene expression regulation, in particular acting as translational regulators. Focusing on those knockout strains with a large number of altered proteins, we performed paired transcriptome/proteome measurements to uncover translational regulators and features of translational regulation. Furthermore, by similarity clustering of these proteome changes, we infer gene functionality that can be extended to other species such as human or baker’s yeast.

2022-09-20 | GSE167543 | GEO

Reanalysis of Pandey lab's draft of the human proteome

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

Gene-resolution analysis of DNA copy number variation using oligonucleotide expression microarrays

Project description:We present a novel method of using commercial oligonucleotide expression microarrays for aCGH, enabling DNA copy number measurements and expression profiles to be combined using the same platform. This method yields aCGH data from genomic DNA without complexity reduction at a median resolution of approximately 17,500 base pairs. Due to the well-defined nature of oligonucleotide probes, DNA amplification and deletion can be defined at the level of individual genes and can easily be combined with gene expression data. Keywords: genomic DNA, CGH, Copy Number Variation

2007-03-29 | GSE7364 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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