Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Hs_Hela_AspN_HCD

ABSTRACT: Human hela proteome, AspN HCD

REANALYSIS of: PXD000900

INSTRUMENT(S): QExactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Others

SUBMITTER: Guo X, Trudgian DC, Lemoff A, Yadavalli S, Mirzaei H

PROVIDER: PAe005048 | PeptideAtlas | 2014-12-31

REPOSITORIES: PeptideAtlas

ACCESS DATA

Json Xml

Publications

Confetti: a multiprotease map of the HeLa proteome for comprehensive proteomics.

Guo Xiaofeng X Trudgian David C DC Lemoff Andrew A Yadavalli Sivaramakrishna S Mirzaei Hamid H

Molecular & cellular proteomics : MCP 20140402 6

Bottom-up proteomics largely relies on tryptic peptides for protein identification and quantification. Tryptic digestion often provides limited coverage of protein sequence because of issues such as peptide length, ionization efficiency, and post-translational modification colocalization. Unfortunately, a region of interest in a protein, for example, because of proximity to an active site or the presence of important post-translational modifications, may not be covered by tryptic peptides. Detec ...[more]

PMID: 24696503

Similar Datasets

Gene expression analysis of Aspn+/+ and Aspn-/- fetal MSCs [mouse]

Project description:Gene expression analysis of Aspn+/+ and Aspn-/- fetal MSCs

2020-04-13 | GSE109642 | GEO

Project description:MT-HCD

| PRJNA1035014 | ENA

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 expression analysis of Aspn+/+ and Aspn-/- fetal MSCs [mouse]

Project description:Gene expression analysis of Aspn+/+ and Aspn-/- fetal MSCs [mouse]

| PRJNA431587 | ENA

Profiling proteome-scale antibody responses to M. tuberculosis proteins in TB suspect's sera

2012-07-06 | GSE30722 | GEO

Profiling proteome-scale antibody responses to M. tuberculosis proteins in sera of macaques infected with M. tuberculosis

2012-07-06 | GSE30721 | GEO

Profiling proteome-scale antibody responses to M. tuberculosis proteins in sera of macaques infected with M. tuberculosis

Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression. To investigate antibody responses during the course of infection, we probed M. tuberculosis proteome microarrays with serial sera collected from experimentally infected cynomolgus macaques. Based on infection outcome, the macaques were grouped into three classes; A) active disease (n = 4), B) latent infection (n=5) and C) reactivation disease (n = 5). Note that the macaques in the reactivation class developed signs of disease spontaneously without any experimental intervention. For each animal, we tested one pre-infection time point and approximately ten post-infection time points at one-month intervals.

2012-07-05 | E-GEOD-30721 | biostudies-arrayexpress

HDCA binding proteins

Project description:To elucidate the molecular mechanism behind the anti-NAFLD effect of HDCA, we screened for potential HDCA binding proteins using biotin-labeled HDCA and HuProt human proteome microarray.

2023-08-17 | GSE241065 | GEO

MOTS-c peptide binding protein

Project description:To elucidate the molecular mechanism of MOTS-c against NASH progression, we screened for potential MOTS-c binding proteins using biotin-labeled MOTS-c and HuProt human proteome microarray.

2024-01-18 | GSE253264 | GEO

Transcription profiling by high throughput sequencing of HeLa human cancer cell line

Project description:Illumina single-end sequencing of Hela_2 (HeLa cell line). While the number and identity of proteins expressed in a single human cell type is currently unknown, this fundamental question can be addressed by advanced mass spectrometry (MS)-based proteomics. On-line liquid chromatography coupled to high resolution MS and MS/MS yielded more than 150,000 unique peptides that identified more than 10,000 different human proteins encoded by more than 9,000 human genes. Deep transcriptome sequencing revealed transcripts for nearly all detected proteins. We show that the abundances of more than 90% of proteins and transcripts fall within a 10,000-fold range, and allocate the proteome to different compartments, complexes and functions. Comparisons of the proteome and the transcriptome, and analysis of protein complex databases and GO categories, suggest that we achieved almost complete coverage of the functional transcriptome and the proteome of a single cell type.

2011-11-12 | E-MTAB-823 | biostudies-arrayexpress

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