Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mass Spectrometry confirmation of BSA peptide modifications during alkaline sequencing reactions.

ABSTRACT: DDA analysis of samples of commercial tryptic peptides of BSA which had been either untreated ("original"), conjugated with the Harnimarta et al sequencing reagent ("conj") or conjugated and exposed to alkaline cleavage conditions ("seq"). Data was searched in Proteome Discoverer 2.5 using a 58.017 Da for the sequencing reagent dynamic modification. The associated BSA2 fasta includes a synthetic sequence to generate in silico tryptic peptides representing the original BSA tryptic peptides lacking a single N-terminal amino acid.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Bos Taurus (ncbitaxon:9913)

SUBMITTER: Edward Marcotte

PROVIDER: MSV000096402 | MassIVE | Wed Nov 13 09:05:00 GMT 2024

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Proteome sequencing of tobacco yellow leaf mutants

Project description:Subsequently, using a combination of BSA-seq, transcriptomic sequencing (RNA-seq), and proteomic sequencing approaches, we identified the candidate gene Nitab4.5_0008674g0010 that encodes dihydroneopterin aldolase as a factor associated with tobacco leaf yellowing.

2024-06-15 | PXD053162 |

Identification of targets of the protein disulfide reductase thioredoxin

Project description:Identification of targets of the protein disulfide reductase thioredoxin using liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) and thiol specific differential labeling with isotope-coded affinity tags (ICAT). Reduction of specific target disulfides is quantified by measuring ratios of cysteine residues labeled with the heavy (13C) and light (12C) ICAT reagents in peptides derived from tryptic digests of Trx-treated and non-treated samples. Keywords: protein, LC-MS/MS, ICAT

2008-11-20 | GSE11650 | GEO

Nassar2022 - Microbiome sequencing NER model

Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications

2022-02-21 | MODEL2202170012 | BioModels

Next Generation Protein Sequencing

Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.

2017-04-03 | PXD003804 | Pride

A Study of ELI-002 in Subjects With KRAS Mutated Pancreatic Ductal Adenocarcinoma (PDAC) and Other Solid Tumors

Project description:This is a Phase 1 study to assess the safety and efficacy of ELI-002 immunotherapy (a lipid-conjugated immune-stimulatory oligonucleotide [Amph-CpG-7909] plus a mixture of lipid-conjugated peptide-based antigens [Amph-Peptides]) as adjuvant treatment of minimal residual disease (MRD) in subjects with KRAS/neuroblastoma ras viral oncogene homolog (NRAS) mutated PDAC or other solid tumors.

| 2374931 | ecrin-mdr-crc

Mass spectral Analysis of Synthetic Peptides: Implications in Proteomics

Project description:Tryptic synthetic peptides generated in silico from human proteome are used as standards to evaluate the performance of MS and algorithm used to identify the proteins.

2021-01-04 | PXD017992 | Pride

A Study of ELI-002 7P in Subjects With KRAS/NRAS Mutated Solid Tumors

Project description:This is a Phase 1/2 study to assess the safety and efficacy of ELI-002 7P immunotherapy (a lipid-conjugated immune-stimulatory oligonucleotide [Amph-CpG-7909] plus a mixture of lipid-conjugated peptide-based antigens [Amph-Peptides 7P]) as adjuvant treatment in subjects with solid tumors with mutated KRAS/NRAS. This study builds on the experience obtained with related product ELI-002 2P, which was studied in protocol ELI-002-001 under IND 26909.

| 8247 | ecrin-mdr-crc

NovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing

Project description:De novo peptide sequencing is a fundamental research area in mass spectrometry (MS) based proteomics. However, those methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) and the significance of de novo peptide-spectrum matches (PSMs). Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species), and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide sequencing methods on target-decoy spectra and to estimate their FDRs. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide sequencing methods, and how their performances depend on specific applications and the types of data. Our FDR estimation also shows that some tools may perform better than the others in distinguishing between de novo PSMs and random matches, and can be used to assess the significance of de novo PSMs.

2024-08-28 | PXD055277 | Pride

De novo peptide sequencing tools benchmark

Project description:Our study is a large-scale evaluation of de novo peptide sequencing tools using both publicly and proprietary heterogeneous datasets spanning multiple species, mass spectrometers, post-translational modifications, and a wide range of use cases. This dataset contains a publicly available subset of this dataset. The dataset includes raw MS/MS spectra in their original vendor formats as well as in mzML and Mascot Generic Format (MGF). Additionally, peptide spectral hits (PSMs) identified through a database search and rescoring workflow, along with the dataset-specific protein databases used for annotation, are provided.

2024-10-23 | MSV000096182 | MassIVE

Combining de novo peptide sequencing algorithms, a synergistic approach to boost both identifications and confidence in bottom-up proteomics

Project description:Complex MS-based proteomics datasets are usually analyzed by protein database-searches. While this approach performs considerably well for sequenced organisms, direct inference of peptide sequences from tandem mass spectra, i.e. de novo peptide sequencing, oftentimes is the only way to obtain information when protein databases are absent. However, available algorithms suffer from drawbacks such as lack of validation and often high rates of false positive hits (FP). Here we present a simple method of combining results from commonly available de novo peptide sequencing algorithms, which in conjunction with minor tweaks in data acquisition ensues lower empirical FDR compared to the analysis using single algorithms. Results were validated using state-of-the art database search algorithms as well specifically synthesized reference peptides. Thus, we could increase the number of PSMs meeting a stringent FDR of 5% more than threefold compared to the single best de novo sequencing algorithm alone, accounting for an average of 11,120 PSMs (combined) instead of 3,476 PSMs (alone) in triplicate 2 h LC-MS runs of tryptic HeLa digestion.

2019-09-25 | PXD005280 | Pride

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