Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

GNPS - Deep Neural Networks for Classification of LC-MS Spectral Peaks

ABSTRACT: Files associated with the manuscript "Deep Neural Networks for Classification of LC-MS Spectral Peaks"

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Mohit Jain

PROVIDER: MSV000084186 | GNPS | Thu Aug 08 17:12:00 BST 2019

REPOSITORIES: GNPS

ACCESS DATA

Json Xml

Similar Datasets

Deep Neural Networks for Classification of LC-MS Spectral Peaks

Project description:Files associated with the manuscript "Deep Neural Networks for Classification of LC-MS Spectral Peaks"

2019-08-08 | MSV000084186 | MassIVE

Deep Neural Networks for Classification of LC-MS Spectral Peaks.

Project description: Not available

| S-EPMC7089603 | biostudies-literature

inSPIRE Spectral Rescoring Tool

Project description:inSPIRE is an open-source tool for spectral rescoring of mass spectrometry search results. For this project, inSPIRE was applied to MaxQuant, PEAKS DB, and Mascot search results from a tryptic digestion of the K562 proteome. Here we provide the RAW files and search results using MaxQuant, PEAKS DB, and Mascot. We also reprocessed RAW data from the PXD031709 and PXD031812 repositories for which we provide the search result files. Additionally, we provide PEAKS search results from RAW files from the PXD015489 repository which was used as training data for a predictor used within inSPIRE. Michele Mishto, Head of the research group Molecular Immunology at King’s College London and the Francis Crick Institute, London (UK). Email: michele.mishto@kcl.ac.uk,

2022-10-26 | PXD034056 | Pride

SPECtre: a spectral coherence-based classifier of actively translated transcripts from ribosome profiling sequence data

Project description:Active protein translation can be assessed and measured using ribosome profiling sequencing strategies. Existing approaches make use of sequence fragment length or frame occupancy to differentiate between active translation and background noise, however they do not consider additional characteristics inherent to the technology which limits their overall accuracy. Here, we present an analytical tool that models the overall tri-nucleotide periodicity of ribosomal occupancy using a classifier based on spectral coherence. Our software, SPECtre, examines the relationship of normalized ribosome profiling read coverage over a rolling series of windows along a transcript against an idealized reference signal. A comparison of SPECtre against current methods on existing and new data shows a marked improvement in accuracy for detecting active translation and exhibits overall high sensitivity at a low false discovery rate. Classification of actively translated transcripts in ribosome profiling data derived from human neuroblastoma SH-SY5Y cells, and data previously published derived from mouse embryonic stem cells and zebrafish embryos.

2016-07-01 | E-GEOD-75947 | biostudies-arrayexpress

Deep metaproteomics of inflammatory bowel diseases

Project description:Inflammatory bowel disease (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), is associated with a loss or an imbalance of host-microbe interactions. Depletion-assisted deep metaproteomics was employed to reveal disease-specific networks of host-microbial protein associations in IBD.

2023-06-28 | PXD043380 | iProX

Direct data-independent acquisition proteomics with in silico spectral libraries by deep learning

Project description:Data-independent acquisition (DIA) proteomics allows systematic and unbiased measurement of protein samples and enables fast quantitative analysis of large cohorts of samples. However, sample-specific spectral libraries are usually required prior to perform DIA experiments. The libraries are built by data-dependent acquisition (DDA) proteomic analysis on the same samples normally with pre-fractionation, which is time-consuming and limits the identification/quantification by DIA to the peptides identified by DDA. Herein, we propose DeepDIA, a deep learning based approach to generate in silico spectral libraries for DIA analysis. We benchmarked DeepDIA with HeLa and mixed proteome data sets, showing that the quality of in silico spectral libraries is comparable to that of experimental spectral libraries. We further demonstrated that DeepDIA can be performed on human cell lines and human serum without pre-knowledge of peptides lists by DDA experiments. Compared to the state-of-the-art protocol using DDA-based spectral library with high abundance protein depletion and pre-fractionation, the number of identified and quantified proteins from human serum was increased by >100% using DeepDIA. Accuracy of the identification results was validated using a standard mixture containing >800 stable isotope labelled reference peptides from >500 proteins in human plasma. We expect this work contributing to the studies of quantitative proteomics and especially blood proteomics, whereas expanding the toolbox for DIA proteomics.

2019-12-02 | PXD014108 | iProX

Generation of a deep mouse brain spectral library for transmembrane proteome profiling in mental disease models

Project description:The establishment of a high-quality mouse brain transmembrane proteins spectral library enables in-depth profiling of the proteins across multiple brain regions. DIA data analysis, combining different search pipeline based on the spectral library, discovered a new GPCR regulator which was associated with depression verified via in vivo tests. This library represents a valuable resource that has the potential to discover the putative drug targets.

2023-11-26 | PXD047251 | iProX

Prediction of glycopeptide fragment mass spectra by deep learning

Project description:Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the non-linear glycan structure in an intact glycopeptide. Herein, we propose a deep learning-based approach for the prediction of fragment spectra of intact glycopeptides. Our model adopts tree-structured long-short term memory networks to process the glycan moiety and a graph neural network architecture to incorporate potential fragmentation pathways of a specific glycan structure. This feature is beneficial to model explainability and differentiation ability of glycan structural isomers. We further demonstrated that predicted spectral libraries can be used for analyzing DIA data of glycopeptides as a supplement for library completeness. We expect that this work will provide a valuable deep learning resource for glycoproteomics.

2023-12-17 | PXD045248 | iProX

Photoperiodic spectral tuning of carbon metabolism in heterotrophic marine flavobacteria

Project description:Photoperiodic spectral tuning of carbon metabolism in heterotrophic marine flavobacteria

| PRJNA532887 | ENA

Multicolor spectral flow cytometry evaluation of peripheral blood mononuclear cells from NSCLC patients

Project description:To investigate a non-invasive strategy for immune monitoring the peripheral blood by flow cytometry, to address the critical need to itdentify predictive immunological biomarkers that correlate with treatment response Peripheral blood mononuclear cells (PBMCs) from 19 non–small-cell lung cancer (NSCLC) patients before and after ICI treatment and four healthy human donors were evaluated, utilizing spectral flow to monitor 24 immune cell markers simultaneously over the course of treatment. We performed immune cell profiling analysis using data obtained from RNA-seq of 19 different patients before and after immunotherapy, to validate the multi-color flow based immune profiling

2023-08-03 | GSE235048 | 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