Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Differential Nycodenz label free (DIA)

ABSTRACT: Mapping the sub cellular proteome using a differential fractionation and an orthogonal nycodenz fractionation combined with quantitative mass spectrometry using Data Independent Acquisition (DIA)

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Rattus Norvegicus (ncbitaxon:10116)

SUBMITTER: Peter Lobel

PROVIDER: MSV000083844 | MassIVE | Thu May 23 10:38:00 BST 2019

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Differential-Nycodenz label free (MS1)

Project description:Mapping the subcellular proteome using a differential fractionation and an orthogonal nycodenz fractionation combined with quantitative mass spectrometry using label free quantification in MS1

2019-05-24 | MSV000083851 | MassIVE

Differential-Nycodenz (TMT-MS3)

2019-05-23 | MSV000083843 | MassIVE

Differential-Nycodenz (TMT-MS2)

2019-05-23 | MSV000083842 | MassIVE

Differential-Nycodenz combined with an orthogonal rate zonal fractionation of M & L differential fractions (MS1)

Project description:Differential-Nycodenz fractionation analyzed with an orthogonal fractionation of two combined differential fractions (Heavy and Light mitochondrial (ML)) using rate zonal centrifugation. Analysis is performed using label free MS1 quantification

2019-05-23 | MSV000083847 | MassIVE

Differential-Nycodenz combined with an orthogonal rate zonal fractionation of M & L differential fractions (TMT_MS3)

2019-05-24 | MSV000083850 | MassIVE

Differential-Nycodenz combined with an orthogonal rate zonal fractionation of M & L differential fractions (TMT_MS2)

2019-05-23 | MSV000083848 | MassIVE

Deep and fast label-free Dynamic Organellar Mapping - DIA datasets

Project description:The Dynamic Organellar Maps (DOMs) approach combines cell fractionation and shotgun-proteomics for global profiling analysis of protein subcellular localization. Here, we have drastically enhanced the performance of DOMs through data-independent acquisition (DIA) mass spectrometry (MS). DIA-DOMs achieve twice the depth of our previous workflow in the same MS runtime, and substantially improve profiling precision and reproducibility. This repository contains all DIA-LFQ benchmark datasets that were measured with our optimized DIA methods: single shot or triple shot on 100 min, 44 min and 21 min gradients.

2023-08-25 | PXD034971 | Pride

Sublingual Microcirculation and Postoperative Ileus

Project description:The aim of this pilot study is to establish if a correlation between sub-lingual microcirculation measured by Orthogonal polarization spectral (OPS) imaging and symptoms of postoperative ileus exist in patients undergoing elective colorectal surgery.

| 2142858 | ecrin-mdr-crc

COSMOS: A Platform for real-time morphology-based, label-free cell sorting using deep learning (scRNA-Seq)

Project description:Cells are the singular building blocks of life, and comprehensive understanding of morphology among other properties is crucial to assessment of underlying heterogeneity. We developed Computational Sorting and Mapping of Single Cells (COSMOS), a platform based on Artificial Intelligence (AI) and microfluidics to characterize and sort single cells based on real-time deep learning interpretation of high-resolution brightfield images. Supervised deep learning models were applied to characterize and sort cell lines and dissociated primary tissue based on high-dimensional embedding vectors of morphology without need for biomarker labels and stains/dyes. We demonstrate COSMOS capabilities with multiple human cell lines and tissue samples. These early results suggest that our neural networks embedding space can capture and recapitulate deep visual characteristics and can be used to efficiently purify unlabeled viable cells with desired morphological traits. Our approach resolves a technical gap in ability to perform real-time deep learning assessment and sorting of cells based on high-resolution brightfield images.

2023-09-25 | GSE241834 | GEO

C. elegans LC-MS/MS analysis by label-free quantification

Project description:Quantitative proteomics mapping by label-free quantification in live C. elegans

2024-11-05 | PXD052493 | Pride