Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Global Protein-Ligand Binding Affinity Profiling via Photocatalytic Labeling

ABSTRACT: Submission for manuscript "Global Protein-Ligand Binding Affinity Profiling via Photocatalytic Labeling" Files contained within the folder "Raw MS Files" are raw spectrum files (.d) from a timsTOF Pro 2 mass spectrometer, these files were processed using DIANN using the provided FASTA file and in silico spectral library in the folder "DIANN_in_sillico_library_FASTA" and processed according to methods outlined in the submission supplemental files. The protein level quantification (report.pg_matrix.tsv) and peptide level quantitation files (report.pr_matrix.tsv) are provided in the folder "DIANN_Results."

INSTRUMENT(S): timsTOF Pro 2

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

SUBMITTER: Jacob B. Geri

PROVIDER: MSV000096433 | MassIVE | Fri Nov 15 20:21:00 GMT 2024

SECONDARY ACCESSION(S): PXD057955

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Bulk RNA-seq profiling of pleural mesothelioma and comparator pleural specimens

Project description:This GEO submission contains processed bulk RNA sequencing data generated from pleural mesothelioma tumors and comparator pleural specimens. Raw sequencing data are available through controlled access in dbGaP under accession phs004285. Processed gene expression matrices and sample-level metadata for the bulk RNA-seq libraries are provided in this submission.

2026-04-07 | GSE327166 | GEO

Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens

Project description:This GEO submission contains processed single-cell RNA sequencing data generated using the Seq-Well platform from pleural mesothelioma tumors and comparator pleural specimens. Raw sequencing data are available through controlled access in dbGaP under accession phs004285. Processed expression matrices and cell-level metadata for the single-cell libraries are provided in this submission.

2026-04-07 | GSE327167 | GEO

scRNA-seq of a knockout village during hPSC-derived islet differentiation

Project description:This submission consists of processed single-cell RNA-seq data of knockout village samples, provided as filtered feature–barcode matrices generated using Cell Ranger v7.1.0 with default parameters. We previously deposited the same biological samples and data processed by STAR under GEO accession GSE288587. The corresponding raw FASTQ files are available in ENA under accession ERP168459. The supplementary file (reanalysis_samples.xlsx) provides a reference table linking each sample in this submission to its corresponding GSM in GSE288587, which contains the detailed experimental descriptions of culture information, genotypes, and differentiation stages.

2025-12-12 | GSE313516 | GEO

Efficacy, safety, and spatial transcriptomic rationale of orelabrutinib plus obinutuzumab in marginal zone lymphoma

Project description:This submission contains raw 10x Genomics Visium HD Spatial Gene Expression FASTQ files from three FFPE mucosa-associated lymphoid tissue lymphoma samples analyzed in the O2 marginal zone lymphoma study. Processed Space Ranger and downstream spatial transcriptomics files will be added before final GEO release. Submitter contact email: lcxujiadai@163.com.

2026-07-15 | GSE337521 | GEO

The landscape of protein expression in cancer based on public proteomics data

Project description:This project contains raw data, intermediate files and results used to create the integrated map of protein expression in human cancer (including data from cell lines and tumours). The map is based on joint reanalysis of 11 large-scale quantitative proteomics studies. The datasets were primarily retrieved from the PRIDE database, as well as MassIVE database and CPTAC data portal. The raw files were manually curated in order to capture mass spectrometry acquisition parameters, experimental design and sample characteristics. The raw files were jointly processed with MaxQuant computational platform using standard settings (see Data Processing Protocol). Due to size of the data, the processing was done in two batches denoted as “celllines” and “tumours” analysis. In total, using a 1% peptide spectrum match and protein false discovery rates, the analysis allowed identification of 21,580 protein groups in the cell lines dataset (MQ search results available in ‘txt-celllines’ folder), and 13,441 protein groups in the tumours dataset (MQ search results available in ‘txt-tumours’ folder).

2019-07-18 | PXD013455 | Pride

The human phosphoproteome map based on PRIDE data

Project description:This project contains raw data, intermediate files and results used to create the PRIDE human phosphoproteome map. The map is based on joint reanalysis of 110 publicly available human datasets. All relevant datasets were retrieved from the PRIDE database, and after manual curation, only assays that employed dedicated phospho-enrichment sample preparation strategies (e. g. metal oxide affinity chromatography, anti-P-Tyr antibodies, etc.) were included. Raw files were jointly processed with MaxQuant computational platform using standard settings (see Data Processing Protocol). In total, the joint analysis allowed identification of 252,189 phosphosites at 1% peptide spectrum match false discovery rate (PSM FDR) (MQ search results available in ‘txt-100PTM’ folder), of which 121,896 passed the additional 1% site localization FDR threshold (MQ search results available in ‘txt-001PTM’ folder).

2019-02-13 | PXD012174 | Pride

Molecular and clinicopathologic characteristics of CNS tumors with BCOR::EP300 gene fusions

Project description:Genomewide DNA methylation array profiling of 37 BCOR altered tumors and 37 non-BCOR altered tumors to study the rare tumor entity of EP300::BCOR fusion in central nervous system. The raw methylation idat files and processed beta values were provided here.

2022-10-09 | GSE211156 | GEO

Integrated spatial transcriptomics (Stereo-seq) and bulk RNA-seq of cardiac sonogenetics in rodent heart tissue across time points [Stereo-seq]

Project description:This GEO Series contains two complementary transcriptomic datasets generated to study cardiac sonogenetics in rodent heart tissue. First, spatial transcriptomics was performed using Stereo-seq (SAW v8.1.3) to generate spatially resolved gene-expression maps from heart sections, providing GEF outputs, tissue images, and associated QC files. Second, bulk RNA-seq was performed on matched heart tissue samples from wild-type (WT) and sonogenetic (MscL-G22S) groups across multiple time points to quantify gene-level expression changes at the whole-tissue level. Raw sequencing files (FASTQ) and processed expression matrices (counts/TPM tables) are provided for both assays. Together, these datasets enable cross-validation of spatially localized transcriptional patterns with bulk gene-expression measurements.

2026-03-17 | GSE324075 | GEO

Integrated spatial transcriptomics (Stereo-seq) and bulk RNA-seq of cardiac sonogenetics in rodent heart tissue across time points [RNA-Seq]

2026-03-17 | GSE324074 | GEO

MELK inhibition promotes megakaryopoiesis and platelet recovery in immune thrombocytopenia through ERK–cofilin signaling

Project description:Maternal embryonic leucine zipper kinase (MELK) has been implicated in cell-cycle regulation, yet its transcriptional programs in megakaryocytic cells remain incompletely defined. To profile MELK-dependent gene expression changes, we performed bulk RNA-seq on the human megakaryoblastic cell line MEG-01 transduced with a control pLKO.1 vector or a MELK-targeting shRNA (sh2-MELK), with three independent biological replicates per condition. Paired-end sequencing reads (raw FASTQ files) and processed gene-level expression quantifications are provided to support differential expression and pathway analyses of MELK knockdown in megakaryocytic cells.

2026-04-02 | GSE322507 | 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