Weber Andrew A - OmicsDI

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Transcriptomics (23)
Genomics (12)
Unknown (12)
Metabolomics (6)
Proteomics (3)

Organisms

Homo sapiens (27)
Mus musculus (6)
Arabidopsis thaliana (2)
Vibrio cholerae (1)
Caenorhabditis elegans (1)

Repository

biostudies-arrayexpress (25)
EGA (10)
MetaboLights (6)
MassIVE (1)
PanoramaPublic (1)
pride (1)

Tissue

Lymph node (1)

Technology Type

Mass spectrometry (5)
Illumina HiSeq 2000, Illumina Infinium HumanMethylation450 BeadChip, Affymetrix expression array, ILLUMINA (1)
Mass spectrometry assay (1)
NMR spectroscopy (1)
Bottom-up proteomics (1)
Mass Spectrometry (1)

Instrument Platform

Illumina NovaSeq 6000 (15)
Illumina HiSeq 2500 (3)
N/A (2)
NextSeq 500 (2)
Liquid Chromatography MS - negative - hilic (2)
Liquid Chromatography MS - negative - reverse phase (2)
Liquid Chromatography MS - positive - hilic (2)
Q Exactive (2)
ShARC (1)
Agilent 2100 (1)
Illumina-compatible library preparation equipment (1)
Monarch RNA purification column system (1)
Standard mammalian cell culture equipment (1)
Maxwell® 16 AS2000 (1)
NextSeq 2000 (1)
DNBSEQ-T7 (1)
Orbitrap Fusion Lumos (1)
Gas Chromatography MS - positive (1)
Liquid Chromatography MS - negative (1)
Liquid Chromatography MS - positive (1)
Liquid Chromatography MS – negative - hilic (1)
Liquid Chromatography MS – positive - reverse phase (1)
Nuclear Magnetic Resonance (NMR) - (1)

Publication Date

2025 (13)
2026 (12)
2020 (3)
2011 (1)
2009 (1)
2022 (1)
2023 (1)
2024 (1)

CHEBI ID

CHEBI:16027 (2)
CHEBI:16335 (2)
CHEBI:17126 (2)
CHEBI:17368 (2)
CHEBI:17509 (2)
CHEBI:17568 (2)
CHEBI:18186 (2)
CHEBI:25017 (2)
CHEBI:25094 (2)
CHEBI:27470 (2)
CHEBI:10138 (1)
CHEBI:10565 (1)
CHEBI:1148 (1)
CHEBI:116314 (1)
CHEBI:15354 (1)
CHEBI:15365 (1)
CHEBI:15366 (1)
CHEBI:15383 (1)
CHEBI:15428 (1)
CHEBI:15613 (1)
CHEBI:15676 (1)
CHEBI:15698 (1)
CHEBI:15713 (1)
CHEBI:15727 (1)
CHEBI:15727, CHEBI:57485 (1)
CHEBI:15729 (1)
CHEBI:15741 (1)
CHEBI:15756 (1)
CHEBI:15760 (1)
CHEBI:15811 (1)

Metabolite Name

(+)-Pyroglutamic acid (1)
(+/-)-Pipecolate (1)
(+/-)-Propionylcarnitine chloride (1)
(-)-Tetradecanoylcarnitine (1)
(10E)-12-Oxododecenoic acid (1)
(10E,12Z,15Z)-9-hydroxyoctadeca-10,12,15-trienoic acid (1)
(13S)-Hydroxyoctadecadienoate (1)
(1s,3z)-3-[(2e)-2-[(1r,3ar,7as)-7a-Methyl-1-[(2r)-6-Methylheptan-2-Yl]-2,3,3a,5,6,7-Hexahydro-1h-Inden-4-Ylidene]ethylidene]-4-Methylidene-Cyclohexan-1-Ol (1)
(2-hydroxy-3-stearoyloxy-propyl) 2-(trimethylammonio)ethyl phosphate (1)
(2E)-2-Phenyl-2-propenoic acid (1)
(2E)-3-(1H-imidazol-4-yl)prop-2-enoic acid (1)
(2R,3R,4S,5S,6R)-2-[[(2R,3S,4S,5R,6R)-6-[(2R,3R,4S,5R,6R)-6-[(2S,3S,4R,5S)-3,4-dihydroxy-2,5-bis(hydroxymethyl)oxolan-2-yl]oxy-4,5-dihydroxy-2-(hydroxymethyl)oxan-3-yl]oxy-3,4,5-trihydroxy-oxan-2-yl]methoxy]-6-(hydroxymethyl)oxane-3,4,5-triol (1)
(2S)-1-[(2S)-2-azaniumyl-3-phenyl-propanoyl]pyrrolidine-2-carboxylate (1)
(2S)-1-[(2S)-5-amino-2-[[(2S)-2-amino-4-methyl-pentanoyl]amino]-5-keto-pentanoyl]proline (1)
(2S)-2-(methylamino)Pentanedioic acid (1)
(2S)-2-Amino-3-methylbutanoic acid (1)
(2S)-2-[[(4S)-4-amino-4-carboxy-butanoyl]amino]-4-methyl-pentanoic acid (1)
(2S)-2-amino-5-[[(1S)-1-carboxy-2-methyl-propyl]amino]-5-oxo-pentanoic acid (1)
(2S)-3-(5-mercapto-3-methyl-imidazol-4-yl)-2-(methylammonio)propionate (1)
(2S,3R)-(-)-Threonine (1)
(2S,3R)-2-[[[[9-[(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)-2-oxolanyl]-6-purinyl]amino]-oxomethyl]amino]-3-hydroxybutanoic acid (1)
(2S,3S)-alpha-Amino-beta-merthyl-n-valerate (1)
(2S,3S,4R)-2-aminohexadecane-1,3,4-triol (1)
(3R)-3-[(Z)-octadec-9-enoyl]oxy-4-(trimethylazaniumyl)butanoate (1)
(3R,3'S)-3,3'-Dihydroxy-beta,beta-carotene-4,4'-dione (1)
(3S,6S)-3-Benzyl-6-(2-methylpropyl)piperazine-2,5-dione (1)
(4S)-4-amino-5-[[(1S)-1-carboxyethyl]amino]-5-keto-valeric acid (1)
(6R)-6-[(3R,5S,7R,8R,9S,10S,13R,14S,17R)-3,7-dihydroxy-10,13-dimethyl-2,3,4,5,6,7,8,9,11,12,14,15,16,17-tetradecahydro-1H-cyclopenta[a]phenanthren-17-yl]-2-methylheptanoic acid (1)
(9Z)-octadec-9-enamide (1)
(9Z,12Z)-octadeca-9,12-dienoic acid [1-(anilinomethyl)-2-[(9Z,12Z,15Z)-octadeca-9,12,15-trienoyl]oxy-ethyl] ester (1)

Study type

RNA-seq of coding RNA (9)
RNA-seq of total RNA (4)
RNA-seq of coding RNA from single cells (3)
Transcription profiling by array (2)
Spatial transcriptomics by high-throughput sequencing (1)
ATAC-seq (1)
Hi-C (1)
Ribo-seq (1)
Single nucleus RNA sequencing (1)
ChIP-seq (1)
Methylation profiling by high throughput sequencing (1)

Release Date

2025 (13)
2026 (12)
2020 (4)
2018 (2)
2011 (1)
2009 (1)
2024 (1)
2023 (1)
2016 (1)
2015 (1)

Lab affiliation

Section Mass Spectrometry and Proteomics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (1)

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Characterisation of monophasic solvent-based tissue extractions for detection of polar metabolites and lipids applying UHPLC-MS clinical metabolic phenotyping assays

Metabolic phenotyping of tissues uses metabolomics and lipidomics to measure the relative polar and non-polar (lipid) metabolite levels in biological samples. This approach aims to understand disease biochemistry and identify biochemical markers of disease. Sample preparation methods must be repr...

2020-09-28 | MTBLS1707 | MetaboLights

Simultaneously discovering the fate and biochemical effects of pharmaceuticals through untargeted metabolomics

Untargeted metabolomics is an established approach in toxicology for characterising endogenous metabolic responses to xenobiotic exposure. Detecting the xenobiotic and its biotransformation products as part of the metabolomics analysis provides an opportunity to simultaneously gain deep insights int...

2023-07-03 | MTBLS2746 | MetaboLights

Assessment of human plasma and urine sample preparation for re-producible and high-throughput UHPLC-MS clinical metabolic phenotyping

Clinical metabolic phenotyping employs metabolomics and lipidomics to detect and measure thousands of metabolites and lipids within human samples. This approach aims to identify metabolite and lipid changes between phenotypes (e.g. disease status) that aid understanding of biochemical mechanisms ...

2020-08-06 | MTBLS1465 | MetaboLights

Experimental and computational approaches for deep metabolome annotation with application to the ecotoxicological model organism Daphnia magna

Identifying metabolomes with greater coverage and confidence is a critical step towards interpreting the metabolic basis of human and environmental health. Yet for over two decades the field of metabolomics has been inhibited by limited metabolite identification. To address this, we developed the...

MTBLS2273 | MetaboLights

Regional HNSCC metabolomics reveals widespread changes to one-carbon metabolism and S-adenosylmethionine metabolism across tumour core, tumour edge and adjacent non-tumour tissues

Cancer, including head and neck squamous cell carcinoma (HNSCC), induces changes to metabolism that drive the disease. Regional metabolomics can help to understand metabolic variation across the tumour including changes near the tumour core, where hypoxia is likely more pronounced. We apply ultra...

2026-06-03 | MTBLS1905 | MetaboLights

Bulk RNA sequencing of mutant MAPT over-expression in neural organoids

Developing and benchmarking model systems to understand neurodegeneration remains an important challenge. In this work, we overexpressed mutant MAPT (P301L,V337M) in neural organoids to understand the resulting pathology.

ORGANISM(S): Homo sapiens

2026-03-31 | E-MTAB-16510 | biostudies-arrayexpress

Diel, daily, and spatial variation of coral reef seawater microbial communities.

Not available

S-EPMC7065756 | biostudies-literature

RNA-sequencing of transgenic Arabidopsis seedlings constitutively expressing a Colletotrichum higginsianum effector

The fungal pathogen Colletotrichum higginsianum secretes effector proteins during infection of Arabidopsis. To explore the host processes perturbed by the effector candidate ChEC108 in host plants, transgenic Arabidopsis lines were generated to express AtUBQ10pro:ChEC108-eGFP or AtUBQ10pro:ChEC108^D...

ORGANISM(S): Arabidopsis thaliana

2026-05-21 | E-MTAB-16996 | biostudies-arrayexpress

RNA-seq of Vibrio cholerae wild-type and dbfS, dbfQ, and dbfR(D51V) mutant strains

RNA-seq was performed to characterize transcriptional changes governed by the DbfRS two-component signaling system in Vibrio cholerae. The experiment compared global gene expression in wild-type and mutant strains lacking dbfS or dbfQ, as well as a phospho-dead dbfR(D51V) variant. Cultures were grow...

ORGANISM(S): Vibrio cholerae

2025-11-20 | E-MTAB-16165 | biostudies-arrayexpress

PAR-6, but not E-cadherin and β-integrin, is necessary for epithelial polarization in C. elegans.