relative quantitative analysis

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Organisms

Homo sapiens (105)
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Repository

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Colon mucinous adenocarcinoma (NCI Metathesaurus CL029553) in DiseaseLocation rectosigmoid colon has DiseaseStaging T3N2M1 (1)
HIV (1)
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Technology Type

Mass Spectrometry (1896)
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SWATH MS (121)
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HDMSE (21)
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MSE (6)
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Agilent 2100 Bioanalyzer (2)
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G2565BA DNA microarray scanner [Agilent] (2)
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NextSeq 550 (2)
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QuantStudio 12K Flex (1)
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Ribo-Zero Plant rRNA removal kit (Illumina); TruSeq Stranded Total RNA LT kit (Illumina) (1)

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2004 (15)
2003 (2)
2002 (2)
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UNIPROT ID/AC

P27361 (2)
P04049 (2)
P19687 (1)
P16068 (1)
P63151 (1)
Q07890 (1)
P06213 (1)
Q02297 (1)
P21860 (1)
P04626 (1)
Q05609 (1)
Q0WPQ2 (1)
P49333 (1)
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P01308 (1)
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O00750 (1)
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P01127 (1)
Q9GZP0 (1)
Q9NRA1 (1)
Q15198 (1)
Q9LKL2 (1)
O81713 (1)

ENSEMBL ID

ENSG00000170477 (18)
ENSG00000229353 (11)
ENSG00000247315 (6)
ENSG00000147251 (5)

CHEBI ID

CHEBI:30769 (61)
CHEBI:18012 (55)
CHEBI:15741 (54)
CHEBI:15354 (47)
CHEBI:17822 (39)
CHEBI:18132 (32)
CHEBI:16411 (30)
CHEBI:17234 (28)
CHEBI:17552 (19)
CHEBI:17553 (18)
CHEBI:16000 (18)
CHEBI:24996 (2)
CHEBI:29108 (2)
CHEBI:17138 (2)
CHEBI:15361 (2)
CHEBI:15422 (2)
CHEBI:16908 (2)
CHEBI:72738 (1)
CHEBI:18053 (1)
CHEBI:18153 (1)
CHEBI:23530 (1)
CHEBI:22676 (1)
CHEBI:89363 (1)
CHEBI:16480 (1)
CHEBI:15552 (1)
CHEBI:16038 (1)
CHEBI:49183 (1)
CHEBI:16618 (1)
CHEBI:15996 (1)
CHEBI:33699 (1)

Metabolite Name

Creatine (54)
Choline (53)
Hypoxanthine (52)
Spermidine (50)
L-Phenylalanine (48)
Uracil (47)
Adenosine (47)
Adenine (47)
Creatinine (47)
Indole (46)
Uridine (46)
L-Tyrosine (44)
L-Histidine (43)
Taurine (43)
Inosine (43)
Guanine (42)
L-Tryptophan (42)
Betaine (41)
Cytidine (41)
Citric acid (39)
Histamine (39)
Riboflavin (39)
Azelaic acid (38)
Xanthine (38)
Guanosine (38)
Cytosine (37)
Thymine (35)
Pantothenic acid (35)
Ornithine (34)
Fumaric acid (34)

First Public Date

2014 (86)
2013 (28)
2025 (24)
2022 (24)
2018 (21)
2021 (20)
2020 (20)
2019 (20)
2024 (19)
2017 (15)
2026 (13)
2015 (13)
2023 (12)
2016 (12)
2011 (1)

Modelling Approach

Ordinary differential equation model (14)
Constraint-based model (8)
Partial differential equation model (2)

Study status

Recruiting (1)

Lab affiliation

Instituto de Investigaciones Sanitarias de Santiago de Compostela (14)
Chair of Biochemistry II, Theodor Boveri-Institute, Biocenter, University of Würzburg, Würzburg, Germany (10)
Department of Biochemistry and Functional Proteomics, Institute of Biology II, Faculty of Biology and BIOSS Centre for Biological Signalling Studies, University of Freiburg, 79104 Freiburg im Breisgau, Germany (9)
Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge, CB2 0XY, UK (9)
Cellzome (6)
Institute of Pharmacology and Structural Biology, CNRS, Toulouse, France (6)
Liverpool John Moores University (6)
Department of Genome Sciences University of Washington USA (5)
MDC (5)
Department of Biomedical Sciences, University of Padova, Italy (5)
Department of Molecular Biology and Radiobiology, Mendel University in Brno, CZ (5)
National Key Laboratory of Medical Molecular Biology & Department of Immunology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences (5)
Institute of Pharmacology and Structural Biology, CNRS, Toulouse (5)
VetMedZg Laboratory,Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medicine, Veterinary Medicine and Life Sciences, University of Glasgow, Glasgow, UK (5)
Universität Greifswald Institut für Pharmazie, AG Pharmazeutische Biotechnologie Greifswald, Germany (5)
Proteomics Core Facility, Biozentrum, University of Basel, Switzerland (5)
Parasitology Laboratory, Institute of Natural Resources and Agrobiology (IRNASA, CSIC). Cordel de Merinas, 40-52, 37008 Salamanca, Spain. (4)
Department of Biochemistry and Functional Proteomics, Institute of Biology II, Faculty of Biology and Signalling Research Centres BIOSS and CIBSS, University of Freiburg, 79104 Freiburg im Breisgau, Germany (4)
School of Agriculture, Meiji University (4)
Moffitt Cancer Center (4)
Mendel University in Brno (4)
Staff Scientist Biological Systems & Engineering Division Lawrence Berkeley National Laboratory Berkeley CA 94720 (4)
Department of Biochemistry and Molecular Biology, University of Calgary, Alberta, Canada; Department of Physiology and Pharmacology, University of Calgary, Alberta, Canada; The Hotchkiss Brain Institute, University of Calgary, Alberta, Canada; McCaig Institute for Bone and Joint Health, University of Calgary, Alberta, Canada (4)
German Cancer Consortium (DKTK), partner site Freiburg German Cancer Research Center (DKFZ) Foundation under Public Law c/o Department of Urology Zentrale Klinische Forschung (ZKF) Medical Center-University of Freiburg Breisacher Str. 66, 79106 Freiburg, Germany (4)
Center for Neuroscience and Cell Biology – University of Coimbra (4)
Cambridge Institute for Medical Research, University of Cambridge (4)
Cornell University (4)
Vividion Therapeutics (3)
Ruhr University Bochum, Medical Faculty, Medizinisches Proteom-Center (3)
DIMEVET Università degli Studi di Milano (3)

Keyword

Early onset (1)
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Young adult (1)
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Diet (1)
Rectal cancer (1)

IsPrivate

False (24)

Model Flag

Non Kinetic (8)

Submitter Keywords

Immuno-oncology (1)

Classification

bacteria (10)
protozoa (2)
viruses (1)

Modification

N6 (5)
2x(15)N labeled L-lysine (5)
4x(15)N labeled L-arginine (4)
57.021464 (3)
-17.026549 (2)
42.010565 (2)
15.994915 (2)
4-tetrahydrothiazine-3-carboxylic acid (2)
Methionine (1)
28.0313 (1)
45.029395 (1)
4x(2)H labeled dimethylated residue (1)
-18.010565 (1)
4x(2)H labeled dimethylated L-lysine (1)
4 (1)
N6-dimethyl-L-lysine (1)
Not available (1)

Study type

Transcription profiling by array (2929)
Comparative genomic hybridization by array (275)
RNA-seq of coding RNA (247)
ChIP-seq (95)
Unknown experiment type (88)
Methylation profiling by array (67)
Other (66)
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Genotyping by array (49)
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Methylation profiling by high throughput sequencing (20)
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Plant - High-throughput sequencing (3)
Cell line - High-throughput sequencing (3)
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ChIP-chip by SNP array (2)
Human - Methylation microarray (2)
Animal - High-throughput sequencing (2)

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2010 (758)
2013 (732)
2014 (721)
2015 (718)
2022 (602)
2012 (590)
2021 (557)
2016 (539)
2011 (513)
2023 (478)
2020 (433)
2019 (425)
2024 (408)
2025 (387)
2018 (366)
2017 (312)
2008 (274)
2009 (238)
2007 (137)
2026 (77)
2006 (69)
2005 (41)
2004 (29)
2003 (13)
2002 (12)
2001 (5)
2000 (4)
1999 (2)
1998 (1)

Location

Finland (1)
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Germany (1)
Italy (1)
Spain (1)
United States (1)

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Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow

Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions t...

2018-03-26 | MTBLS417 | MetaboLights

Quantitative Metabolomic Dataset of Avian Eye Lenses

Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics can help diagnose diseases, reveal molecular basis of a disease, and ...

2023-06-30 | MTBLS7739 | MetaboLights

The Relative Content and Distribution of Absorbed Volatile Organic Compounds in Rats Administered Asari Radix et Rhizoma Are Different between Powder- and Decoction-Treated Groups

Asari Radix et Rhizoma (ARR) is an important traditional Chinese medicine. Volatile organic compounds (VOCs) are the main active constituents of ARR. Research on the metabolite profile of VOCs and the difference of absorbed constituents in vivo after an administration of ARR decoction and powder wil...

2021-02-01 | MTBLS2053 | MetaboLights

Absolute quantitative lipidomics reveals lipidome-wide alterations in aging brain (Mouse brain NEG UPLC-MS assay)

INTRODUCTION: The absolute quantitation of lipids at the lipidome-wide scale is a challenge but plays an important role in the comprehensive study of lipid metabolism.

OBJECTIVES: We aim to develop a high-throughput quantitative lipidomics approach to enab...

2018-08-03 | MTBLS495 | MetaboLights

Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome

INTRODUCTION: Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to n...

2024-04-23 | MTBLS7429 | MetaboLights

Absolute quantitative lipidomics reveals lipidome-wide alterations in aging brain (Mouse brain POS UPLC-MS assay)

INTRODUCTION: The absolute quantitation of lipids at the lipidome-wide scale is a challenge but plays an important role in the comprehensive study of lipid metabolism.

OBJECTIVES: We aim to develop a high-throughput quantitative lipidomics approach to enab...

2018-08-03 | MTBLS562 | MetaboLights

Integrative Modeling of Quantitative Plasma Lipoprotein, Metabolic, and Amino Acid Data Reveals a Multiorgan Pathological Signature of SARS-CoV-2 Infection

The metabolic effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on human blood plasma were characterized using multi-platform metabolic phenotyping with Nuclear Magnetic Resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Quantitative mea...

2021-01-29 | MTBLS2014 | MetaboLights

Matrix Effect on Chemical Isotope Labeling and Its Implication in Metabolomic Sample Preparation for Quantitative Metabolomics

Matrix effect from various constituents in biological samples can reduce the accuracy of quantitative metabolomics. Differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) can overcome the matrix effect on MS detection based on measuring the intensity ratios of met...

2015-07-01 | MTBLS194 | MetaboLights

Integrating Blood Microsampling Devices with CE-MS for Untargeted Analysis of Polar Metabolomics

Capillary electrophoresis–mass spectrometry (CE-MS) offers considerable advantages for polar compound metabolomics analysis, including simple workflows, fast method development, and suitability for small sample volumes. Blood microsampling (BμS) techniques (such as dried blood spots, quantitative...

2026-01-13 | MTBLS13090 | MetaboLights

Relative Quantitative Analysis of Site-Specific N-Linked Glycosylation in Hyperglycosylated In-terferon-β via Mass Spectrometry

Glycosylation is a critical determinant of the efficacy, stability, and pharmacological behavior of therapeutic proteins. R27T, an engineered variant of interferon-β1a, contains two N-glycosylation sites (Asn25 and Asn80), increasing its structural complexity and analytical requirements. In this stu...

ORGANISM(S): Homo sapiens (Human)

2026-09-21 | PXD077477 | Pride

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INTRODUCTION: Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to n...

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