Imperial College London
Alternate

ProfessorMatthiasMerkenschlager

Faculty of Medicine, Institute of Clinical Sciences

Professor of Cell Biology
 
 
 
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Contact

 

+44 (0)20 3313 8239matthias.merkenschlager

 
 
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Location

 

5.11DLMS BuildingHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gomez-Cabrero:2019:10.1038/s41597-019-0202-7,
author = {Gomez-Cabrero, D and Tarazona, S and Ferreiros-Vidal, I and Ramirez, RN and Company, C and Schmidt, A and Reijmers, T and von, Saint Paul V and Marabita, F and Rodriguez-Ubreva, J and Garcia-Gomez, A and Carroll, T and Cooper, L and Liang, Z and Dharmalingam, G and van, der Kloet F and Harms, AC and Balzano-Nogueira, L and Lagani, V and Tsamardinos, I and Lappe, M and Maier, D and Westerhuis, JA and Hankemeier, T and Imhof, A and Ballestar, E and Mortazavi, A and Merkenschlager, M and Egner, JT and Conesa, A},
doi = {10.1038/s41597-019-0202-7},
journal = {Scientific Data},
pages = {1--15},
title = {STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse},
url = {http://dx.doi.org/10.1038/s41597-019-0202-7},
volume = {6},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system.
AU  - Gomez-Cabrero,D
AU  - Tarazona,S
AU  - Ferreiros-Vidal,I
AU  - Ramirez,RN
AU  - Company,C
AU  - Schmidt,A
AU  - Reijmers,T
AU  - von,Saint Paul V
AU  - Marabita,F
AU  - Rodriguez-Ubreva,J
AU  - Garcia-Gomez,A
AU  - Carroll,T
AU  - Cooper,L
AU  - Liang,Z
AU  - Dharmalingam,G
AU  - van,der Kloet F
AU  - Harms,AC
AU  - Balzano-Nogueira,L
AU  - Lagani,V
AU  - Tsamardinos,I
AU  - Lappe,M
AU  - Maier,D
AU  - Westerhuis,JA
AU  - Hankemeier,T
AU  - Imhof,A
AU  - Ballestar,E
AU  - Mortazavi,A
AU  - Merkenschlager,M
AU  - Egner,JT
AU  - Conesa,A
DO  - 10.1038/s41597-019-0202-7
EP  - 15
PY  - 2019///
SN  - 2052-4463
SP  - 1
TI  - STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse
T2  - Scientific Data
UR  - http://dx.doi.org/10.1038/s41597-019-0202-7
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000494480700002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.nature.com/articles/s41597-019-0202-7
UR  - http://hdl.handle.net/10044/1/75089
VL  - 6
ER  -
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