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Items: 1 to 20 of 43

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1.

Assessing sub-cellular resolution in spatial proteomics experiments.

Gatto L, Breckels LM, Lilley KS.

Curr Opin Chem Biol. 2019 Feb;48:123-149. doi: 10.1016/j.cbpa.2018.11.015. Epub 2018 Dec 14. Review.

2.

ensembldb: an R package to create and use Ensembl-based annotation resources.

Rainer J, Gatto L, Weichenberger CX.

Bioinformatics. 2019 Jan 25. doi: 10.1093/bioinformatics/btz031. [Epub ahead of print]

PMID:
30689724
3.

Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics.

Geladaki A, Kočevar Britovšek N, Breckels LM, Smith TS, Vennard OL, Mulvey CM, Crook OM, Gatto L, Lilley KS.

Nat Commun. 2019 Jan 18;10(1):331. doi: 10.1038/s41467-018-08191-w.

4.

A Bayesian mixture modelling approach for spatial proteomics.

Crook OM, Mulvey CM, Kirk PDW, Lilley KS, Gatto L.

PLoS Comput Biol. 2018 Nov 27;14(11):e1006516. doi: 10.1371/journal.pcbi.1006516. eCollection 2018 Nov.

5.

Preprints help journalism, not hinder it.

Tennant J, Gatto L, Logan C.

Nature. 2018 Aug;560(7720):553. doi: 10.1038/d41586-018-06055-3. No abstract available.

PMID:
30158616
6.

Negative feedback via RSK modulates Erk-dependent progression from naïve pluripotency.

Nett IR, Mulas C, Gatto L, Lilley KS, Smith A.

EMBO Rep. 2018 Aug;19(8). pii: e45642. doi: 10.15252/embr.201745642. Epub 2018 Jun 12.

7.

hiPSC hepatocyte model demonstrates the role of unfolded protein response and inflammatory networks in α1-antitrypsin deficiency.

Segeritz CP, Rashid ST, de Brito MC, Serra MP, Ordonez A, Morell CM, Kaserman JE, Madrigal P, Hannan NRF, Gatto L, Tan L, Wilson AA, Lilley K, Marciniak SJ, Gooptu B, Lomas DA, Vallier L.

J Hepatol. 2018 Oct;69(4):851-860. doi: 10.1016/j.jhep.2018.05.028. Epub 2018 Jun 5.

8.

A subcellular map of the human proteome.

Thul PJ, Åkesson L, Wiking M, Mahdessian D, Geladaki A, Ait Blal H, Alm T, Asplund A, Björk L, Breckels LM, Bäckström A, Danielsson F, Fagerberg L, Fall J, Gatto L, Gnann C, Hober S, Hjelmare M, Johansson F, Lee S, Lindskog C, Mulder J, Mulvey CM, Nilsson P, Oksvold P, Rockberg J, Schutten R, Schwenk JM, Sivertsson Å, Sjöstedt E, Skogs M, Stadler C, Sullivan DP, Tegel H, Winsnes C, Zhang C, Zwahlen M, Mardinoglu A, Pontén F, von Feilitzen K, Lilley KS, Uhlén M, Lundberg E.

Science. 2017 May 26;356(6340). pii: eaal3321. doi: 10.1126/science.aal3321. Epub 2017 May 11.

PMID:
28495876
9.

Using hyperLOPIT to perform high-resolution mapping of the spatial proteome.

Mulvey CM, Breckels LM, Geladaki A, Britovšek NK, Nightingale DJH, Christoforou A, Elzek M, Deery MJ, Gatto L, Lilley KS.

Nat Protoc. 2017 Jun;12(6):1110-1135. doi: 10.1038/nprot.2017.026. Epub 2017 May 4.

PMID:
28471460
10.

BioContainers: an open-source and community-driven framework for software standardization.

da Veiga Leprevost F, Grüning BA, Alves Aflitos S, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Vera Alvarez R, Griss J, Nesvizhskii AI, Perez-Riverol Y.

Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192.

11.

A Bioconductor workflow for processing and analysing spatial proteomics data.

Breckels LM, Mulvey CM, Lilley KS, Gatto L.

Version 2. F1000Res. 2016 Dec 28 [revised 2018 Jan 1];5:2926. doi: 10.12688/f1000research.10411.2. eCollection 2016.

12.

DAPAR & ProStaR: software to perform statistical analyses in quantitative discovery proteomics.

Wieczorek S, Combes F, Lazar C, Giai Gianetto Q, Gatto L, Dorffer A, Hesse AM, Couté Y, Ferro M, Bruley C, Burger T.

Bioinformatics. 2017 Jan 1;33(1):135-136. doi: 10.1093/bioinformatics/btw580. Epub 2016 Sep 6.

13.

Ten Simple Rules for Taking Advantage of Git and GitHub.

Perez-Riverol Y, Gatto L, Wang R, Sachsenberg T, Uszkoreit J, Leprevost Fda V, Fufezan C, Ternent T, Eglen SJ, Katz DS, Pollard TJ, Konovalov A, Flight RM, Blin K, Vizcaíno JA.

PLoS Comput Biol. 2016 Jul 14;12(7):e1004947. doi: 10.1371/journal.pcbi.1004947. eCollection 2016 Jul. No abstract available.

14.

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics.

Breckels LM, Holden SB, Wojnar D, Mulvey CM, Christoforou A, Groen A, Trotter MW, Kohlbacher O, Lilley KS, Gatto L.

PLoS Comput Biol. 2016 May 13;12(5):e1004920. doi: 10.1371/journal.pcbi.1004920. eCollection 2016 May.

15.

Analysis of Drosophila melanogaster proteome dynamics during embryonic development by a combination of label-free proteomics approaches.

Fabre B, Korona D, Groen A, Vowinckel J, Gatto L, Deery MJ, Ralser M, Russell S, Lilley KS.

Proteomics. 2016 Aug;16(15-16):2068-80. doi: 10.1002/pmic.201500482. Epub 2016 May 10.

16.

Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.

Lazar C, Gatto L, Ferro M, Bruley C, Burger T.

J Proteome Res. 2016 Apr 1;15(4):1116-25. doi: 10.1021/acs.jproteome.5b00981. Epub 2016 Mar 1.

17.

A draft map of the mouse pluripotent stem cell spatial proteome.

Christoforou A, Mulvey CM, Breckels LM, Geladaki A, Hurrell T, Hayward PC, Naake T, Gatto L, Viner R, Martinez Arias A, Lilley KS.

Nat Commun. 2016 Jan 12;7:8992. doi: 10.1038/ncomms9992.

18.

Testing and Validation of Computational Methods for Mass Spectrometry.

Gatto L, Hansen KD, Hoopmann MR, Hermjakob H, Kohlbacher O, Beyer A.

J Proteome Res. 2016 Mar 4;15(3):809-14. doi: 10.1021/acs.jproteome.5b00852. Epub 2015 Nov 17.

19.

Dynamic Proteomic Profiling of Extra-Embryonic Endoderm Differentiation in Mouse Embryonic Stem Cells.

Mulvey CM, Schröter C, Gatto L, Dikicioglu D, Fidaner IB, Christoforou A, Deery MJ, Cho LT, Niakan KK, Martinez-Arias A, Lilley KS.

Stem Cells. 2015 Sep;33(9):2712-25. doi: 10.1002/stem.2067. Epub 2015 Jun 23.

20.

Visualization of proteomics data using R and bioconductor.

Gatto L, Breckels LM, Naake T, Gibb S.

Proteomics. 2015 Apr;15(8):1375-89. doi: 10.1002/pmic.201400392. Review.

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