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Items: 43

1.

Precocious puberty.

Bradley SH, Lawrence N, Steele C, Mohamed Z.

BMJ. 2020 Jan 13;368:l6597. doi: 10.1136/bmj.l6597. Review. No abstract available.

PMID:
31932347
2.

How do paediatricians use and monitor antithyroid drugs in the UK? A clinician survey.

Lawrence N, Cheetham T, Elder C.

Clin Endocrinol (Oxf). 2019 Sep;91(3):417-423. doi: 10.1111/cen.14046. Epub 2019 Jun 17.

PMID:
31179554
3.

Big data and the NHS - we have the -technology, but we need patient and professional engagement.

Lawrence NR, Bradley SH.

Future Healthc J. 2018 Oct;5(3):229-230. doi: 10.7861/futurehosp.5-3-229.

4.

Using primary care data for health research in England - an overview.

Bradley SH, Lawrence NR, Carder P.

Future Healthc J. 2018 Oct;5(3):207-212. doi: 10.7861/futurehosp.5-3-207.

5.

Memory and mental time travel in humans and social robots.

Prescott TJ, Camilleri D, Martinez-Hernandez U, Damianou A, Lawrence ND.

Philos Trans R Soc Lond B Biol Sci. 2019 Apr 29;374(1771):20180025. doi: 10.1098/rstb.2018.0025.

6.

The Emergence of Organizing Structure in Conceptual Representation.

Lake BM, Lawrence ND, Tenenbaum JB.

Cogn Sci. 2018 Jun;42 Suppl 3:809-832. doi: 10.1111/cogs.12580. Epub 2018 Jan 9.

PMID:
29315735
7.

Efficient inference for sparse latent variable models of transcriptional regulation.

Dai Z, Iqbal M, Lawrence ND, Rattray M.

Bioinformatics. 2017 Dec 1;33(23):3776-3783. doi: 10.1093/bioinformatics/btx508.

8.

Single-cell RNA-seq and computational analysis using temporal mixture modelling resolves Th1/Tfh fate bifurcation in malaria.

Lönnberg T, Svensson V, James KR, Fernandez-Ruiz D, Sebina I, Montandon R, Soon MS, Fogg LG, Nair AS, Liligeto U, Stubbington MJ, Ly LH, Bagger FO, Zwiessele M, Lawrence ND, Souza-Fonseca-Guimaraes F, Bunn PT, Engwerda CR, Heath WR, Billker O, Stegle O, Haque A, Teichmann SA.

Sci Immunol. 2017 Mar 3;2(9). pii: eaal2192. doi: 10.1126/sciimmunol.aal2192. Erratum in: Sci Immunol. 2018 Mar 9;3(21):.

9.

Rapid Analysis of Copper Ore in Pre-Smelter Head Flow Slurry by Portable X-ray Fluorescence.

Burnett BJ, Lawrence NJ, Abourahma JN, Walker EB.

Appl Spectrosc. 2016 May;70(5):826-8. doi: 10.1177/0003702816638282. Epub 2016 Mar 22.

PMID:
27006021
10.

Genome-wide modeling of transcription kinetics reveals patterns of RNA production delays.

Honkela A, Peltonen J, Topa H, Charapitsa I, Matarese F, Grote K, Stunnenberg HG, Reid G, Lawrence ND, Rattray M.

Proc Natl Acad Sci U S A. 2015 Oct 20;112(42):13115-20. doi: 10.1073/pnas.1420404112. Epub 2015 Oct 5.

11.

Fast Nonparametric Clustering of Structured Time-Series.

Hensman J, Rattray M, Lawrence ND.

IEEE Trans Pattern Anal Mach Intell. 2015 Feb;37(2):383-93. doi: 10.1109/TPAMI.2014.2318711.

12.

A reverse-engineering approach to dissect post-translational modulators of transcription factor's activity from transcriptional data.

Gambardella G, Peluso I, Montefusco S, Bansal M, Medina DL, Lawrence N, di Bernardo D.

BMC Bioinformatics. 2015 Sep 3;16:279. doi: 10.1186/s12859-015-0700-3.

13.

Diagnostic accuracy of bone turnover markers as a screening tool for aseptic loosening after total hip arthroplasty.

Lawrence NR, Jayasuriya RL, Gossiel F, Wilkinson JM.

Hip Int. 2015 Nov-Dec;25(6):525-30. doi: 10.5301/hipint.5000253. Epub 2015 May 22.

PMID:
26044531
14.

Warped linear mixed models for the genetic analysis of transformed phenotypes.

Fusi N, Lippert C, Lawrence ND, Stegle O.

Nat Commun. 2014 Sep 19;5:4890. doi: 10.1038/ncomms5890.

15.

Inference of RNA polymerase II transcription dynamics from chromatin immunoprecipitation time course data.

wa Maina C, Honkela A, Matarese F, Grote K, Stunnenberg HG, Reid G, Lawrence ND, Rattray M.

PLoS Comput Biol. 2014 May 15;10(5):e1003598. doi: 10.1371/journal.pcbi.1003598. eCollection 2014 May.

16.

Transcriptomic indices of fast and slow disease progression in two mouse models of amyotrophic lateral sclerosis.

Nardo G, Iennaco R, Fusi N, Heath PR, Marino M, Trolese MC, Ferraiuolo L, Lawrence N, Shaw PJ, Bendotti C.

Brain. 2013 Nov;136(Pt 11):3305-32. doi: 10.1093/brain/awt250. Epub 2013 Sep 24.

PMID:
24065725
17.

Linear latent force models using Gaussian processes.

Álvarez MA, Luengo D, Lawrence ND.

IEEE Trans Pattern Anal Mach Intell. 2013 Nov;35(11):2693-705. doi: 10.1109/TPAMI.2013.86.

18.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

Hensman J, Lawrence ND, Rattray M.

BMC Bioinformatics. 2013 Aug 20;14:252. doi: 10.1186/1471-2105-14-252.

19.

Resonant photoemission observations and DFT study of s-d hybridization in catalytically active gold clusters on ceria nanorods.

Zhou Y, Lawrence NJ, Wang L, Kong L, Wu TS, Liu J, Gao Y, Brewer JR, Lawrence VK, Sabirianov RF, Soo YL, Zeng XC, Dowben PA, Mei WN, Cheung CL.

Angew Chem Int Ed Engl. 2013 Jul 1;52(27):6936-9. doi: 10.1002/anie.201301383. Epub 2013 May 28. No abstract available.

PMID:
23716469
20.

Detecting regulatory gene-environment interactions with unmeasured environmental factors.

Fusi N, Lippert C, Borgwardt K, Lawrence ND, Stegle O.

Bioinformatics. 2013 Jun 1;29(11):1382-9. doi: 10.1093/bioinformatics/btt148. Epub 2013 Apr 4.

PMID:
23559640
21.

Mining regulatory network connections by ranking transcription factor target genes using time series expression data.

Honkela A, Rattray M, Lawrence ND.

Methods Mol Biol. 2013;939:59-67. doi: 10.1007/978-1-62703-107-3_6.

PMID:
23192541
22.

Unravelling the enigma of selective vulnerability in neurodegeneration: motor neurons resistant to degeneration in ALS show distinct gene expression characteristics and decreased susceptibility to excitotoxicity.

Brockington A, Ning K, Heath PR, Wood E, Kirby J, Fusi N, Lawrence N, Wharton SB, Ince PG, Shaw PJ.

Acta Neuropathol. 2013 Jan;125(1):95-109. doi: 10.1007/s00401-012-1058-5. Epub 2012 Nov 13.

23.

Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison.

Titsias MK, Honkela A, Lawrence ND, Rattray M.

BMC Syst Biol. 2012 May 30;6:53. doi: 10.1186/1752-0509-6-53.

24.

Modeling meiotic chromosomes indicates a size dependent contribution of telomere clustering and chromosome rigidity to homologue juxtaposition.

Penfold CA, Brown PE, Lawrence ND, Goldman AS.

PLoS Comput Biol. 2012;8(5):e1002496. doi: 10.1371/journal.pcbi.1002496. Epub 2012 May 3.

25.

Controlling E. coli adhesion on high-k dielectric bioceramics films using poly(amino acid) multilayers.

Lawrence NJ, Wells-Kingsbury JM, Ihrig MM, Fangman TE, Namavar F, Cheung CL.

Langmuir. 2012 Mar 6;28(9):4301-8. doi: 10.1021/la2033725. Epub 2012 Feb 17.

PMID:
22339263
26.

Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies.

Fusi N, Stegle O, Lawrence ND.

PLoS Comput Biol. 2012 Jan;8(1):e1002330. doi: 10.1371/journal.pcbi.1002330. Epub 2012 Jan 5.

27.

Genome-wide occupancy links Hoxa2 to Wnt-β-catenin signaling in mouse embryonic development.

Donaldson IJ, Amin S, Hensman JJ, Kutejova E, Rattray M, Lawrence N, Hayes A, Ward CM, Bobola N.

Nucleic Acids Res. 2012 May;40(9):3990-4001. doi: 10.1093/nar/gkr1240. Epub 2012 Jan 5.

28.

Defect engineering in cubic cerium oxide nanostructures for catalytic oxidation.

Lawrence NJ, Brewer JR, Wang L, Wu TS, Wells-Kingsbury J, Ihrig MM, Wang G, Soo YL, Mei WN, Cheung CL.

Nano Lett. 2011 Jul 13;11(7):2666-71. doi: 10.1021/nl200722z. Epub 2011 May 31.

PMID:
21627100
29.

A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression.

Kalaitzis AA, Lawrence ND.

BMC Bioinformatics. 2011 May 20;12:180. doi: 10.1186/1471-2105-12-180.

30.

tigre: Transcription factor inference through gaussian process reconstruction of expression for bioconductor.

Honkela A, Gao P, Ropponen J, Rattray M, Lawrence ND.

Bioinformatics. 2011 Apr 1;27(7):1026-7. doi: 10.1093/bioinformatics/btr057. Epub 2011 Feb 7.

PMID:
21300702
31.

Formation of a porous cerium oxide membrane by anodization.

Lawrence NJ, Jiang K, Cheung CL.

Chem Commun (Camb). 2011 Mar 7;47(9):2703-5. doi: 10.1039/c0cc04806b. Epub 2011 Jan 13.

PMID:
21234482
32.

TFInfer: a tool for probabilistic inference of transcription factor activities.

Asif HM, Rolfe MD, Green J, Lawrence ND, Rattray M, Sanguinetti G.

Bioinformatics. 2010 Oct 15;26(20):2635-6. doi: 10.1093/bioinformatics/btq469. Epub 2010 Aug 24.

PMID:
20739311
33.

Model-based method for transcription factor target identification with limited data.

Honkela A, Girardot C, Gustafson EH, Liu YH, Furlong EE, Lawrence ND, Rattray M.

Proc Natl Acad Sci U S A. 2010 Apr 27;107(17):7793-8. doi: 10.1073/pnas.0914285107. Epub 2010 Apr 12.

34.

Elementary properties of CaV1.3 Ca(2+) channels expressed in mouse cochlear inner hair cells.

Zampini V, Johnson SL, Franz C, Lawrence ND, Münkner S, Engel J, Knipper M, Magistretti J, Masetto S, Marcotti W.

J Physiol. 2010 Jan 1;588(Pt 1):187-99. doi: 10.1113/jphysiol.2009.181917. Epub 2009 Nov 16.

35.

puma: a Bioconductor package for propagating uncertainty in microarray analysis.

Pearson RD, Liu X, Sanguinetti G, Milo M, Lawrence ND, Rattray M.

BMC Bioinformatics. 2009 Jul 9;10:211. doi: 10.1186/1471-2105-10-211.

36.

Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities.

Gao P, Honkela A, Rattray M, Lawrence ND.

Bioinformatics. 2008 Aug 15;24(16):i70-5. doi: 10.1093/bioinformatics/btn278.

PMID:
18689843
37.

Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities.

Sanguinetti G, Lawrence ND, Rattray M.

Bioinformatics. 2006 Nov 15;22(22):2775-81. Epub 2006 Sep 11.

PMID:
16966362
38.

Probe-level measurement error improves accuracy in detecting differential gene expression.

Liu X, Milo M, Lawrence ND, Rattray M.

Bioinformatics. 2006 Sep 1;22(17):2107-13. Epub 2006 Jul 4.

PMID:
16820429
39.

Propagating uncertainty in microarray data analysis.

Rattray M, Liu X, Sanguinetti G, Milo M, Lawrence ND.

Brief Bioinform. 2006 Mar;7(1):37-47. Review.

PMID:
16761363
40.

A probabilistic dynamical model for quantitative inference of the regulatory mechanism of transcription.

Sanguinetti G, Rattray M, Lawrence ND.

Bioinformatics. 2006 Jul 15;22(14):1753-9. Epub 2006 Apr 21.

PMID:
16632490
41.

Accounting for probe-level noise in principal component analysis of microarray data.

Sanguinetti G, Milo M, Rattray M, Lawrence ND.

Bioinformatics. 2005 Oct 1;21(19):3748-54. Epub 2005 Aug 9.

PMID:
16091409
42.

A tractable probabilistic model for Affymetrix probe-level analysis across multiple chips.

Liu X, Milo M, Lawrence ND, Rattray M.

Bioinformatics. 2005 Sep 15;21(18):3637-44. Epub 2005 Jul 14.

PMID:
16020470
43.

Reducing the variability in cDNA microarray image processing by Bayesian inference.

Lawrence ND, Milo M, Niranjan M, Rashbass P, Soullier S.

Bioinformatics. 2004 Mar 1;20(4):518-26. Epub 2004 Jan 22.

PMID:
14990447

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