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Dr Chris Newby

Chris

Asthma UK Lecturer

Email: c.newby@qmul.ac.uk
Telephone: 020 7882 7330

Profile

 

My research involves statistical analysis and research in to respiratory diseases including asthma and COPD. This includes cluster analysis, factor analysis, structural equation modelling, longitudinal analysis and gene expression analysis. I am also interested in data sharing and harmonisation of large datasets.

 

Research

Research Interests:

AirPROM, Airway Disease Predicting Outcomes through Patient Specific Computational Modelling.

BioSHaRE, The mission of BioSHaRE is to ensure the development of harmonized measures and standardized computing infrastructures.

COPD-MAP, a MRC/ABPI Inflammation and Immunology Initiative

Publications

Newby, C., J. Agbetile, et al. (2014). "Lung function decline and variable airway inflammatory pattern: Longitudinal analysis of severe asthma." Journal of Allergy and Clinical Immunology 134(2): 287-294. e285.

Newby, C., L. G. Heaney, et al. (2014). "Statistical Cluster Analysis of the British Thoracic Society Severe Refractory Asthma Registry: Clinical Outcomes and Phenotype Stability." PloS one 9(7): e102987

Ghebre, M. A., M. Bafadhel,…..Chris Newby, Paul Burton, Chris Brightling. (2014). "Biological clustering supports both “Dutch” and “British” hypotheses of asthma and chronic obstructive pulmonary disease." Journal of Allergy and Clinical Immunology.

Desai, D., Newby, et al. (2013). "Elevated sputum interleukin-5 and submucosal eosinophilia in obese individuals with severe asthma." American journal of respiratory and critical care medicine 188(6): 657-663.

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