andrea jorgensen

Professor Andrea Jorgensen

Andrea Jorgensen is Professor of Biostatistics and leads the Department of Health Data Science’s Statistical Genetics and Pharmacogenetics Research Group. Her research interests lie within the development and application of methods for the design and analysis of pharmacogenetic studies. She is statistical lead on several large pharmacogenetic studies, working closely with colleagues within the Wolfson Centre for Personalised Medicine and the MRC Centre for Drug Safety Science, where she applies methods to various study designs across a broad and diverse range of disease areas including epilepsy, anticoagulation, asthma and lupus. She works on the development of methods and software for the design and analysis of genetic studies with survival outcomes, which are particularly common in pharmacogenetics. She was also co-lead of the MRC Network of Hubs for Trials Methodology Research's Stratified Medicine Working Group, and is an active member of the same working group for the Network’s successor, TMRP, where she developed guidance on the design and analysis of biomarker-guided randomised controlled trials (www.bigted.org). Andrea also has extensive experience of methods for conducting systematic reviews and meta-analyses of pharmacogenetic studies, and is a keen advocate for improving the quality and reporting of such studies to facilitate evidence synthesis. Together with other members of the group, she developed the STROPS reporting guidelines with a view to improving the completeness and transparency of reporting of pharmacogenetic studies. 

Personal webpage: Andrea Jorgensen - University of Liverpool

Email: aljorgen@liverpool.ac.uk

 

 

 

Professor Bertram Mueller-Myhsok

Bertram Müller-Myhsok is Professor and Chair of Statistical Genetics. He is on a part time appointment, the second affiliation being with the Max Planck

Institute of Psychiatry in Munich. His research interests lie in the development of statistical methodology bridging the areas of machine learning, statistics, artificial intelligence, and deep learning. A research focus within these areas are the development and application of such methodology on questions related to subgroup detection in high-dimensional datasets. Special applications are with psychiatric, neurologic, and obstetric phenotypes, especially in conjunction with longitudinal datasets, or, in a more general sense, datasets containing ordered dimensions and inhibiting a certain degree of autocorrelation in and/or arising from those dimensions.

This work also implicates aspects of statistical computing and reaches into aspects of unsupervised and semi-supervised learning as well as transfer learning. 

He is a co-PI of the EU-funded initial training network (ITN) Machine Learning Frontiers in Precision Medicine (MLFPM, https://mlfpm.eu/). 

Personal webpage: Bertram Muller-Myhsok - University of Liverpool

Email: bmm@liverpool.ac.uk

 

Dr Anna Fowler

Anna Fowler is a tenure-track research fellow in statistical genetics. Her research focuses on the development of statistical methods, including machine learning methodology, for genetic sequencing data. A current research focus is on immuno-genetics and the analysis of immune repertoire sequencing to improve our understanding of the adaptive immune system and for disease diagnosis. Other interests include the identification of rare variants in complex sequencing data, such as copy number variants from whole exome sequencing or mutations in circulating tumour DNA. Her work is largely translational with an emphasis on collaborations with clinicians and industrial partners, and the development of user friendly software.

Personal webpage: Anna Auer-Fowler - University of Liverpool

Email: a.fowler@liverpool.ac.uk

 

 

Dr Liam Brierley

Liam Brierley is an MRC Skills Development Fellow. Liam's research aims to understand the process of disease emergence and zoonotic transmission of new RNA viruses from animals to humans. By applying a genomic perspective, he aims to improve systems for predicting future emergence and pandemic potential.

Personal webpage: Liam Brierley - University of Liverpool

Email: Liam.Brierley@liverpool.ac.uk

 

 

Dr Schadrac Agbla

Schadrac Agbla is a postdoctoral researcher in Biostatistics, holding an MRC Skills Development Fellowship. His research aims to develop a randomisation-based method for causal inference using machine learning techniques and to investigate the causal factors for preterm birth and their effects on early child development delay. He also has interests in understanding and improving diagnostics of paediatric TB and of drug resistance for adult TB patients. He is involved in a multicountry project on improving the diagnostic and monitoring for multidrug resistant TB patients in Africa (DIAMA).

Personal webpage: Schadrac Agbla - University of Liverpool

Email: Schadrac.Agbla@liverpool.ac.uk

 

 

Dr Ravi Girikematha-Shankar

Ravi Girikematha Shankar is a post-doctoral research associate working on an MRC-funded project focusing on developing methodology and software to analyse time to event outcomes in whole exome sequencing studies, including complex datasets such as those including imputed data and rare variants. 

He received a PhD in Biostatistics from National Institute of Mental Health and Neuro Sciences, Bengaluru, India in 2018. His PhD research was on exploring utility of Quantile Regression methods and its extensions in biomedical research using real life and simulated datasets. He proposed a combined approach of censored quantile regression and latent class growth models in analysing time to event and targeted gene expression data to identify genes signatures. His PhD advisor was Prof. K. Thennarasu. He also has a Master’s degree in Agricultural Statistics from Gandhi Krishi Vigyan Kendra, Bengaluru, India where he worked on statistical models for stability analysis in agricultural crops for his dissertation. He also worked as a junior business analyst at a pharma-analytics company for a short period before joining academia as a researcher. 

Ravi is proficient in applications of various advanced statistical methods on diverse datasets using leading statistical software packages including R, Stata and SPSS.

Personal webpage: Ravi Girikematha Shankar - University of Liverpool

Email: ravi.shankar@liverpool.ac.uk / ravigs1988@gmail.com<

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