My research is motivated towards enabling a “panor-omic” view of patients through the integration of genomics data with data derived from patient records, the exposome, social graphs, remote monitoring and imaging to develop strategies for P4 medicine, namely, medicine that is precise, predictive, preventative and participatory of patient datasets.
Head of Bioinformatics
My background is in biochemistry/molecular biology (Bristol), and have since worked as a bioinformatician/software developer. I am currently working on developing the RADAR-CNS data collection platform. Other projects include monitoring seasonal infectious diseases & deep-learning image analysis pipelines for high-content screening.
Senior Software Development Group Leader
Research interests focus on addressing the disparity between the large body of theory in Artificial Intelligence and concrete translations into real-world applications, specifically in Healthcare. I currently lead projects using novel computational methodologies to solve pressing issues in clinical care at SLaM.
Applied Intelligent Systems Lead
My expertise and Interests include translational bioinformatics, Applied Predictive Modelling & Machine Learning, Next Generation Sequence Analysis & Personalised Medicine, Drug repositioning, Biomarker discovery, Open Science, Data Science.
Senior Data Scientist group Leader
Please contact me for general group enquiries or CTI projects, or visit the CTI website.
My current research focus is on annotating, analysing and searching large scale healthcare data by utilising Knowledge Graph techniques.
Post-Doctoral Data Scientist
I am working on using Graph Theory as a framework to study EHR data. My background is Systems Biology and Pharmacology, most recently I obtained a PhD applying Systems Biology methods to understand the progression of neurodegenerative disease and developing Graph Theory software.
Post-doctoral Research Fellow in Bioinformatics
I am currently working on gene expression analysis (RNA-Seq) in the context of Alzheimer’s disease. My background is in Biology and Bioinformatics and I have worked with several types of ‘omics data, including microarrays and DNA-methylation data sourced from different animal models.
Guillermo Carbajosa Antona
Postdoctoral Research Worker
I am a Postdoctoral Researcher (Developer) in Bioinformatics working on an MNDA grant (Dobson/Al-Chalabi) to develop a high throughput gene, environment and epigenetics database and analysis system for international ALS research.
Postdoctoral Researcher (Developer) in Bioinformatics
I am a Computer Engineer specialised in Distributed Systems. My background is in High Performance Computing, Algorithms, Cloud Infrastructure and Software Development. In the past, I have worked as IT consultant.
Software Developer BRC mHealth
Background in Biomedical Science and Bioinformatics. Current research involves large scale omics data integration for biomarker discovery, drug repositioning and screening of new therapeutic targets.
Bioinformatics Research Worker & Part-time PhD Student
My background is in Biochemistry and Epidemiology. The focus of my PhD research is utilising cognitive assessments from electronic health records to explore biomarkers and risk factors for cognitive decline in dementia.
I have a background in bioinformatics, large-scale data curation, Natural Language Processing (NLP), database programming, algorithm, NET web based technologies, Python and IT infrastructure. My PhD is focused on investigating adverse effects of psychiatric drugs through data-mining of electronic health records.
The main focus of my research focuses on using wearable devices to quantify symptomatic patient behaviours. This includes time series analysis, machine learning and app development.
I graduated with MRes degrees in Molecular Biophysics and Translational Medicine. For my PhD I am working on predicting Psychosis status by using a combination of Biological and Environmental factors. This primarily includes Transcriptomics, Biostatistics and Machine Learning algorithms.
I’m interested in the relationship between sleep disruption and relapse in schizophrenia, and in using mobile and wearable technologies to capture these variables.