Personal profile
Biography
Jasmyn Gooding is a PhD Researcher in the school of Computer Science (CMP) and Research Coordinator in the Faculty of Medicine and Health (FMH) at UEA. She completed her first degree (MSci) At UEA in Biology, with a focus on bioinformatics and evolution
Her research in CMP focuses on applying Deep Learning (DL) to dissect evolutionary signals, in the context of genomics and extinction prediction. She uses forward in time simulations to model species, varying both popluation and genetic parameters to create synthetic data to traing DL models on.
In FMH her role resolves around coordinating Patient and Public Involvement (PPI) activities across >10 currently funded research projects. Aswell as supporting PPI in the the pre-application phase for >30 projects and felowships.
She has a facilitation Role in:
- INfLAIM; Inflammation, nutrition, and the evolution of multiple long term conditions – an AI-based analysis of intersectionality in longitudinal health data,
- AISCS: Improving anxiety assessment in Stroke and Aquired Brain Injury: the validation of Anxiety Intensity Scale Circles and the Yale-anxiety, and Natural Language Proessessing Models.
She is also passionate about science communication, being involved with the Norwich Sciences Festival for the last 5 years aswell as delivering numerous talks.
Alongside these research roles Jasmyn is a Associate Tutor teaching on Maths, Machine Learning and Programming Modules.
Academic Background
I am currently pursing a PhD under the supervision of Dr Taoyang Wu (CMP) and Prof Cock Van Oosterhout (ENV) with a focus on developing Deep Learning Models to assess exitinction risk and recovery potential of species.
I hold a Master of Science Degree (MSci) from UEA, where I completed 3 years following the BSc programme and one additional year to complete a masters research project. During the first 3 years my study and research interestes here interdiciplinerary this high acheievements in modules which had a focus on:
- data science
- evolution
- molecular biology and genetics
- physiology
- health and disease
During my masters year my research concentrated on using a population of long-term monitored great tits (Parus major) and blue tits (Cyanistes caeruleus) as a model for investigating corresspondance between social network manipulation and measuring cognition and behaviour in the wild. This involved extensive data analysis in R and python. Alongside my primary research, I collaborated closely with a PhD student investigating the gut microbiome in wild bird populations. My involvement included assisting with the capture and handling of birds in the field, collecting faecal samples for microbiome analysis, and processing samples in the laboratory using sterile techniques. Through this experience, I developed a range of wet lab skills, bulding on my already extablished experience in DNA extraction, PCR amplification, and gel electrophoresis. This strengthened my technical competencies but also deepened my understanding of host-microbiome interactions which led to me completing a short project where I review of research into the Gut-Brain axis aswell as a critical review of The Loss of Ancestral Microbiota and its Implications for Modern Human Health.
Research Group or Lab Membership
Member, Computational Biology Lab
Member, Lifespan Health
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Master in Science, Biological Sciences, University of East Anglia
2020 → 2024
Keywords
- Bioinformatics & Computational Biology
- machine learning
- Evolution
- Medicine (general)
- Patient and Public Involvement
- MLTCs