Founder, CEO, Epilepsy Advocate

nathan@netadiscovery.org

My fascination for neuroscience has been present for some time with a family member with KBG syndrome and myself having a lived experience with Epilepsy. This led to a recent PhD journey in studying transcriptomic data to better understand mechanisms of Epilepsy. With my developed understanding of bioinformatics as a result of long nights of computing code to unlock biological pathways, I realized a lot more could be done and needed to be done post PhD. So, with this initial journey and being an Epilepsy advocate I have founded Neuronal Epileptotranscriptomic Advancement (NETA).

Chairman

Focus on experimental medicine, a research collaborator and a highly skilled biological and medical information integration specialist. My research disciplines span pharmacology, physiology, translational medicine . My passion is to improve and understand the burden of chronic conditions. In doing so understand drivers of disease, develop health solutions that improve both disease outcomes and quality of life.

COO

With deep expertise in Structural Biology and Biochemistry, my PhD journey has been marked by significant contributions in molecular biology, focusing on protein expression, purification, and characterization. My work has been recognized in leading scientific journals and conferences, highlighting my skill in molecular dynamics and protein interactions.

Research Interests

Committed to drug development, particularly in viral research and transcription factor studies, aiming to merge structural biology with clinical research for groundbreaking advancements.

Scientific Advisor

I have 20 years' experience in deciphering genomics data, including NGS (next-generation sequencing) data analysis, such as genomic, epigenomic, transcriptomic, proteomic and metagenomic analysis, focusing on gene regulation, pathway and causal network analysis, gene signature and biomarker analysis; Constructing integrative genomics platform to serve in design and analysis of NGS experiments.

Research Interests

1: functional characterisation of disease associated genetic changes with AI-enabled approaches, for drug target ID and validation

2: linking disease phenotypes with epigenetic variations, for disease diagnosis and prognosis

3: predicting gene expressions using large-scale genetic and epigenetic data, for disease biology and target MOA