Assistant Professor of Psychiatry – email@example.com
My research aims to answer the following question: How can I generate a good biomarker? Aside from high sensitivity and specificity, a good biomarker must be cost-effective so it can be accessible at population level and be easily repeatable; sensitive to acute or pre-clinical phases of the disease to allow greater therapeutic windows and improve patient management; minimally or non-invasive to minimize patient discomfort and agnostic to ethnic backgrounds. Additionally, a good biomarker should be able to monitor disease progression and response to potential disease-modifying therapies. My research based on measuring RNA species in plasma is designed to address all these issues. RNA is highly dynamic, which is potentially useful for monitoring disease progression and the response to treatment. RNA can be measured by real-time PCR, a cost-effective technique routinely used in clinical laboratories. Plasma is minimally invasive, easily accessible, widely used, and stored in most biobanks. Thus, my research focuses on plasma RNA species quantification and the application of advanced bioinformatics techniques to develop novel biomarkers and to identify novel mechanisms involved in neurodegeneration and acute ischemic stroke.
Postdoctoral Research Associate – firstname.lastname@example.org
Hsiang-Han Chen received his Ph.D. in Bioinformatics and Computational Biology at the University of Minnesota. His doctoral study focuses on data analytic modeling and its biomedical applications. After graduation, he joined the Ibanez Lab as a Postdoctoral Research Associate in 2021. His research focuses on discovering new biomarkers and developing diagnostic tools for pre-symptomatic Alzheimer’s and Parkinson’s diseases using machine learning methods.
Visiting Researcher – email@example.com
Alejandro Cisterna received his Bachelor of Science in Biotechnology and his Master of Science in Bioinformatics at the University of Murcia in Spain. His doctoral studies focus on developing Machine Learning models and software for genomic prioritization of neurodegenerative diseases. Alejandro joined the Ibanez Lab for six months as part of his international training to obtain his Ph.D. His interests are focused on developing software that facilitates diverse phenotype analysis and to generate predictive genomic models for different stages of Alzheimer’s Disease and Parkinson’s Disease using cell-free RNA. He loves playing guitar and tennis.