Antisense oligonucleotides (ASO) are a class of drug molecules that are made of short nucleotide sequences (DNA or RNA) which can bind to RNA and alter its function. Some modifications that are made during the synthesis of these drug molecules can introduce different chemical configurations which in turn affect its pharmacokinetics.
This project aims at understanding the diastereomeric composition of antisense oligonucleotide drug products through investigating how different synthesis processes affect the chemical composition of the drug.
This research seeks to understand and identify predictive functional relationships in neurodegenerative diseases, specifically traumatic brain injury (TBI) and Alzheimer’s disease (AD). TBI is a leading cause of death in persons under the age of 45, and AD is the leading cause of dementia and a leading cause of death in persons over the age of 65. Despite the apparent difference in relevant populations, previous research has shown links between the two as well as between each disease and age.
Tuerk House (TH) is a drug addiction treatment facility serving the Baltimore, MD area. We work in collaboration with TH, Professor Edward Bernat, University of Maryland, and Professor Fadia Shaya University of Maryland Baltimore, School of Pharmacy to analyze the electronic medical record data from TH.
We are currently in the process of creating a rich and multifaceted data set centered on the TH patient population by engineering the data available in the TH EMR.
Movement disorders refers to a group of nervous system conditions that cause abnormal increased or reduced movements, which may be voluntary or involuntary. With the widespread availability of sensor devices many chronic diseases can be monitored as patients performed a variety of free body movements. Machine learning techniques can then be applied on sensor (e.g., accelerometer and gyroscope) and non-sensor variables (e.g., age, sex, other medical conditions) to create models that classify patients into either preconceived (supervised learning) or novel classes (unsupervised learning).
The purpose of this research project is to accurately infer the proportion of each ancestral populations in an organism by infering the ancestry of each genetic locus in the genome of an organism.
Reverse vaccinology focuses on identifying potential vaccine candidates from the perspective of the entire pathogenic genome. In 2000, Rino Rappuoli and colleges first used reverse vaccinology to screen the Group B meningococcus genome and developed the MenB vaccine. With the improvement of sequencing techniques, the integration of organism databases, and the development of many useful bioinformatics tools, reverse vaccinology has been successful in discovering previously unknown antigens and accelerating the development of vaccines.