We develop algorithms for retrieving and storing glycans, analysing their tree like structure and methods for glycan data analytics
We are involved in human disease research through employing statistics and bioinformatics methods such as multivariate analysis and gene expression profiling. The core focus of the research in the Bioinformatics Research Group is developing computational strategies that provide novel biological insights into human disease mechanisms and to introduce potential biomarkers for early diagnosis.
The main objective of the informatics group at SCRU is to undertake human disease-associated research where we strive on understanding disease mechanisms to identify possible diagnostic biomarkers. We employ statistical and bioinformatics approaches in analyzing a diverse range of data for complex diseases.
It was Linus Pauling that first recognized that the Transitions State (TS) along the enzyme catalysed reaction sequence binds the enzyme strongest. It was later proposed that a chemically stable molecule that resembles the TS state would be expected to bind to an enzyme tighter than its natural substrate. These chemically stable TS mimics are known as Transition State Analogues (TSAs). We develop TSA families (Hits) based on the findings from the reaction dynamics studies undertaken in SCRU’s C&M laboratory. These families are then narrowed down to leads using cheminformatics methods.
A primary goal of large scale data analysis and trend prediction is clear communication of significant and relevant trends in the context of the research question. We are investigating interactive and smart device compliant technologies as well as graphing algorithms in order to provide comprehensive, yet concise, visual analytics for chemical and biological data sets. We are emphasizing the integration of data from multiple frames of reference.
Scientific Computing Research Unit
Room 6.37, 6th Level
PD Hahn Building, North Lane
University of Cape Town
7701 Tel: 021 650 2568 Email:email@example.com