Bioinformatics is a multi-disciplinary approach combining computational and biological expertise to analyse biological data (both genomic and clinical), to advance biomedical research and development. Bioinformatics is both a science and an engineering art, concerned with the application of mathematics, physical/chemical principles and information technology to solve biological problems.

In the Bioinformatics Institute, there are four methodology-oriented research divisions comprising of research groups led by independent Principal Investigators that focus on specific areas of computational biology. The common denominator is the goal of understanding biomolecular mechanisms underlying cellular phenomena, which is the basis for a rational understanding of pathogenesis or for planning biotechnological applications.


Research Overview

Functional interpretation of genome data in terms of biomolecular mechanisms is the major task in fundamental life science. Research results in this area will boost mechanistic research in other areas such as cell biology, genetics, immunology and disease-oriented fields. Gene function determination is a first and necessary step towards systematic understanding of biological systems.

What is truly unique about the Biomolecular Function Discovery Division is the group's interactive and integrated research. Scientists from multiple disciplines (molecular biology, genetics, biochemistry and bioinformatics) work closely together to fully understand different aspects of the inherently complex systems intrinsic to living organisms, covering the triad of (i) gene function prediction supported by (ii) intelligent software-workflows and (iii) experimental verification.


Research Overview

The Biomolecular Modelling and Design Group is involved in unraveling the fundamental links between sequence, structure, dynamics and biological functions of molecules such as proteins. Recent advances in computational approaches, in conjunction with data obtained from various experimental techniques, have provided detailed atomistic insights into biological complexity. The group's approach follows this philosophy - to be tightly coupled to experimental laboratories such that testable hypotheses are generated and a feedback mechanism of predictions and validations exists between the groups.

To generate hypotheses about biomolecular functions, we model both evolutionary as well as physical behaviour. The hierarchy of methods, ranging from fast low resolution (evolutionary/comparative analysis) methods to detailed microscopic analysis (docking/electrostatics/Molecular Dynamics/Normal Mode Analysis/Reaction Paths), leads to focused groundwork for experiments to establish the molecule's role in its complex biological setting. The group is highly interdisciplinary in origin and approach and works extensively with experimental and clinical partners and with the pharma industry.


Research Overview

For over three centuries, light microscopy has served as a powerful and indispensable tool for making important biological discoveries. The entry of digital imaging into microscopy has given rise to a new branch of bioinformatics research, also known as Bio-Imaging Informatics. Irrespective of the type of detection device, whether it is the human eye, a camera or an electronic scanner, the human brain still remains the major interpretation engine of image data. However, technological advances in instrumentation, such as 3-dimensional time-lapse imaging and high-throughput screening platforms, have led to experiments that routinely produce thousands of images containing billions of pixels. It is obvious that the manual processing and analysis of images traditionally performed by human experts is increasingly becoming inefficient, incomplete and imprecise.

The four groups of the Imaging Informatics division are dedicated to the field of quantitative microscopy which aims to automate the interpretation of images by applying methods in computer vision, machine learning and statistics. The research groups focus on "Computer Vision and Pattern Discovery", "Complex Cellular Phenotype Analysis", "Machine Learning For Bioimage Analysis" and "Biophysical Modelling".


Research Overview

The Natural Product Biology and Natural Product Chemistry groups jointly explore the chemical and genetic diversity of the plants and microbes within the A*STAR Natural Product Library to discover new bioactive compounds and enzymes for industrial application. The Chemical Genomics group uses chemical genetic tools in Saccharomyces cerevisiae (budding yeast) to uncover targets of bioactive compounds, reveal functions of genes and identify inhibitors of Protein-Protein Interactions. Started as a joint BII-p53Lab in Oct 2013, Antibody & Product Development (APD) Lab worked on Antibody Engineering, Viral drug resistance, Drug development, Scientific Phone Apps, IoT devices, Psychology, Augmented Reality, and psychology game apps.