Research Overview

Biomolecular Sequence to Function Division (BSFD)

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. Function determination from gene expression to protein sequences and cellular pathways is a first and necessary step towards systematic understanding of biological systems.

What is truly unique about the Biomolecular Sequence to Function Division is the group's interactive and integrated research. Scientists from multiple disciplines work closely together to fully understand different aspects of the inherently complex systems intrinsic to living organisms, covering the triad of (i) sequence function prediction supported by (ii) intelligent software-workflows and (iii) latest AI algorithms.

Research Objectives

The major goal is the determination of the various aspects of molecular and cellular function (enzymatic activities, posttranslational modifications, 3D structures, translocation signals, etc.) from sequences and the discovery of new cellular pathways with novel methods from computational biology and artificial intelligence. 

This division consists of FIVE groups:



Biomolecular Structure to Mechanism Division (BSMD)

Research Overview

The Biomolecular Structure to Mechanism Division 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 division'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 division is highly interdisciplinary in origin and approach and works extensively with experimental and clinical partners and with the pharma industry.

This division consists of FIVE groups:



Cellular Image Informatics Division (CIID)

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 five 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", "Biophysical Modelling", "Computational Digital Pathology" and "Clinical Data Analytics & Radiomics"

This division consists of FIVE groups:



Biomedical Data Hub Division (BDHD)

Research Overview

Data Hub division is a centralized effort to engage eminent research cohorts, health clusters and public sector to strategize and develop an enterprise grade datahub and an advanced biomedical informatics
platform. Our Clinical Engagement arm specializes in integrated omics and clinical data analytics. We use  these capabilities for risk prediction modelling, disease surveillance and intervention discovery. We cover molecular phenotyping and data analytics across a broad spectrum of health adversities and age groups. We also cover electronic health records and real-world data to achieve precision health objectives and enhance human potential. The key objective of this group is to use multidimensional data to develop advanced patient journey applications and build intervention roadmaps for clinicians.

Our Data Architecture & Repository arm specialises in data-life cycle management of clinical research data from public hospitals where these datasets can be both structural (clinical information) and non-structural (sequencing, imaging, IoT) in nature. We also have in-place proper data governance framework which is compliant and an 27001-compliant secured compute environment to host post-approval data analysis activities. In a nutshell, we provide a secured and governed collaborative playspace for both clinical data owners and data scientists to foster their scientific ideas.


This division consists of FOUR groups: