COMPUTATIONAL BIOLOGY

The modern biology researcher faces vast amounts of data produced by high-throughput analytical technologies for DNA, RNA, and proteins.​

This rich and complex mix of data is also confounded by a variety of biological and nonbiological factors, which makes it difficult, inefficient, and inaccurate to draw the right research conclusions.

By understanding and exploiting properties of the underlying biology, instruments, technologies, and experiment designs, we develop advanced methods to process and analyse these large amounts of complex, biological data – which help solve problems in biology, biotechnology, and medicine.

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WHAT WE DO

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Develop effective and efficient algorithmic techniques used in the acquisition, storage, analysis, and dissemination of biological data.

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Design innovative and elegant computational approaches to decipher the structure, function, and behaviour of cells, and explore how changes in these affect phenotypes.

SUB AREAS:

Bioinformatics Algorithms

Omics Data Analysis

​Learning Theory

​Machine Learning

OUR RESEARCH PROJECTS

OUR RESEARCH GROUPS