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Joint CMU-Pitt Ph.D. Program in Computational Biology
Robert F. Murphy and Ivet Bahar, Directors
Background Information on Computational Biology
Computational Biology is the research field concerned with solving biological problems using mathematical and computational methods. It is grounded in theories and concepts of life, physical and quantitative sciences. The methods have their origins in various scientific computing traditions including those in physics, chemistry, engineering, and computer science.
There have been fundamental changes in biological and biomedical research methodology and topics in recent years due to spectacular advances in genomics/proteomics as well as computer technologies. The major impact of the burst of sequence and expression data at genome scale and the recent advances in spectroscopic and imaging techniques was not, however, to elucidate the origin and mechanism of biological events as the naive gene-to-drug paradigm would imply, but to demonstrate that there is a need for novel theories and advanced tools in order to decipher the implications of these data, and devise methods of controlling/modifying biological function.
New initiatives are now taking shape after the completion of genome sequencing projects, such as structural genomics, functional genomics or proteomics. There is now a shift in emphasis - from sequence to structure, from genes to proteins and their complexes, from interacting pairs to interaction networks. There is also a change in the scale of the explored processes, from atomic/molecular to supramolecular, cellular and systems levels. It is now clear that researchers should develop theories and methods that extend
- beyond DNA and protein sequences, but decipher sequence-structure-function relations;
- beyond static images/structures of biomolecules, but simulate their dynamics
- beyond single molecules/pairs, but model networks/cascades of interactions.
Furthermore there is a need for characterizing structure and function at multiple scales to establish the link between genotype and phenotype. Experiments cannot meet this goal unless conducted in coordination with theoretical, mathematical and/or computational models and methods that allow for
- high throughput analysis and organization of biological data, and
- realistic visualization and simulation of complex processes.
Computational Biology is a field that encompasses a wide range of topics, ranging from molecular modeling and protein dynamics to large-scale analysis of genome/proteome data. One of the promises of computational biology is the ability to manipulate vast amount of data in a time span not possible by traditional experimental techniques. Researchers who will develop and implement theories, methods and tools in this field must be comprehensively trained on the current state-of-the-art to acquire the quantitative background and skills to advance the field, and be in a position to appreciate the potential, strength and limitations of computational, mathematical, and engineering tools for tackling biological problems.
Computational biology is being recognized as an essential and indispensable field in biomedical research. This bas gained tremendous popularity in recent years due to the availability of high computing power to scientists, development of user-friendly graphical-user interfaces in commonly used software applications, and the efficiency with which these studies can be carried out relative to traditional methods.
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