The dilemma of modern biology, and in particular molecular biology, is that staggering amounts of data have been and still are being accumulated and stored, but the question of what to actually do with this vast data set is still in its infancy. A great deal of emphasis in biological science is placed upon bioinformatics , essentially storing information and data in library catalogs that can be retreived. The main examples here are the mapping of the human genome and the vast stores of information on protein structure that are held in various protein data banks. The dna sequences of hundreds of organisms have been decoded and stored in this way, and massive sequencing efforts seek to identify mutations in a variety of genes in cancers. The vast volume of data that is produced requires automated/computer systems to read it and to compare sequencing results; consequently there have been considerable advances in computational biology and bioinformatics/biostatistics with major efforts in gene finding, sequence alignment, genome assembly, protein structure etc.
This is of course very important but in itself may never reach the deeper understanding of what actually makes life function, and how these processes can go awry and produce pathological states, disease and cancer. The list of ‘working parts’ is essentially complete but a deep and fundamental mathematical-physical understanding of how the parts actually function together to generate the underlying processes of life is still essentially lacking–the whole is still much greater than the sum of the parts. The explosion of information produced by the genomics revolution will be difficult to understand without the continued application of powerful mathematical methods. Knowing how to properly describe and fully utilize this data using such methods could also open up new and powerful applications in medicine, genetic engineering, drug design and cancer therapy.
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