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May 1, 2012 (Vol. 32, No. 9)

Mathematics Transforming Bioresearch

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    The CRC Aggressiveness Explorer developed at the Institute for Systems Biology allows researchers to visualize the molecular signatures associated with colorectal cancer. Each signature has a score indicating the statistical evidence for tumor aggressiveness.

    Human and animal health, agriculture, energy production, environmental protection, and a host of other activities of interest to humans have something startling in common: the key to improvements in all of them is likely to require a significant computational component.

    As Darwin once said “Mathematics seems to endow one with something like a new sense,” and the powerful tools of mathematics are enabling those who are able to utilize this “new sense” to see connections, structures, and even possibilities that up to now have been invisible.

    What Darwin couldn’t have guessed is that the powerful tools of mathematics would be harnessed to extraordinary computational power, and that both would be needed to deal with the exponential increase in the volume of data coming from today’s laboratories and research institutes.

    The computational power itself is increasing at breathtaking rates. In our recent past, it took 30 years to determine the complete DNA sequence of a cold virus genome. Today a virus of the same size can be sequenced in minutes. We can now read more than 500x billion bases in a week, compared to 25,000 in 1990 and 5 million in 2000.

    “We are talking about exabytes [1018 bytes] of information,” marvels Leroy Hood, M.D., Ph.D., president and co-founder of the Institute for Systems Biology.

    Where are we going with our new ability to develop larger and larger amounts of data, while marrying this information with ever more sophisticated use of Darwin’s “new sense”?

  • Revolutionary and Powerful

    For Dr. Hood, the results are revolutionary and they were powerfully encouraged by the Human Genome Project (HGP).

    “It was one of the most transforming events in biology, creating a whole cadre of mathematicians and computer scientists who applied their talents to biology,” he explains. “They expanded their views of biology and began analyzing many other types of biological questions.”

    According to Dr. Hood, the HGP meant a change in the relationship between mathematicians and biology. “Mathematicians have had a fascination with biology for a long time,” he continues, “but historically their contributions were limited.”

    The problem was too much of a top-down approach. “The great advantage of the Human Genome Project was, it was bottom up, where the objective was to define all the elements in a biological object (the 3 billion base-pairs of sequence of the 24 different human chromosomes) without consideration of hypothesis-driven questions,” he says. “It takes enormous amounts of bottom-up data to decipher biological complexity.”

    In Dr. Hood’s case, this has played out in a highly mathematical interdisciplinary systems approach to biological discovery, geared to handling extraordinary amounts of information. As just one example of the kinds of numbers in play, he points out that, “With a world population of seven billion people and with each individual having six billion nucleotides, you multiply these together and you are getting very large amounts of information.”

    The premise of the Institute’s work is that diseases result from perturbations of biological networks. These perturbations can arise from biological changes, such as mutations in the information of the genome, or from environmental influences, such as toxins or bacteria.

    Disease-perturbed networks both cause and reflect the progression of a disease. Thus, diseases can be diagnosed, treated, and prevented by understanding and intervening in the networks that underlie health and illness.

    One of the Institute’s strong points is establishing the computational infrastructure needed to analyze the thousands and eventually the millions of human genome sequences that will become available over the next 10 years. These computational tools will enable large-scale comparative analyses of human genomes and their attendant molecular, cellular, and phenotypic data.

    Dr. Hood cites two ultimate objectives of systems biology. The first is the ability to predict the behavior of a system with its emergent properties from knowing what kinds of perturbations that are applied to it. The second objective is the ability to understand the system in sufficient detail so it can be redesigned to create completely new emerging properties.

    “Being able to redesign systems whether it’s with genetics or whether it’s with drugs is going to be at the heart of the new kind of medicine that will emerge from systems biology—P4 Medicine, that is, predictive, personalized, preventive, and participatory medicine.”

    Dr. Hood has a quick example of how personalized medicine can work. “A friend of mine at Microsoft had a defect in vitamin D transporters and was suffering from osteoporosis. To reverse his osteoporosis, all he had to do was take 20 times the normal amount of Vitamin D.”

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