A New Biology for the 21st Century (2009) / Chapter Skim
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3 Why Now?
3 Why Now?
Pages 39-64
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From page 39... ...
These technologies led in turn to the electronic industry, the computer industry, and the information technology industry, which together have created a world that could scarcely have been imagined a century ago. Before the transition associated with the discovery of the electron, scientists gathered increasing amounts of data, but those data could not be put to full use because of the lack of a conceptual framework.
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From page 40... ...
Because living systems are so complex, much biological experimentation has had to focus on individual or small numbers of components within a single organizational level. The reductionist approach has helped reveal many of the basic molecular, cellular, physiological, and ecological processes that govern life.
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From page 41... ...
Genetics, cell biology, ecology, microbiology, biochemistry, and molecular biology each took on various aspects of the challenge. The sheer volume of knowledge generated in each of these subdisciplines made it increasingly difficult for researchers who studied organisms to keep up with the progress being made by researchers studying cells, and those studying molecules rarely interacted with those studying ecosystems.
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From page 42... ...
To accelerate progress in the life sciences, researchers from different subdisciplines need to interact and collaborate to a greater extent. Presenting these communities with a common problem to solve will provide an opportunity for them to bring their different skills and perspectives to bear and accelerate the development of conceptual and technological approaches to understanding the connections between the different levels of biological organization (Box 3.3)
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From page 43... ...
Moreover, drugs shown to have efficacy in such animal models have failed in human clinical trials. Better understanding of which characteristics are shared and which are not is a major outstanding challenge in biology, which, when met, will greatly improve our ability to predict how results in one organism will apply to another.
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From page 44... ...
As an indication of the kind of mathematical and computational tools needed, analyses of gene sequence data to derive the phylogeny of the animal kingdom required the full-time use of 120 processors over several months (Hejnol et al., in press)
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From page 45... ...
Even with technologies based on the physical and chemical sciences, there remain many poorly characterized parameters. These limitations also apply to the biological systems, even under the best of circumstances, so bringing an engineering mindset to bear on biological questions is already beginning to add a new layer of value to basic biological research.
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From page 46... ...
In the case of the brain-machine interface that permitted monkey thoughts to make a robot walk, the electrodes were placed in the part of the brain that earlier neurobiological studies had shown contained neurons that fired when primates walk. Detailed video images of leg movements were then combined with measurements of simultaneous brain cell activity, and then analyzed using sophisticated computational methods.
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From page 47... ...
WHY NOW? 47 BOX 3.5 Nanotechnology -- The Artificial Retina The intertwined nature of the physical and life sciences is exemplified in the prog ress that has been made with the artificial retina, a device that resulted from a multi laboratory initiative supported by the Department of Energy.
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From page 48... ...
Many of the advances in sequencing technology were incremental, but there were some game-changing developments, like the demonstration that random shotgun sequencing could be applied successfully to a large complex genome. That kind of transformative event cannot be predicted, but setting an important goal and providing
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From page 49... ...
Random shotgun sequencing, in which a computer detects overlaps of raw sequencing "reads" to construct a complete genome, was not considered useful for human genome sequencing due to the size and complexity of the human genome. However, with the development of new sequencing and computational methods (developed by engineers and computational scientists who turned their efforts to solving biological problems)
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From page 50... ...
, we must be able to determine the composition of such communities, how they function under conditions that promote the health of the system, and the effects of imbalances in these communities when they are perturbed. The patterns that emerge from these studies can be used to develop predictive models, so that we might recognize problems early and intervene before the situation is irreversible.
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From page 51... ...
WHY NOW? 51 Confocal micrograph depicting the colonization of host animal tissues (blue)
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From page 52... ...
Another lesson from the Human Genome Project is that even scientific efforts that appear incremental can spawn transformative advances. Similar efforts to allow systematic characterizations at other levels of biological complexity, like the cell, organism, and community, could have similarly dramatic downstream payoffs.
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From page 53... ...
While information on genome sequences is relatively straightforward to represent because of its onedimensional nature, it is much more difficult to represent information on the biological function of genes and proteins and their organization into dynamic cellular processes. Nevertheless, much of the output of life sciences researchers is now captured in electronic form, and databases now include far more than just DNA sequence data.
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From page 54... ...
This combination of techniques provides unprecedented insight into the molecular organization of cellular landscapes. Similarly, the technology to characterize the location and activity of individual cells within a living organism is also improving.
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From page 55... ...
Quantum dots (QDs) provide a powerful tool for biological investigations.
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From page 56... ...
High-Throughput Technologies Recent advances in DNA sequencing technologies have been tremendous. Using current next-generation technology, the Joint Genome Institute, headed by the Lawrence Berkeley National Laboratory and Lawrence Livermore National Laboratory, sequenced over 20 billion nucleotides in the month of October 2008 (DOE Joint Genome Institute, 2009)
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From page 57... ...
. Because DNA polymerase incorporates complementary nucleotides, monitoring the fluorescent signal of the added nucleotide during synthesis allows one to determine the DNA sequence of the original DNA.
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From page 58... ...
Silicon microelectronics has made computation ever faster, cheaper, more accessible, and more powerful. Microfluidic chips, feats of minuscule plumbing where more than a hundred cell cultures or other experiments can reside in a rubbery silicone integrated circuit the size of a quarter, could bring a similar revolution of automation to biological and medical research.
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From page 59... ...
. These monitoring approaches are also beginning to impact ecological sciences, with real-time 24/7 monitoring of habitat function within reach.
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From page 60... ...
Efforts to create effective environments along these lines have accelerated since the early 1990s, in a field generally called "tissue engineering." Tissue engineers develop materials, scaffolds, or devices that provide biochemical and biophysical cues to facilitate cell survival, proliferation, differentiation, and organization into functional three-dimensional tissues. The field of tissue engineering promises to provide more effective experimental systems for studying complex human tissue physiology and pathophysiology in vitro.
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From page 61... ...
The lesson from physical and chemical sciences over the past century is that a combination of quantitative multivariate measurement with computational analysis is typically essential for predictive models, and the challenge for life science is that for the foreseeable future it will still have an incomplete knowledge of all of the components and interactions that make up biological systems. Improved measurement technologies and mathematical and computational tools have led to the emergence of a new approach to biological questions, termed "systems biology," which strives to achieve predictive modeling.
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From page 62... ...
It clearly can be anticipated that development and application of novel mathematical and computational approaches will be motivated by the difficult problems continuing to arise in systems biology due to issues such as incomplete information concerning system components and properties, heterogeneity and stochasticity, convolution of biochemical and biophysical processes, and the multiple length- and time-scales inherent in attempting to establish predictive models at all levels of biological organization, from the molecular, through the organism, population, ecosystem, and finally, the global scales. Computational Biology Biology and mathematics have long been intertwined.
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From page 63... ...
. Conclusion All of these factors -- increasing integration within the life sciences and between the life sciences and other disciplines, a deep pool of detailed knowledge of biological components and processes, previous investment in the generation of shared data resources, stunning technological innovations, and crosscutting sciences that are foundational across many applications -- have put the
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From page 64... ...
The United States was a leader in the development of the life sciences throughout the 20th century and would benefit greatly by remaining in that position in the 21st century. Especially in economically challenging times, the drive to stay at the forefront of critical areas of research can motivate needed investments and changes.
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