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This article by Barbara Fox was prepared for the April 30, 2003 edition of U.S. 1 Newspaper. All rights reserved.
Meet the Minds of the Icahn Laboratory
When Princeton University first planned to create a
genomics institute in January, 1999, Shirley M. Tilghman was to be
the director. But when she became president of the university in 2001,
genetics pioneer David Botstein was named to the institute post.
Botstein, who remains at Stanford University through June, has established
key genetic techniques that are used today. In 1980 he and three colleagues
proposed a method for mapping genes that laid the groundwork for the
Human Genome Project. He also led the effort to map and sequence the
yeast genome, which in 1996 was the first large genome of its kind
to be sequenced. "He has been a leader in thinking about the databases
that are necessary in a post-genome era to collate and integrate all
of the data that are coming in from so many sources," says Tilghman.
Botstein has also been effective at integrating approaches from disciplines
outside biology, such as physics and engineering, says Tilghman: "He
understands both the enormous promise of that kind of research and
the difficulty of it. He doesn’t underestimate how hard it is."
David Botstein grew up in New York City, where both his mother and
late father were physicians. His brother, Leon Botstein, is the president
of Bard College, and his sister is a physician. With a bachelor’s
degree from Harvard and a doctoral degree from the University of Michigan,
Botstein taught at Massachusetts Institute of Technology from 1967
to 1988 and was vice president for science at the biotechnology company
Genentech for two years, before taking a teaching position at Stanford
School of Medicine.
Botstein says he is looking forward to doing both research and teaching
at Princeton. "The emergence of the data from the Human Genome
Project completely changes the way biology can and will be done,"
he says. "The question of what kind of preparation young people
should have in order to enter into this exciting new world requires
"My experience and the experience of the people around me is that
students ask very good questions, and you know you are in an area
in which not enough is understood when you can’t give a straight answer
to a relatively simple question," he says.
Based on similar projects at MIT, Botstein hopes to develop a series
of undergraduate courses called "project labs," emphasizing
current research questions and cutting-edge techniques and challenging
challenge students to address the same kinds of questions being investigated
by the institute’s faculty.
"They’ll be faced with the interdisciplinary problem right from
the beginning. For those with talent for it, I think that will guide
their subsequent choice of how to educate themselves in a much better
way than following in the path of standard disciplines," says
Botstein. "We are recognizing that biology has become, in the
post-genome-sequence period, an information science and these young
people are world leaders in that intersection of biology and information
— Barbara Fox
The intradisciplinary research in the Carl Icahn Laboratory
will focus on biological networks. Five faculty members in the Lewis-Sigler
Institute will have their laboratories and offices in the new Icahn
building, and the sixth member, Harold Shapiro, — the president
emeritus of the university — will participate in seminars on bioethics
but will keep his current office. A seventh faculty member, interim
director James Broach, will retain his laboratory in the molecular
biology department. David Botstein, the director, moves in on July
To be appointed are five Lewis-Sigler fellows, who will teach and
be able to do research without having to raise grant money. In the
coming years additional research groups will be added. Together with
assistants and graduate student fellows, the building will house from
10 or 12 research groups and 125 to 150 people.
Saeed Tavazoie: Molecular Biologist
Saeed Tavazoie, a molecular biologist, is studying the
properties of intracellular networks — called transcriptional
networks — that regulate the expression of genes. These networks
control the intuitive behaviors of cells, such as expression, adaptation
Scientists have been using genetic and biochemical techniques to discover
how genes are regulated at a single location, but little is known
about the global structure of transcriptional networks — their
overall connectivity and organization. "In addition, we lack the
conceptual framework for integrating such knowledge into a predictive
understanding of their dynamics," writes Tavazoie. "We are
using genomic, computational, and analytic methods to address these
Among the research activities in his laboratory are the development
of algorithms for inferring the structure of networks from genomic
data, and the development of new methods to validate computational
predictions of networks. He also tries to elucidate combinatorial
logic — what happens when more than one "connection" of
a transcription factor and a DNA binding site is regulating the activity
of a gene.
"Evolution provides us with a unifying perspective," writes
Tavazoie. "Our long-term goal is to better understand how the
structural and dynamical properties of networks reflect, and depend
on, the physical, chemical, multicellular, and ecological contexts
in which they have evolved."
Stas Shvartsman: Chemical Engineer
Stas Shvartsman, a chemical engineer, takes a multidisciplinary
approach — using reaction engineering, transport theory, applied
mathematics, and computation — to study the computational biology
of cell signaling networks.
Because defects in these networks may lead to a range of diseases,
he wants to develop mechanistic, predictive models of them. These
models could be used to assign the functionality of signaling networks
in different organisms. "Organisms as diverse as fruit flies and
humans rely on homologous molecular components and network architectures
for similar biological functions," writes Shvartsman.
Mona Singh: Computer Scientist
Mona Singh, a computer scientist, develops computational
methods for predicting protein-protein interactions within an organism
solely on the basis of sequence information. "We are particularly
interested in developing algorithms for genome-level analysis of protein
structure, function, and interactions," writes Singh.
"Since a genome contains a complete `parts list’ of an organism,
whole-genome data allows one to begin to address exhaustively the
problem of determining and predicting which proteins can interact
with each other. Traditionally, knowledge of protein-protein interactions
has been accumulated from biochemical and genetic experiments; however,
as whole-genome data accumulates, it becomes increasingly necessary
to develop computational methods for predicting these interactions.
Computational methods have already proven to be a useful first step
for rapid genome-wide identification of putative protein function
and structure, but research in the problem of computationally determining
biologically relevant partners for given protein sequences is just
"Much of our work on predicting protein structure and protein-protein
interactions has focused on the coiled coil motif. The coiled coil
is a common and important structural motif that mediates protein-protein
interactions, and is found in proteins involved in transcription,
in cell-cell and viral-cell fusion events, and in maintaining the
structural identity of cells. We have developed highly effective sequence-based
methods for identifying whether a given protein sequence can take
part in a coiled coil structure, and are currently developing novel
computational techniques to predict whether two coiled coil proteins
interact with each other, and if so, what the nature of this interaction
William Bialek: Physics Professor
William Bialek, a physics professor, is interested in
attaching numbers to the intuitive assumption that living systems
"do a good job" at solving many different problems. Even single-celled
organisms, such as bacteria, sense their environment and control their
internal chemistry, he says. "The same problems of sensing and
control occur for every cell in our own bodies, but we also use our
brains to build an internal representation of the world and to learn
the rules that operate in the world."
For each of these different problems Bialek has explored the theoretical
limits to what biological systems can do given the "hardware"
that they have to work with. In many cases he and his colleagues have
been able to show how an organism has selected a set of nearly optimal
mechanisms for its most crucial tasks. This search for optimality
has led, for example, to the discovery of new phenomena in the neural
code, the "language" that the brain uses to process the information
that we take in through our eyes, ears and other senses.
John J. Hopfield: Computational Biologist
John Hopfield, a computational neural biologist, examines
how the neural circuits of the brain produce such powerful and complex
computations. All his work is with computers, using systems of differential
equations to model and represent aspects of neurobiology.
"I do computer simulations of the way that large networks of neuro
cells behave," says Hopfield. "The basis for these models
is a century of research in neuro biology. The models make predictions
and I can then go to friends in a neurobiology laboratory to find
out if those predictions have some kind of correspondence to reality."
"While the brain is totally unlike modern computers, much of what
it does can be described as computation. Associative memory, logic
and inference, recognizing an odor or a chess position, parsing the
world into objects, and generating appropriate sequences of locomotor
muscle commands are all describable as computation," says Hopfield.
"We seek to understand some aspects of neurobiological computation
through studying the behavior of equations modeling the time-evolution
of neural activity."
"Identifying words in natural speech is a difficult computational
task which brains can easily do," writes Hopfield. "We use
this task as a test-bed for thinking about the computational abilities
of neural networks and neuromorphic ideas."
Hopfield also studies how rats or garden slugs employ their sense
of smell to understand what objects are present in the environment.
"We have been studying how such computations might be performed
by the known neural circuitry of the olfactory bulb and prepiriform
cortex of mammals or the analogous circuits of simpler animals,"
David Tank: Biophysicist
David Tank, a biophysicist, studies cellular and circuit
mechanisms of persistent neural activity and chemical dynamics in
neurons. Persistent neural activity is a form of neural circuit dynamics
associated with short-term memory.
"Persistent neural activity is a sustained increase or suppression
of action potential firing elicited by a brief sensory stimulus or
motor command," Tank writes. "Across the population of participating
neurons, the pattern of sustained changes in action potential firing
is correlated with the information held in short term memory, while
disruption of persistent activity produces deficits in memory-guided
behavior. These characteristics suggest that the memory is actually
the dynamic state of the circuit."
"Many of our experiments are designed to test the hypothesis that
persistent activity is produced by positive feedback implemented by
recurrent excitation through synaptic connections and to explore the
importance of particular synaptic currents."
Tank is also trying to measure the chemical and electrical dynamics
of neurons by using laser scanning microscopy to study the concentration
of calcium in nerve terminals in the mammalian brain.
James Broach Molecular Biologist
James Broach, a molecular biologist, is the acting director
of the Lewis-Sigler Institute until David Botstein takes over this
summer. Broach will not be moving his laboratories to the Icahn building
but will have a close association. He studies how cells process information
gleaned from their environment to make decisions regarding growth
and development. Using baker’s yeast as a model organism, he employs
new genomic analysis tools to examine the cell’s response to nutrient
availability. He monitors simultaneously the changes in activity of
every one of the 6,000 genes in the organism.
One outcome of this analysis is a deeper understanding of the function
of the yeast version of the human Ras oncogene, the gene most often
mutated in human cancers. The analysis conducted by Broach’s group
identifies therapeutic targets that could be used to reverse the tumorigenic
state of those cancers.
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