[Paleopsych] SW: On Computational and Systems Biology

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Subject: SW: On Computational and Systems Biology

Theoretical Biology: On Computational and Systems Biology

    The following points are made by Albert Goldbeter (Current Biology
    2004 14:R601):
    1) Systems biology, computational biology, integrative biology --many
    names are being used to describe an emerging field that is
    characterized by the application of quantitative theoretical methods
    and a tendency to take a global view of problems in biology. This
    field is not entirely novel, but what is clear and significant is that
    the life sciences community recognizes its increasing importance. This
    is the really new aspect: many experimentalists are beginning to
    accept the view that theoretical models and computer simulations can
    be useful to address the dynamic behavior of complex regulatory
    networks in biological systems.
    2) Theoretical or mathematical biology has existed for many decades,
    as attested by the journals that carry these terms as part of their
    names. Until recently, however, these journals were outside of the
    mainstream and largely ignored by the majority of molecular and cell
    biologists. As the attitude to theoretical approaches in biology is
    shifting, it is not surprising to see their revival under new names,
    if only because a change in name is often needed to focus attention.
    After all, even at the cellular level, many sensory systems are built
    to respond to changes in stimulus intensity and adapt to constant
    3) The hype that currently surrounds computational and systems biology
    has the beneficial consequences of triggering further interest and
    creating a momentum for new opportunities, but it also carries some
    dangers [1], in particular that of making the field appear merely a
    fashion. The French stylist Coco Chanel once said la mode, c'est ce
    qui se demode - fashion is what comes out of fashion . In the view of
    the author, this does not apply to computational approaches to
    biological dynamics, which are here to stay.
    4) Regarding the surge of interest in theoretical approaches to
    biology it is natural to ask: why now? One triggering factor is
    undoubtedly the completion of genome projects for a number of species
    and realization that the sequences alone cannot tell us how cells and
    organisms function. Understanding dynamic cellular behavior and making
    sense of the data that are accumulating at an ever increasing pace
    requires the study of protein and gene regulatory networks. This
    network approach naturally encourages one to take a more integrative
    view of the cell and, at an even higher level, of the whole organism.
    5) Quantitative models show that certain types of biological behavior
    occur only in precise conditions, within a domain bounded by critical
    parameter values. This can contrast with the intuitive expectations
    from simple verbal descriptions. This is well illustrated by cellular
    rhythms [2,3]. Thus, cytosolic Ca2+ oscillations are triggered in
    various types of cell by treatment with a hormone or neurotransmitter.
    But repetitive Ca2+ spiking only occurs in a range of stimulation
    bounded by two critical values: below and above this range, the
    intracellular Ca2+ concentration reaches a low or a high steady-state
    level, respectively. Another example is the well-known generation of
    oscillations in models based on negative feedback. It is
    straightforward to explain in words why oscillations can readily be
    generated by negative feedback; but this verbal explanation largely
    misses the point, as it fails to explain why oscillations only occur
    in precise conditions, which critically affect both the degree of
    cooperativity of repression and the delay in the negative feedback
    References (abridged):
    1. North, G. (2003). Biophysics and the place of theory in biology.
    Curr. Biol. 13, R719-R720
    2. Goldbeter, A. (1996). Biochemical Oscillations and Cellular
    Rhythms. (Cambridge, UK: Cambridge Univ. Press)
    3. Goldbeter, A. (2002). Computational approaches to cellular rhythms.
    Nature 420, 238-245
    4. Thomas, R. and d'Ari, R. (1990). Biological Feedback. (Boca Raton,
    FL: CRC Press)
    5. Pomerening, J.R., Sontag, E.D., and Ferrell, J.E.Jr. (2003).
    Building a cell cycle oscillator: hysteresis and bistability in the
    activation of Cdc2. Nat. Cell Biol. 5, 346-351
    Current Biology http://www.current-biology.com
    Related Material:
    The following points are made by Eors Szathmary (Current Biology 2004
    1) Billions of years of evolution have produced organisms of stunning
    diversity. Some of these are relatively simple, like the bacteria;
    others show impressive complexity. For two decades, the author has
    worked on a theoretical reconstruction and understanding of the major
    transitions that generated the levels of biological organization that
    we see today. Although many in biology have an antipathy to
    mathematics, the author "simply cannot live without it." A large part
    of his research consists of making models of intermediate stages of
    organization and the evolutionary transitions between them.
    2) Although theoretical biology is avoided by many biologists because
    of their formulae phobia, theoretical biology is not necessarily
    mathematical, at least not when important ideas and concepts are
    conceived for the first time. The theory of Charles Darwin
    (1809-1882), as he presented it, was not mathematical (although later
    he commented that his reluctance to embrace mathematics was foolish,
    as mathematically minded persons seem to have an "extra sense"). But
    neither was the conceptualization by Michael Faraday (1791-1867) of
    the electromagnetic field: the mathematical structure was built later
    by James Clerk Maxwell (1831-1879). The theoretical evolutionary
    embryologist August Weismann (1834-1914) was often more rigorous than
    Darwin, but still not mathematical.
    3) The Golden Age of theoretical biology was the first half of the
    20th century, when Ronald Fisher (1860-1962), John Burdon Sanderson
    Haldane (1892-1964) and Sewall Wright (1889-1988) founded population
    genetics and Alfred Lotka (1880-1949), Vito Volterra (1860-1940) and
    Vladimir Kostitzin (1883-1963) started to build up theoretical
    ecology. These seeds have born many fruits since then. Take
    evolutionary biology, for example. A few decades after the Golden Age,
    evolutionary biologists started to tackle (ultimately with
    considerable success) questions where the Darwinian answer is far from
    obvious. Why do we age? Why are there sterile insect castes? At first
    it does not seem to make much sense to argue that your death or
    sterility increases your fitness. But evolutionary theory can provide
    satisfactory resolutions of these conundrums. In some cases even the
    question itself cannot be formulated well enough without some
    modeling: the problem of the evolutionary maintenance of sex is a case
    in point. Whole sub-disciplines, like evolutionary game theory, have
    been set up to meet such challenges.
    4) The problems become a lot harder when we come to the large-scale
    dynamics of evolution. Imagine, say, a thousand Earth-like planets
    with exactly the same initial conditions of planetary development.
    After one, two, three billion years (and so on), how many of them
    would still have living creatures? And would they be like the
    eukaryotes? We have simply no knowledge about the time evolution of
    this distribution, and "educated" guesses differ widely.(1-4)
    1> Benner, S.A. (2003). Synthetic biology: Act natural. Nature 421,
    2. Ganti, T. (1971). The Principle of Life (in Hungarian). (Budapest:
    3. Ganti, T. (2003). The Principles of Life. ( Oxford University
    4. Maynard Smith, J. and Szathmary, E. (1995). The Major Transitions
    in Evolution. (Oxford: Freeman/Spektrum),
    Current Biology http://www.current-biology.com
    Related Material:
    The following points are made by John J. Tyson (Current Biology 2004
    1) Many areas of modern science and engineering owe their strength and
    vitality to a rich interplay of experiment, theory, and computation.
    For example, quantum chemistry, aerodynamics, meteorology, and
    membrane electrophysiology are all firmly based on extensive
    quantitative observations, sound theoretical formalisms, and accurate
    predictive calculations. Molecular cell biology, on the other hand, is
    still, for the most part, proudly and precariously balanced on one leg
    -- experimental observations -- and its staunchest defenders believe
    that theoretical and computational approaches have little or nothing
    to contribute to our understanding of cell physiology(1).
    2) This view is surely wrong. A living cell is an intrinsically
    dynamical system, ceaselessly adapting in space, time, and internal
    state to environmental challenges. Catalogs of genes and static
    diagrams of the structural and functional relationships of proteins,
    though necessary for full understanding, can never adequately account
    for the dynamism of organelles and cells. Take, for example, cilia:
    these beautiful tiny whips, attached to many cells, lash back and
    forth in wondrous synchrony, propelling cells through liquids or
    liquids past cells. Without cilia you would not have been born (they
    transport eggs from ovary to uterus) and you could not breathe (they
    continually sweep mucus and debris from the lungs and airways). How do
    these elegant little machines accomplish their essential tasks?
    3) Open any modern textbook of cell biology and you will find an
    attempt to answer this fundamental question. What you will see is a
    parts list of a typical cilium -- dynein, tubulin, nexin, and so on --
    and a pseudo-color, artist's rendition of how the parts seem to be
    connected. Then a few words about how dynein molecules can pull on
    microtubules, causing then to slide past each other. End of story.
    4) This explanation leaves one unsatisfied. How are we to understand
    the dynamic function of a cilium from this static textbook picture?
    The essence of a cilium is to move in space and time. What principles
    organize the tiny pulls of each dynein motor into the "power stroke"
    that sweeps along the cilium from base to tip? What forces drive the
    recovery stroke along a trajectory so different from the power stroke?
    What invisible choreographer synchronizes the movements of vast fields
    of cilia to carry the egg to its destination?
    5) These sorts of questions cannot be answered by cataloging parts,
    defining their connections, and drawing schematic diagrams. The
    problem demands a movie. "Well then, if you want a movie, go to the
    electronic version of the textbook and click on the icon for the quick
    time movie of a beating cilium." What you will see is either a living
    cilium observed through a microscope or an animated cartoon of how the
    author imagines a cilium to move. But animation is not scientific
    explanation; it is likely to be as entertaining and as fundamentally
    mistaken as a Road Runner cartoon. What we desire is a realistic
    computation of the coordinated motion of a field of cilia, based on
    solid principles of biochemistry and biophysics, including the forces
    exerted by motor proteins on the stiff and elastic components of the
    axoneme, and the forces exerted by cilia on the viscoelastic liquid in
    which they are immersed. Although much interesting work has been done
    on this problem [2-5], a full and satisfying solution remains for the
    References (abridged):
    1 Lawrence, P. (2004). Theoretical embryology: a route to extinction?.
    Curr. Biol. 14, R7-R8
    2 Dillon, R.H. and Fauci, L.J. (2000). An integrative model of
    internal axoneme mechanics and external fluid dynamics in ciliary
    beating. J. Theor. Biol. 207, 415-430
    3 Gueron, S. and Levit-Gurevich, K. (2001). A three-dimensional model
    for ciliary motion based on the internal 9+2 structure. Proc. R. Soc.
    Lond. B. Biol. Sci. 268, 599-607
    4 Brokaw, C.J. (2002). Computer simulation of flagellar movement VIII:
    Coordination of dynein by local curvature control can generate helical
    bending waves. Cell Motil. Cytoskeleton 53, 103-124
    5 Lindemann, C.B. (2002). Geometric clutch model version 3: The role
    of the inner and outer arm dyneins in the ciliary beat. Cell Motil.
    Cytoskel. 52, 242-254
    Current Biology http://www.current-biology.com

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