Waiting for Einstein

The dawn of a unified theory of biology may finally be upon us.

By | October 1, 2008

I just finished reading a biography of Albert Einstein by Walter Isaacson (Simon & Schuster, 2008) and thoroughly enjoyed it. I have long been fascinated by how this one man was able to revolutionize physics in the early 20th century.

Isaacson argues that Einstein achieved his breakthroughs by creating a conceptual framework that could link disparate areas of physics. This framework was built by combining experiments, theory and philosophy. Einstein's deep intuition regarding experimental systems (from his days as a patent clerk), skill in mathematics, and his philosophical perspective of causality provided the means to create theories in quantum mechanics and relativity that could make testable predictions spanning the smallest to the largest processes in the universe.

The 21st century has been called the era of biology, just as the 20th century was for physics. The sequencing of the human genome and the exponential growth in biological knowledge gives credence to such claims. Unlike physics, however, we are still a long way from a unified understanding of biological processes that can predict outcomes from first principles. But there is optimism that it will come.

Biology certainly has a lot of experimental data on which we could build a unified foundation. We even have functional philosophies in the form of empiricism and the scientific method. However, we are woefully short on quantitative biological theories or logical or mathematical frameworks by which we could generate testable predictions in the way that relativity and quantum theory did.

There have been attempts to generate a theoretical framework for some aspects of biology, such as "metabolic theory,"1 but these tend to be focused on explaining a subset of biological phenomena based on underlying physical constraints. Evolution is the most general theory we have, but it serves mostly to explain how life arrived where it is today, rather than predict outcomes of our laboratory experiments.

Many biologists feel that there never will be a theoretical biology that is predictive. The late and great Stephen Jay Gould alluded to this idea when he frequently stated that life is a "contingent outcome of history." In other words, if you replayed the history of life on earth multiple times, you would get different results. If evolution itself is not predictable, can we really create a biological theory that predicts outcomes from first principles?

Small-scale biological theories, such as those describing membrane and protein interactions, can be predictive because the relevant processes are dominated by physical constraints, such as diffusion, hydrophobicity and entropy. The problem is that these types of theories do not scale, and become far less predictive as we increase the complexity of the system. Systems biology, my field, also tries to create a predictive framework, but the vast majority of models are still descriptive, not predictive. Emergent properties tend to arise that are difficult to predict from the behavior of the underlying components. And predicting emergent properties is necessary if we truly want to understand problems such as how changes in specific genes can lead to disease.

Mathematical approaches to simplification that worked for physics are simply not going to work for biology. So what will work? In my opinion, some of the most promising concepts come from ideas about networks. There are a lot of similarities between computer networks, social networks and biological networks. For example, proteins that act as "bottlenecks", or critical connectors between parts of regulatory networks in cells, tend to be essential - just as bottlenecks are critical to social and transportation networks.2 Ideas on how to analyze and predict network behavior have been informed by concepts arising from the computational and social sciences, which are themselves increasingly concerned with understanding networks. The interesting thing about these ideas is that they work at scales ranging from the molecular to the population level.

Network biology is still in the early stages of development, but is rapidly becoming one of the foundations of systems biology. It promises to unify fundamental aspects of biology in a unique and powerful way. Biology doesn't have an Einstein yet, but there's reason to hope that we might find one.

Steven Wiley is a Pacific Northwest National Laboratory Fellow and director of PNNL's Biomolecular Systems Initiative.

References

1. B. Grant, "The powers that might be," The Scientist, 21(3):42, March 2007. 2. H. Yu et al., "The importance of bottlenecks in protein networks: Correlation with gene essentiality and expression dynamics," PLoS Comput Biol, 3(4):e59, 2007.
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Comments

Avatar of: Ronald Brown

Ronald Brown

Posts: 1

October 2, 2008

It should be useful to point out the development of new mathematical methods which are described in \n`Memory evolutive systems: Hierarchy, Emergence, cognition' A.C. Ehresmann, J.-P. Vanbremeersch, Elsevier, (2007). \n\nIt uses concepts and techniques from category theory, very well explained. This theory, developed during the last century, has proved extremely important for understanding and developing mathematical structures, their interrelationships, and their applications. These developments have also been essential background for the solution of, for example, Fermat's last theorem. \n\nFurther, new ideas on `Higher dimensional algebra' (not in the above book) have potentiality for analysing heirarchical systems, and more complicated systems of interrelations and dependencies, and have already been applied in concurrency theory in computer science.\n\nOne expects it to be a long time before predictive rather than just descriptive results emerge, but instead of longing for a biologically inclined great intuitive, it could pay to look at what new ideas are currently around and see how they might be developed. \n\nRonnie Brown\nwww.bangor.ac.uk/r.brown\n\n\n\n

October 6, 2008

Life, time and theories of Einstein are awe inspiring and mind boggling. Said that,I believe that the Unification theory has become an obcession in Physics.It is too premature to talk of predictive aspects, when even the descriptive side does not have sufficient models.The very basis of evolution appears the struggle for survival and retaining life with changing external environment. We have yet to come closer to 90%predictability of Monsoon rainfall with a meagre 16 known variables.Can we then dream of predictable models with large no.of unknown causes and bizzare effects. It seems, God loves to play dice in Biology!
Avatar of: John Horsfall

John Horsfall

Posts: 3

October 6, 2008

Steven Wiley has it the wrong way round. Physics is still waiting for its moment of unification, at least until Geneva powers up again, whereas biology has had its own unified theory since 1859. It is called evolution by natural selection.

October 8, 2008

Au contraire ..by John Horsfall asserts existance of a Unified theory. I beg to differ. Theory of Natural selection is still a theory in its beta version. It has yet to rejoin the objections.(I am keeping the intelligent design part out of my submission). Till that time it is an incomplete theory - not a wrong theory. Today it is the best fit amongst few available theories. Yet, it is an explanatory theory; it has yet to attain a respectable status of enjoying a mathematical formula that has an appeciable degree of predictability. If we are addressing "Unification", then even the Mendelian Theory with its binomial function cannot be united with Theory of Natural selection today. Thus, even if we do get an Einstein, his first job will be to postulate a few credible theories. The suceesor may may unify these. So, may ne we need an Issac Newton and a Niel Bohr of Biology first. Einstein may appear later on on the scene.\n\nDr. S. M. Sapatnekar\nDirector\nClnical Research Education and\nManagementAcademy; Mumbai; India \n
Avatar of: Ken Dev

Ken Dev

Posts: 7

October 8, 2008

In a 1997 paper (Interdisciplainary Science Reviews, 1997, Vol. 22, No. 1, pp 29-36) on "The Changing face of biology," it was pointed out that that the DNA structure itself is the "Grand Unification" aspect of biology, and the life process, irrespective of its source, has a single origin in the long string of four letters, A, T, C and G. The rest of biology can be represented as many branches of the same tree with its root intact; even the eukaryotes and prokaryotes diverged billions of years ago, presumably from the same root.

October 8, 2008

Nature is cyclic and periodic. With number of protons and neutrons as unit multiples, added into the nucleus, we can change the lightest hydrogen atom into the heaviest Uranium. In biology, the DNA having been identified as a unit of life, with its components A, G, T, C groups appearing and reappearing in sequences to define a particular kind of life? what is that specific combination of groups or a unit multiple in DNA, which when added on to itself will change a life form from say litchen to grass, grass to shrub, shrub to creeper and from creeper to a tree? If we can do that, perhaps the all plant kinds or to that matter, all life forms can be put into a periodic classification analogous to the Mendeleev's Periodic Table, and consequently a unified teory of biology. I think, a serious collective multidisciplinary effort is needed to work on this idea. I strongly believe in the cyclic and periodic law of nature and its reality. And evolving such unified theory may not be impossible if the unit multiple is identified. Work of Elizabeth Kubler Ross has now scientifically proved even the cyclic /periodic nature in human life, death and rebirth.
Avatar of: Wes  Klasky

Wes Klasky

Posts: 1

October 8, 2008

My problem with this article is that Darwin is biology?s Einstein. The theory of evolution is a broad, unifying theory that describes how life got to where it is and makes predictions on where it is going. This theory covers everything from single celled organisms, organ systems, and complex animals. Also the understanding of the network systems that is proposed would seem to fall under this same theory because then first step to understand the network would be to deconstruct and figure out how each piece has built on the last to become such a system.

October 9, 2008

I will surely keep a close eye on this field of network biology; but I would personally call Darwin the "Issac Newton" of Biology than Einstein, so we still need an Einstein.
Avatar of: Richard Gordon

Richard Gordon

Posts: 3

October 14, 2008

Try:\n\nGordon, R. (1999). The Hierarchical Genome and Differentiation Waves: Novel Unification of Development, Genetics and Evolution, Singapore & London: World Scientific & Imperial College Press. http://www.wspc.com.sg/books/lifesci/2755.html, 2 vols., 1836p.\n\n-Dick Gordon, gordonr@cc.umanitoba.ca
Avatar of: null null

null null

Posts: 1

October 19, 2008

Actually, till now our biology research only deal with half of natural biology. All the conception, such system biology, network biology, came out from the half region. We know few of the other half.
Avatar of: Bruce Lepper

Bruce Lepper

Posts: 1

October 30, 2008

The varied nature of preceding posts is maybe an indication that on this particular subject Gould's hunch goes towards a certain reality. Humans would like to be able to predict and thereby control everything all the time, that's for sure. It is a part of their biology/psychology. But evolution demonstrates that future biological developments of living organisms are a result of the total environment, which is itself a shifting target. Especially when runaway cultural and technological evolution are added to the mix.\nComprehension does not have to lead to prediction.
Avatar of: Nelson Thompson

Nelson Thompson

Posts: 12

November 3, 2008

Not Convincing.
Avatar of: Steven Bissell

Steven Bissell

Posts: 1

November 3, 2008

I've been out of academic/professional biology for a few years, but last time I checked Natural Selection qualified as a unifying theory. As to it being predictive, I'm unsure (1) why it isn't a unifying theory(2) why predictive power determines a unified theory. Einstein was attempting to explain all physics in one theory, not predict the outcome of experiments. In fact he commented about experiments which confirmed his theory by saying that if they hadn't it would have been unfortunate 'because the theory is right.'
Avatar of: RONALD MATHISON

RONALD MATHISON

Posts: 4

November 3, 2008

A first step to a unified theory of biology is defining the elements that need to be unified. \n\nThis is quite clear in physics - where the unified field theory seeks to allow all of the fundamental forces between elementary particles to be written in terms of a single field. \n\nOnce the objective of unification in biology is identified then the tools will be applied or developed to support the unity hypothesis. Concepts emanating from networks may be a part of the unity or it may not.\n\n\n

November 3, 2008

All biological phenomena can be described as being or resulting from the network interactions among functionally heterogeneous elements (of a 'system') in a dynamical environment. In their interactions, the elements exchange and modify mass and energy into various forms. A spontaneous process, inextricably attendant, is modification of the network's function.\n\nPut differently, the functional quality of the network changes over the course of its life history. For example, actions occurring in the biological system are broadly directed or skewed by its environment and, in turn, the environment is modified by the network's processes. This inevitable 'evolution' of the network's functionality and environment produces a novel form of _control_ on the system's behavior and that of other co-interacting systems (as viewed on larger scales).\n\nThe individual dynamics exhibited by all persisting biological networks are simple: 1. the network's characteristics are coarsely determined by the originating members (the "founder effect"). 2. network elements optimize their co-interactions ("self-optimization"). 3. As a result (all other influences being unchanged) the network functions with relative efficiency at the cost of functional brittleness ("network maturation"). 4. However, changes in its environment (e.g., increased accessible energy, the intrusion of a rel. more effective element, etc.) can reduce the network's brittleness ("desaturation"). 5. Networks themselves interact as elements of networks (viewed at larger scales) and produce the "cluster-of-clusters organization" of biological networks. 6. As the system or network matures (with attendant decrease in accessible energy and mass resources), the functioning of the now mature and optimized network appears more machinelike or deterministic (as opposed to appearing nondeterministically controlled as ecosystem control is commonly viewed), the "ultranetwork effect". \n\nThe most accessible example of these ecological dynamics is the ecosystem. Moreover, the same set of dynamics also describes Darwinian evolution, which the model arguably subsumes.\n\nThis model and its rationale are further outlined in my article "On the evolution and dynamics of biological networks" _Revista di Biologia/Biology Forum_ 100(1) pp. 93-118 (2007).\n\nA useful and leisurely introduction to this view can be found in my book _Beginnings: creativity, belief, evolution and our interconnected universe_ Idler's Cove Press, California 2002.\n\nDennis Hollenberg\nEugene, OR
Avatar of: John Torday

John Torday

Posts: 12

November 3, 2008

I agree with Steven Wiley's premise that biology (and therefore medicine too) needs a unifying theory. But like contemporary physics, we need a Periodic Table and the Quantum Mechanics of Biology before the Einstein of biology can 'invent' him/herself. Until then we will remain entrenched in descriptive, ex post facto reasoning, to our collective detriment. We suffer from a 'forest and trees' problem in biology. We know, for example, that embryogenesis is the result of cell-cell communication, as is homeostasis and regeneration. We have suggested (Torday and Rehan, 2004,2007) that complex physiology can be deconvoluted based on cell-cell signaling between ligand and receptor. Such an approach could provide the basis for a Periodic Table of Biology (http://evolutionarymedicine.labiomed.org/), but it will require a Kuhnian paradigm shift. \n\nTorday JS, VK Rehan. Deconvoluting lung evolution using functional/comparative genomics. Am J Resp Cell Mol Biol. 2004 Jul 31(1):8-12.\n\nTorday JS. A Periodic Table for Biology. The Scientist 2004 Jun 18(12): 32-33.\n\nTorday JS, Rehan VK. The evolutionary continuum from lung development to homeostasis and repair. Am J Physiol Lung Cell Mol Physiol. 2007 Mar;292(3):L608-11.\n\n\n
Avatar of: Richard Bentley

Richard Bentley

Posts: 6

November 3, 2008

While biology is trying to evolve into a reductionist theory, physics is moving away from such an approach. It may turn out that physical theories can only apply within areas of scale or energy, instead of one "theory of everything". One other comment: while Einstein made several seminal contributions to physics early in the 20th century, he was never able to accept quantum mechanics because of its deterministic nature. In the end he pursued vainly his attempt to unify all of physics, which perhaps may be ultimately a futile pursuit.
Avatar of: Ankur Dnyanmote

Ankur Dnyanmote

Posts: 1

November 3, 2008

We are not waiting for anyone or anything. The question is not unification of all biology, or of all physics for that matter. The question is the unification of THE phenomenon. \n Biology is complex chemistry and biochemistry is complex physics. Natural selection and evolution are properties of matter that have manifested as life and living systems. At the root of life is the DNA, but the DNA extends into molecular realms of C, H, N, O atoms that extend into quantum nature of reality. From a classical perspective too, life is unique to the 3rd rock from the sun. \n Why? What role does gravity, electromagnetism, space and time, play in the evolution of the living systems from the non-living matter of quarks and bosons? The theory of unification requires an insanely broad mind - not necessarily in terms of detailed comprehension, but rather endowed with infinite innocence and curiosity. Our present socio-political networks impart on us a rigidly tacit frame of reference that dangerously prohibits the leaps of imagination that can potentially shift the current paradigms. We all remain comfortably imprisoned in the collusion that 'things' are separate. Ironically we aspire unification of these separate things.\n Unification is truly impossible, because in the time-line of universes, systems change so dramatically, that any model of unification will only be an ephemeral moment of realization in the insignificant flux of scientific theories. We must come to terms with this egotistic hubris. \n Unification is an attempt to hold on to something that cannot be grasped, to create something that cannot be preserved, and to explain something that cannot be understood - because 'it' changes, constantly. \n Now equations - these we can certainly formulate, although mathematics is the language of nature that we communicate our understanding of nature in. Nevertheless, meaning does not involve making permanent that which is inherently impermanent. It is for THESE reasons that philosophy is the critical foundation of scientific thought. The only thing we can do is tap into the harmony of nature. The rhythm of our actions will branch out of the melodies that we compose.
Avatar of: anonymous poster

anonymous poster

Posts: 1

November 3, 2008

In neuropsychology it's well known that one cannot be aware of what they are not aware of. Our peer review system is waiting for the next Einstein to come through the front door...while he/she may have already come through the back door.\n\nMathematics simply models the first principles of biophysics. Theory is not truth, just models. Neural networks have made connections between the real world of experiment and the model world of simulation. Let the real world correct the models through the use of neural nets and see where the simulations run.
Avatar of: anonymous poster

anonymous poster

Posts: 3

November 3, 2008

Might the fundamental problem of systems biology be a methodological problem? \n\nBiologists have made great progress in measuring the constituent parts of biological systems. Now we might need to measure the interactions over time that describe and help predict how biological systems work - function internally, respond to their environments including treatments and act as agents on their environments. In other words, we might need to measure the edges when two or more nodes can be measured repeatedly. Still again, we might need to measure how actions in two or more nodes might be coordinated where coordination of action is an emergent systems property. Measures of interaction over time or coordination of action that are computed from two or more individuals can be analyzed statistically.\n\nMeasurement helps make scientific investigations and mathematical modeling possible. Fortunately, a computational algorithm for measuring interactions over time or coordination of action is now available. This algorithm applies to time series data for two or more variables for one individual. This algorithm is available from Curtis A. Bagne, who is the author of this comment.
Avatar of: x hj

x hj

Posts: 1

November 3, 2008

I think it is impossible to predict accurately the process of life. Advanced life like plant, animal and human are composed of numerous different molecule and the inaction among them is also affected by the environment. Thefefore, how can we predict the future of a life in biology regard.
Avatar of: anonymous poster

anonymous poster

Posts: 3

November 3, 2008

To comment on the statement of an anonymous post below, "Our peer review system is waiting for the next Einstein to come through the front door..."\nI think it more accurate to state that "The peer review system is preventing the next Einstein from coming through the front or back door..."\nSome have likened our much revered peer review system to the immune system. It's first response to a new idea or paradigm is to reject it.
Avatar of: null null

null null

Posts: 97

November 4, 2008

Rethink Unified Field Theory And Evolution\n\n\nPlease glance at the following four brief essays and then re-read this note.\n\nI humbly suggest that the underlying, essential thought, of these essays deserves your attention:\n\n- Earth's life is an up-phased matter of the inanimate matter, all matter being essentially a format of constrained energy.\n\n- The cosmos is an evolving energy affair consisting of endless intertwined evolutions.\n\n- Culture is a ubiquitous trait of all matter, the driver of Evolution, of all evolutions. This is an extension of Darwin's and Broken Symmetry concepts. \n\n- The further comprehension of Culture and Evolution is the essence of the quest for a Unified Field Theory.\n\nRespectfully yours,\n\nDov Henis \n(A DH Comment From The 22nd Century)\n http://blog.360.yahoo.com/blog-P81pQcU1dLBbHgtjQjxG_Q--?cq=1\n\n==========================\n\n(1) On Complexity \nhttp://www.the-scientist.com/community/posts/list/60/122.page#943\n\n(2) Broken Symmetry" Is Physics' Term Of Biology's "Evolution\nhttp://www.the-scientist.com/community/posts/list/40/122.page#885\n\n(3) More On Forces-Matter-Life Unified Theory \nhttp://www.the-scientist.com/community/posts/list/60/122.page#957 \n\n(4) Why 'Life' In Forces-Matter-Life Unified Theory \nhttp://www.the-scientist.com/community/posts/list/60/122.page#963
Avatar of: Alec Schaerer

Alec Schaerer

Posts: 4

November 4, 2008

If the idea were totally true of a theory of life needing to be predictive for being serious, this would mean that developing theories would fully be steered by the observed structures (a neural network, the brain, etc.). In other words, one would not be able to actually know what really is guiding the process. One would only be driven from one level of described "elements" to the next (more minute) level ? which is precisely what this type of science is actually being forced to do ? while in fact there is no totally stable fundamental element (even protons finally are not). On this path the resulting theories would on principle not be able to warrant a complete coverage of what they are aspiring to.\n\nThis does of course not exclude the belief of possessing a method or system that warrants what one is fantasizing; such beliefs can be upheld as long as the type of consulted evidence does not contradict the belief. For example, as long as one addresses only the mechanically and repetitively induced aspects of life, the characteristics of carriers of life (bodies in the widest sense, and their functions), one can remain in the belief of being in control, even though one overrsees only some aspects of life.\n\nConcerning mathematics it is useful to remember that mathematics can never offer more than a description, because it is only a language, albeit a precise and completely formalized one. Especially in its algebraic branch, mathematics can never get rid of its language status because it is formal: the symbols stand for something else. The overall order ? whereby things are exactly as they are ? cannot be found by any formal means, for the same reason as logic cannot be proved per se, but only as specific types of logic. Syntactic information 'hidden' in a language should not be expected to yield complete truth merely because it leads from one logical step to another (a widespread fallacy ? especially in physics and economics). For instance the meaning of terms in an equation, or of axioms of a geometry, stems from conceptual attributions in the respective case, not only from the syntactic interrelations between terms. There have been many attempts at generally reducing semantics to syntactics, i.e. at an all-out formalization; think for instance of Hilbert's program. They must ultimately fail, because syntactic information ('rules') is not strictly all of what constitutes a system. Remaining in intransparent foundations must finally suggest arbitrary moves ? 'auxiliary' hypotheses, postulates, etc., ? for overriding handicaps at its edge cases.\n\nThe additional idea of empirically confirming hyptheses can only cover events of the past, not actuality and even less anything authentically future-oriented, because one can observe only something that already exists, not somethig in its actual becoming or in its being envisaged. The activity of distinguishing, observing, describing, or measuring has on principle the problem of the 'blind spot': it cannot cover itself too. The type of predictivness that is available on this path is on principle self-limited. Of coures one can find some events that can be predicted, namely the recurring ones and those which are mechanicall induced. But that does not cover all of life ? and especially not the gist of life, which is in its aspect of autonomous guidance of its own organism. The most alive form is a self-aware mind in its mental activity. Any theory that it not uncompromisingy up to that cannot claim to be capable of explaining coherently the totality of life.\n\nThe real question is in mechanicity versus organicity (regulation by external influence versus self-regulation by self-referentiality), and, for methodologically tackling the crucial points, conceptually fully coming to terms with categoriality (the very first decisions that determine a systematic theoretical structure). This is possible only by means of uncompromising intra- and inter-subjective transparence. The Einstein of biology probably already has been around for a long time, but since especially today's mainsteam thinking is so entrenched in its prejudices ? thereby refusing to address the ultimately relevant methodological issues ? it would not even be capable of recognizing him or her. One can observe this relatively clearly for instance in the way the Nobel prizes are being issued.\n\n\nAlec A. Schaerer\n-- \nScientific collaborator\nDepartments of Geoscience and Philosophy\nUniversity if Basel / Switzerland\ne-mail alec.schaerer@unibas.ch

November 4, 2008

A unified biological theory is the same as a unified field theory, no need for application of extraneous biological terms (e.g. "metabolic"). It's all the same, life, but a rush to conclude, elucidate...prove this, would spoil all the fun! It's rather interesting to explore all the other possibilities that might snag the essence of what "unifies" all things, describes operability and offers predictability, though deep in our intuition we confess we are exploring only our imaginative ideas...well, and this just gets to get the point of it...the idea, the exploration within the mind is an expression of the essence of what we seek to understand...that fundamental gist of what unifies. It's fun, but in the end, not that complicated...this and that...all the same isn't it ;-)
Avatar of: anonymous poster

anonymous poster

Posts: 3

November 4, 2008

How about trying to do all that we can do now to advance systems biology scientifically. Fundamentally new measures of "interaction over time" and "coordination of action" might provide new opportunities for empirical science of dynamic networks to advance from where we are now. Please see "Methodological Problem?" below.
Avatar of: anonymous poster

anonymous poster

Posts: 125

November 4, 2008

We need to first validate the accuracies of the existing data - which in itself is an extremely time-consuming and daunting task. Wet science is quite messy and even the experimental data published in the top journals are prone to frequent errors and uncertainties, as well as subject to the prevailing biases influenced by the currently popular hypotheses or dogmas that are, in turn, based on the incomplete or inaccurate past experimental observations. So, basically the validities of inaccurate experimental data are constantly judged by the inaccurate hypotheses in biological sciences. Thus, it should come as no surprise that this wheel-spinning-at-the-same-spot process has resulted in few, if any, major breakthroughs in describing physiological, much less pathological, processes at the molecular or organic level, such as for cancer or for neurodegenerative disease. Then, too, there are too much experimental data for certain entities or processes but too few or, even, none at all, in others. Some of the critical experimental data are simply unavailable due to technical difficulties, ignorance, or neglect. So, to try to search for a "unified theory" in biology by any or all quantitative approaches based on the incomplete and inaccurate experimental data will only result in an incomplete and inaccurate, unified theory, at best. That, to me, seems like an oxymoronic theory formed from putting a cart before the horse. One has to be reasonably, if not absolutely, certain that the observation from an experiment represents a repeatable phenomenon that can even be modeled quantitatively to describe it reliably, let alone accurately predict a new behavior when one or more of the parameters such as temperature, time, chemical concentrations, etc. are varied. With so many experimental data with so many variations due to different experimental models, techniques, skills, and conditions, even for the same or similar purpose, I doubt very much that a unified theory for even one specific aspect of one specific cell is possible within a foreseeable future. Sorry, Steven Wiley, but I'm afraid that your hopeful version of a general unified theory in biology comparable to that of Einstein's in physics is still light years from becoming a reality.
Avatar of: anonymous poster

anonymous poster

Posts: 2

November 4, 2008

Im wondering how things are going on, but i beleave there is a answer. Best wishes for the 21th.
Avatar of: Ruth Rosin

Ruth Rosin

Posts: 117

November 6, 2008

I quote the author: "Systems biology, my field, also tries to create a predictive framework, but the vast majority of models are still descriptive, not predictive. Emergent properties tend to arise that are difficult to predict from the behavior of the underlying components."\n\nHis field appears to be based on an erroneous initial assumption. Any aggregate of components (whether animate, or not), has properties that are the sum of the properties of the components, as well as properties that depend on the type of organization in which the components are organized into one whole. Properties of the second kind are not just difficult, but simply impossible to predict from the behavior of the underlying components.
Avatar of: anonymous poster

anonymous poster

Posts: 125

November 6, 2008

Top mathematicians and physicists were employed to write their fancy mathmatical models of stock derivatives which are still much simpler than those for biological processes, to predict the stock market behavior, but we all know what happened, don't we? Please put down your crack pipe!

November 6, 2008

Maybe it's Barabasi.
Avatar of: anonymous poster

anonymous poster

Posts: 7

November 7, 2008

If anyone can do it, it will probably come from the younger generation -- they seem to be able to live life and chronicle it simultaneously (e.g., Facebook, blogs, etc.). Dinosaurs like me tend to accumulate mounds of paperwork around their desks (all the e-mails we print out).\n\nLike Einstein, maybe they'll end up saying, "God does not play dice with the universe." \n\nWhat a fascinating universe we have to investigate!\n
Avatar of: Ruth Rosin

Ruth Rosin

Posts: 117

November 8, 2008

I quote the author: "Systems biology, my field, also tries to create a predictive framework, but the vast majority of models are still descriptive, not predictive. Emergent properties tend to arise that are difficult to predict from the behavior of the underlying components." \n\nHis field appears to be based on an erroneous initial assumption. Any aggregate of components (whether animate, or not), has properties that are the sum of the properties of the components, as well as properties that depend on the type of organization in which the components are organized into one whole. Properties of the second kind are not just difficult, but simply impossible to predict from the behavior of the underlying components.

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