SIAM Meeting 10 04 2002 Cell Talk ¦ Bud Mishra Professor of CS & Mathematics (Courant, NYU) Professor (Cold Spring Harbor Laboratory) 10/4/2002 ©Bud Mishra, 2002 Cell Talk»1 10/4/2002 ©Bud Mishra, 2002 Cell Talk»2 Robert Hooke • Robert Hooke (1635-1703) was an experimental scientist, mathematician, architect, and astronomer. Secretary of the Royal Society from 1677 to 1682, he is remembered for the discovery of the proportional relationship of the extension of a spring and the force applied to produce that extension. • His work Micrographia of 1665 contained his microscopical investigations, which included the first identification of biological cells. • Hooke became involved in a dispute with Isaac Newton over the priority of the discovery of the inverse square law of gravitation. Although he communicated some form of inverse square law to Newton, modern opinion is that credit for the law of universal gravitation must go to Newton. • Aubrey held his ability in high regard: "He is certainly the greatest Mechanick this day in the World." 10/4/2002 ©Bud Mishra, 2002 Cell Talk»3 Newton & Hooke • “[Huygen’s Preface] is concerning those properties of gravity which I myself first discovered and showed to this Society and years since, which of late Mr. Newton has done me the favour to print and publish as his own inventions. • “And particularly that of the oval figure of the Earth which was read by me to this Society about 27 years since upon the occasion of the carrying the pendulum clocks to sea and at two other times since, though I have had the ill fortune not to be heard, and I conceive there are some present that may very well remember and do know that Mr. Newton did not send up that addition to his book till some weeks after I had read and showed the experiments and demonstration thereof in this place and had answered the reproachful letter of Dr. Wallis from Oxford.“ 10/4/2002 ©Bud Mishra, 2002 Cell Talk»4 Newton & Hooke • “If I have seen further than other men, it is because I have stood on the shoulders of giants and you my dear Hooke, have not." -Newton to Hooke 10/4/2002 ©Bud Mishra, 2002 Cell Talk»5 Image & Logic • The great distance between – a glimpsed truth and – a demonstrated truth • Christopher Wren/Alexis Claude Clairaut 10/4/2002 ©Bud Mishra, 2002 Cell Talk»6 Micrographia Principia 10/4/2002 ©Bud Mishra, 2002 Cell Talk»7 Micrographia 10/4/2002 ©Bud Mishra, 2002 Cell Talk»8 “The Brain & the Fancy” • “The truth is, the science of Nature has already been too long made only a work of the brain and the fancy. It is now high time that it should return to the plainness and soundness of observations on material and obvious things.” – Robert Hooke. (1635 - 1703), Micrographia 1665 10/4/2002 ©Bud Mishra, 2002 Cell Talk»9 Principia 10/4/2002 ©Bud Mishra, 2002 Cell Talk»10 “Induction & Hypothesis” • Rule IV. In experimental philosophy we are to look upon propositions collected by general induction from phenomena as accurately or very nearly true, notwithstanding any contrary hypotheses that may be imagined, 'till such time as other phenomena occur, by which they may either be made more accurate, or liable to exceptions… Hypotheses non fingo. I feign no hypotheses. Principia Mathematica. 10/4/2002 • This rule we must follow, that the argument of induction may not be evaded by hypotheses. ©Bud Mishra, 2002 Cell Talk»11 Morphogenesis 10/4/2002 ©Bud Mishra, 2002 Cell Talk»12 Alan Turing: 1952 • “The Chemical Basis of Morphogenesis,” 1952, Phil. Trans. Roy. Soc. of London, Series B: Biological Sciences, 237:37—72. • A reaction-diffusion model for development. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»13 “A mathematical model for the growing embryo.” 10/4/2002 • A very general program for modeling embryogenesis: The `model’ is “a simplification and an idealization and consequently a falsification.” • Morphogen: “is simply the kind of substance concerned in this theory…” in fact, anything that diffuses into the tissue and “somehow persuades it to develop along different lines from those which would have been followed in its absence” qualifies. ©Bud Mishra, 2002 Cell Talk»14 Diffusion equation first temporal derivative: rate a/ t = Da r2 a second spatial derivative: flux a: concentration Da: diffusion constant 10/4/2002 ©Bud Mishra, 2002 Cell Talk»15 Reaction-Diffusion a/ t = f(a,b) + Da r2 a f(a,b) = a(b-1) –k1 b/ t = g(a,b) + Db r2 b g(a,b) = -ab +k2 a Turing, A.M. (1952).“The chemical basis of morphogenesis.“ Phil. Trans. Roy. Soc. London B 237: 37 10/4/2002 ©Bud Mishra, 2002 b reaction diffusion Cell Talk»16 Reaction-diffusion: an example A fed at rate F d[A]/dt=F(1-[A]) A+2B ! 3B B!P B extracted at rate F, decay at rate k d[B]/dt=-(F+k)[B] reaction: -d[A]/dt = d[B]/dt = [A][B]2 diffusion: d[A]/dt=DA2[A]; d[B]/dt=DB2[B] [A]/ t = F(1-[A]) – [A][B]2 + DA2[A] [B]/ t = -(F+k)[B] +[A][B]2 + DB2[B] Pearson, J. E.: Complex patterns in simple systems. Science 261, 189-192 (1993). 10/4/2002 ©Bud Mishra, 2002 Cell Talk»17 Reaction-diffusion: an example 10/4/2002 ©Bud Mishra, 2002 Cell Talk»18 Genes: 1952 • Since the role of genes is presumably catalytic, influencing only the rate of reactions, unless one is interested in comparison of organisms, they “may be eliminated from the discussion…” 10/4/2002 ©Bud Mishra, 2002 Cell Talk»19 Crick & Watson :1953 10/4/2002 ©Bud Mishra, 2002 Cell Talk»20 Genome • Genome: – Hereditary information of an organism is encoded in its DNA and enclosed in a cell (unless it is a virus). All the information contained in the DNA of a single organism is its genome. • DNA molecule can be thought of as a very long sequence of nucleotides or bases: S = {A, T, C, G} 10/4/2002 ©Bud Mishra, 2002 Cell Talk»21 Genome in Detail The Human Genome at Four Levels of Detail. Apart from reproductive cells (gametes) and mature red blood cells, every cell in the human body contains 23 pairs of chromosomes, each a packet of compressed and entwined DNA (1, 2). 10/4/2002 ©Bud Mishra, 2002 Cell Talk»22 DNA Structure. The four nitrogenous bases of DNA are arranged along the sugarphosphate backbone in a particular order (the DNA sequence), encoding all genetic instructions for an organism. Adenine (A) pairs with thymine (T), while cytosine (C) pairs with guanine (G). The two DNA strands are held together by weak bonds between the bases. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»23 The Central Dogma • The intermediate molecule carrying the information out of the nucleus of an eukaryotic cell is RNA, a single stranded polymer. • RNA also controls the translation process in which amino acids are created making up the proteins. • The central dogma(due to Francis Crick in 1958) states that these information flows are all unidirectional: “The central dogma states that once `information' has passed into protein it cannot get out again. The transfer of information from nucleic acid to nucleic acid, or from nucleic acid to protein, may be possible, but transfer from protein to protein, or from protein to nucleic acid is impossible. Information means here the precise determination of sequence, either of bases in the nucleic acid or of amino acid residues in the protein.” 10/4/2002 ©Bud Mishra, 2002 Cell Talk»24 RNA, Genes and Promoters • A specific region of DNA that determines the synthesis of proteins (through the transcription and translation) is called a gene – Originally, a gene meant something more abstract---a unit of hereditary inheritance. – Now a gene has been given a physical molecular existence. • Transcription of a gene to a messenger RNA, mRNA, is keyed by a transcriptional activator/factor, which attaches to a promoter (a specific sequence adjacent to the gene). • Regulatory sequences such as silencers and enhancers control the rate of transcription 10/4/2002 ©Bud Mishra, 2002 Cell Talk»25 Gene Expression •When genes are expressed, the genetic information (base sequence) on DNA is first transcribed (copied) to a molecule of messenger RNA, mRNA. •The mRNAs leave the cell nucleus and enter the cytoplasm, where triplets of bases (codons) forming the genetic code specify the particular amino acids that make up an individual protein. •This process, called translation, is accomplished by ribosomes (cellular components composed of proteins and another class of RNA) that read the genetic code from the mRNA, and transfer RNAs (tRNAs) that transport amino acids to the ribosomes for attachment to the growing protein. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»26 Regulation of Gene Expns • Motifs (short DNA sequences) that regulate transcription – Promoter – Terminator • Motifs that modulate transcription – Repressor – Activator – Antiterminator Promoter Terminator 10-35bp 10/4/2002 Transcriptional Initiation ©Bud Mishra, 2002 Gene Transcriptional Termination Cell Talk»27 “The Brain & the Fancy” “Work on the mathematics of growth as opposed to the statistical description and comparison of growth, seems to me to have developed along two equally unprofitable lines… It is futile to conjure up in the imagination a system of differential equations for the purpose of accounting for facts which are not only very complex, but largely unknown,…What we require at the present time is more measurement and less theory.” – Eric Ponder, Director, CSHL (LIBA), 1936-1941. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»28 “Axioms of Platitudes” -E.B. Wilson 1. Science need not be mathematical. 2. Simply because a subject is mathematical it need not therefore be scientific. 3. Empirical curve fitting may be without other than classificatory significance. 4. Growth of an individual should not be confused with the growth of an aggregate (or average) of individuals. 5. Different aspects of the individual, or of the average, may have different types of growth curves. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»29 Genes for Segmentation • Fertilisation followed by cell division • Pattern formation – instructions for – Body plan (Axes: A-P, D-V) – Germ layers (ecto-, meso-, endoderm) • Cell movement - form – gastrulation • Cell differentiation 10/4/2002 ©Bud Mishra, 2002 Cell Talk»30 PI: Positional Information • Positional value – Morphogen – a substance – Threshold concentration • Program for development – Generative rather than descriptive • “French-Flag Model” 10/4/2002 ©Bud Mishra, 2002 Cell Talk»31 bicoid • The bicoid gene provides an A-P morphogen gradient 10/4/2002 ©Bud Mishra, 2002 Cell Talk»32 gap genes • The A-P axis is divided into broad regions by gap gene expression • The first zygotic genes • Respond to maternally-derived instructions • Short-lived proteins, gives bell-shaped distribution from source 10/4/2002 ©Bud Mishra, 2002 Cell Talk»33 Transcription Factors in Cascade • Hunchback (hb) , a gap gene, responds to the dose of bicoid protein • A concentration above threshold of bicoid activates the expression of hb • The more bicoid transcripts, the further back hb expression goes 10/4/2002 ©Bud Mishra, 2002 Cell Talk»34 Transcription Factors in Cascade 10/4/2002 • Krüppel (Kr), a gap gene, responds to the dose of hb protein • A concentration above minimum threshold of hb activates the expression of Kr • A concentration above maximum threshold of hb inactivates the expression of Kr ©Bud Mishra, 2002 Cell Talk»35 Segmentation • Parasegments are delimited by expression of pairrule genes in a periodic pattern • Each is expressed in a series of 7 transverse stripes 10/4/2002 ©Bud Mishra, 2002 Cell Talk»36 Pattern Formation – Edward Lewis, of the California Institute of Technology – Christiane Nuesslein-Volhard, of Germany's Max-Planck Institute – Eric Wieschaus, at Princeton • Each of the three were involved in the early research to find the genes controlling development of the Drosophila fruit fly. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»37 The Network of Interaction EN en wg WG ptc + cid CID CN hh a cell mRNA proteins 10/4/2002 en positive interacions WG PTC PTC PH PH HH HH Cell-to-cell interface Legend: •WG=wingless •HH=hedgehog •CID=cubitus iterruptus •CN=repressor fragment of CID •PTC=patched •PH=patched-hedgehog complex a neighbor negative interacions ©Bud Mishra, 2002 Cell Talk»38 Completeness: von Dassow, Meir, Munro & Odell, 2000 • “We used computer simulations to investigate whether the known interactions among segment polarity genes suffice to confer the properties expected of a developmental module…. • “Using only the solid lines in [earlier figure] we found no such parameter sets despite extensive efforts.. Thus the solid connections cannot suffice to explain even the most basic behavior of the segment polarity network… • “There must be active repression of en cells anterior to wgexpressing stripe and something that spatially biases the response of wg to Hh. There is a good evidence in Drosophila for wg autoactivation…” 10/4/2002 ©Bud Mishra, 2002 Cell Talk»39 Completeness • “We incorporated these two remedies first (light gray lines). With these links installed there are many parameter sets that enable the model to reproduce the target behavior, so many that they can be found easily by random sampling.” 10/4/2002 ©Bud Mishra, 2002 Cell Talk»40 Model hh t HH t PH t EN Tmax hh EN 1 hh t KEN 0, kPTCHH HH t PTC t , HH 0 0, HHH PH t kPTCHH HH t PTC t , PH 0 0, PTC t 0, PTC 0 HPH 6 Pmax hh hh t , hh 0 Hhh HH t 1 1 0.8 0.6 0.4 0.2 5 10/4/2002 ©Bud Mishra, 2002 10 15 20 Cell Talk»41 25 30 Model Parameters 10/4/2002 ©Bud Mishra, 2002 Cell Talk»42 Model hh EN_ : Tmax Tmax hh Hhh EN^ 1.0, hh KEN^ 1.0, KEN EN^ 1.0, . 4.0, Hhh 1.0 ; ? hh Plot hh EN , hh EN_ : Tmax hh Hhh EN KEN EN EN, 0, 2.5 . Tmax 1., hh 1., KEN 1., 4., Hhh 1. 0.8 0.6 0.4 0.2 0.5 10/4/2002 1 1.5 ©Bud Mishra, 2002 2 2.5 Cell Talk»43 Complete Model 10/4/2002 ©Bud Mishra, 2002 Cell Talk»44 Complete Model 10/4/2002 ©Bud Mishra, 2002 Cell Talk»45 S-system 10/4/2002 ©Bud Mishra, 2002 Cell Talk»46 Graphical Representation X2 Reversible Reaction X1 X2 X1 X2 X1 X3 Divergence Branch Point: Degradation processes of X1 into X2 and X3 are independent X3 X1 X3 X1 X3 X2 10/4/2002 Convergence Branch Point: Degradation processes of X1 into X2 and X3 are independent X2 ©Bud Mishra, 2002 Single splitting reaction generating two products X2 and X3, in stoichiometric proportion. Single synthetic reaction involving two source components X1 and X2, in stoichiometric proportion. Cell Talk»47 Graphical Representation X3 X4 X2 X1 The reaction between X1 and X2 requires coenzyme X3 which is converted to X4 X3 X2 X1 The conversion of X1 into X2 is modulated by X3 X3 X1 - 10/4/2002 X2 The conversion of X1 into X2 is modulated by an inhibitor X3 ©Bud Mishra, 2002 Cell Talk»48 Systems of Differential Equations • dXi/dt = (instantaneous) rate of change in Xi at time t = Function of substrate concentrations, enzymes, factors and products: • dXi/dt = f(S1, S2, …, E1, E2, …, F1, F2,…, P1, P2,…) E.g. Michaelis-Menten for substrate S & product P: 1. dS/dt = - Vmax S/(KM + S) 2. dP/dt = Vmax S/(KM + S) 10/4/2002 ©Bud Mishra, 2002 Cell Talk»49 General Form • dXi/dt = Vi+(X1, X2, …, Xn) – Vi-(X1, X2, …, Xn): – Where Vi+(¢) term represents production (or accumulation) rate of a particular metabolite and Vi-(¢) represent s depletion rate of the same metabolite. • Generalizing to n dependent variables and m independent variables, we have: dXi/dt = Vi+(X1, X2, …, Xn, U1, U2, …, Um) – Vi-(X1, X2, …, Xn, U1, U2, …, Um): 10/4/2002 ©Bud Mishra, 2002 Cell Talk»50 Canonical Forms • S-systems result in Non-linear Time-Invariant DAE System. • Note that: Given a system of equations with f and g being arbitrary rational functions, we can transform the system into a set of Differential Binomial Equation System with Linear Constraints: dxi/dt = a x1a1L xnan - b x1b1L xnbn & g1 x1 + L gn xn = 0 10/4/2002 ©Bud Mishra, 2002 Cell Talk»51 Transformation I • Assume that an equation is given as • dx/dt = p(x(t), u(t))/q(x(t), u(t)) – A rational function. p & q are polynomials – p(x(t), u(t)) = a1 m1 + L + ak mk - b1 p1 - L - bl pl – where m’s and p’s are power-products with arbitrary power. a’s and b’s are positive-valued. dx/dt = p(x(t), u(t)) y(t)-1, dc/dt = q(x(t), u(t)) – y(t), c = 0. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»52 Transformation II • dx/dt = a1 m1 + L + ak mk - b1 p1 - L - bl pl = (a1 m1 – w(t)/k) + L + (ak mk – w(t)/k) – (b1 p1 - w(t)/l) - L - (bl pl - w(t)/l) • Equivalent System x(t) - g1(t) - L - gk(t) + gk+1(t) + L + gk+l(t) = 0 dgi/dt = ai mi – w(t)/k , 1 · i · k dgj/dt = b1 p1 - w(t)/l , k+1 · j · k+l 10/4/2002 ©Bud Mishra, 2002 Cell Talk»53 Canonical Forms 10/4/2002 ©Bud Mishra, 2002 Cell Talk»54 Cascade Model: Repressilator? x1 - dx2/dt = a2 X6g26X1g21 - b2 X2h22 dx4/dt = a4 X2g42X3g43 - b4 X4h44 dx6/dt = a6 X4g64X5g65 - b6 X6h66 X1, X3, X5 = const x2 x3 - x4 x5 10/4/2002 - x6 ©Bud Mishra, 2002 Cell Talk»55 How Stable is This??? 10/4/2002 ©Bud Mishra, 2002 Cell Talk»56 Synergy of Tools • Exploit the special structure of Pathways Models and of ‘traces' to create a synergy among different conceptual components •ODEs (XS-systems canonical form) •Temporal Logic •Time Series Analysis •Symbolic Mathematics 10/4/2002 ©Bud Mishra, 2002 Cell Talk»57 S-System Automaton AS • S-System Automata Definition: – Combine snapshots of the IDs (“instantaneous descriptions”) of the system to create a possible world model – Transitions are inferred from “traces” of the system variables: • Definition:Given an S-systems S, the S-system automaton AS associated to S is 4-tuple AS = (S, D, S0, F), where S µ D1 £ L £ DW is a set of states, D µ S £ S is the binary transition relation, and S0, F ½ S are initial and final states respectively. • Definition: A trace of an S-system automaton AS is a sequence s0, s1, …, sn,…, such that s0 2 S0, D(si, si+1), 8 i = 0. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»58 Trace Automaton Simple one-to-one construction of the “trace” automata AS for an S-system S 10/4/2002 ©Bud Mishra, 2002 Cell Talk»59 State Collapse • Definition: The relation Rd holds between two states sk = X(t + k q) and sk+j = X(t + (k+j) q), iff 8 i 2 {1, …, n+m}, | dX/dt(t + k q) - dX/dt(t + (k+j) q) | · d. 10/4/2002 ©Bud Mishra, 2002 Cell Talk»60 Collapsing Algorithm 10/4/2002 ©Bud Mishra, 2002 Cell Talk»61 Collapsed Automata The effects of the collapsing construction of the “trace” automata AS for an S-system S 10/4/2002 ©Bud Mishra, 2002 Cell Talk»62 SimPathica System 10/4/2002 ©Bud Mishra, 2002 Cell Talk»63 Modal Logic Queries 10/4/2002 ©Bud Mishra, 2002 Cell Talk»64 SimPathica: Trace Analysis System 10/4/2002 ©Bud Mishra, 2002 Cell Talk»65 SimPathica 10/4/2002 ©Bud Mishra, 2002 Cell Talk»66 Computational Differential Algebra 10/4/2002 ©Bud Mishra, 2002 Cell Talk»67 Algebraic Approaches 10/4/2002 ©Bud Mishra, 2002 Cell Talk»68 State Space Description 10/4/2002 ©Bud Mishra, 2002 Cell Talk»69 Input-Output Relation 10/4/2002 ©Bud Mishra, 2002 Cell Talk»70 Differential Algebra 10/4/2002 ©Bud Mishra, 2002 Cell Talk»71 Related Problems 10/4/2002 ©Bud Mishra, 2002 Cell Talk»72 Example System 10/4/2002 ©Bud Mishra, 2002 Cell Talk»73 Input-Output Relations 10/4/2002 ©Bud Mishra, 2002 Cell Talk»74 Membership Problem 10/4/2002 ©Bud Mishra, 2002 Cell Talk»75 Obstacles 10/4/2002 ©Bud Mishra, 2002 Cell Talk»76 Some Remarks • Many problems of Kinetic modeling lead naturally to formulation in Differential Algebra! • Yet, most problems in Differential Algebra remain to be solved satisfactorily!! – Many of the tools developed in the algebraic setting (e.g., Gröbner bases, elimination theory, etc.) do not generalize. – Complexity and solvability questions pose intriguing and challenging problems for applied mathematicians and computer scientists!! 10/4/2002 ©Bud Mishra, 2002 Cell Talk»77 Isaac Newton “I know not what I appear to the world, but to myself I seem to have been only like a boy playing on the sea-shore, and diverting myself in now and then finding a smoother pebble or a prettier shell, whilest the great ocean of truth lay all undiscovered before me.” Quoted in D Brewster, Memoirs of Newton 10/4/2002 ©Bud Mishra, 2002 Cell Talk»78 The End http://www.cs.nyu.edu/mishra http://bioinformatics.cat.nyu.edu Valis, Gene Grammar, NYU MAD, Cell Simulation,… 10/4/2002 ©Bud Mishra, 2002 Cell Talk»79