arXiv subjects

Michael Lassig

Publications and source records attributed to Michael Lassig.

18 recordsLinked to original sources

arXiv2015

Pervasive adaptation of gene expression in Drosophila

Gene expression levels are important molecular quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies in recent years have revealed substantial adaptive evolution at the genomic level. However, the evolutionary modes of gene expression have remained controversial. Here we present evidence that adaptation dominates the evolution of gene expression levels in flies. We show that 63% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from the variation of expression within species and the time-resolved divergence across a family of related species, using a new inference method for selection. We identify functional classes of adaptively regulated genes, as well as sex-specific adaptation occurring predominantly in males. Our analysis opens a new avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

q-bio.PE↗

arXiv2005

Universality of Long-Range Correlations in Expansion-Randomization Systems

We study the stochastic dynamics of sequences evolving by single site mutations, segmental duplications, deletions, and random insertions. These processes are relevant for the evolution of genomic DNA. They define a universality class of non-equilibrium 1D expansion-randomization systems with generic stationary long-range correlations in a regime of growing sequence length. We obtain explicitly the two-point correlation function of the sequence composition and the distribution function of the composition bias in sequences of finite length. The characteristic exponent $χ$ of these quantities is determined by the ratio of two effective rates, which are explicitly calculated for several specific sequence evolution dynamics of the universality class. Depending on the value of $χ$, we find two different scaling regimes, which are distinguished by the detectability of the initial composition bias. All analytic results are accurately verified by numerical simulations. We also discuss the non-stationary build-up and decay of correlations, as well as more complex evolutionary scenarios, where the rates of the processes vary in time. Our findings provide a possible example for the emergence of universality in molecular biology.

q-bio.GN↗

arXiv2002

Quantum Game Theory

A systematic theory is introduced that describes stochastic effects in game theory. In a biological context, such effects are relevant for the evolution of finite populations with frequency-dependent selection. They are characterized by quantum Nash equilibria, a generalization of the well-known Nash equilibrium points in classical game theory. The implications of this theory for biological systems are discussed in detail.

cond-mat.stat-mech↗

arXiv2001

The shape of ecological networks

We study the statistics of ecosystems with a variable number of co-evolving species. The species interact in two ways: by prey-predator relationships and by direct competition with similar kinds. The interaction coefficients change slowly through successful adaptations and speciations. We treat them as quenched random variables. These interactions determine long-term topological features of the species network, which are found to agree with those of biological systems.

nlin.AO↗

arXiv1999

Delocalization transitions of semi-flexible manifolds

Semi-flexible manifolds such as fluid membranes or semi-flexible polymers undergo delocalization transitions if they are subject to attractive interactions. We study manifolds with short-ranged interactions by field-theoretic methods based on the operator product expansion of local interaction fields. We apply this approach to manifolds in a random potential. Randomness is always relevant for fluid membranes, while for semi-flexible polymers there is a first order transition to the strong coupling regime at a finite temperature.

cond-mat.soft↗

arXiv1998

Optimizing Smith-Waterman alignments

Mutual correlation between segments of DNA or protein sequences can be detected by Smith-Waterman local alignments. We present a statistical analysis of alignment of such sequences, based on a recent scaling theory. A new fidelity measure is introduced and shown to capture the significance of the local alignment, i.e., the extent to which the correlated subsequences are correctly identified. It is demonstrated how the fidelity may be optimized in the space of penalty parameters using only the alignment score data of a single sequence pair.

cond-mat↗

arXiv1998

On Growth, Disorder, and Field Theory

This article reviews recent developments in statistical field theory far from equilibrium. It focuses on the Kardar-Parisi-Zhang equation of stochastic surface growth and its mathematical relatives, namely the stochastic Burgers equation in fluid mechanics and directed polymers in a medium with quenched disorder. At strong stochastic driving -- or at strong disorder, respectively -- these systems develop nonperturbative scale-invariance. Presumably exact values of the scaling exponents follow from a self-consistent asymptotic theory. This theory is based on the concept of an operator product expansion formed by the local scaling fields. The key difference to standard Lagrangian field theory is the appearance of a dangerous irrelevant coupling constant generating dynamical anomalies in the continuum limit.

cond-mat↗

arXiv1998

Optimal Detection of Sequence Similarity by Local Alignment

The statistical properties of local alignment algorithms with gaps are analyzed theoretically for uncorrelated and correlated DNA sequences. In the vicinity of the log-linear phase transition, the statistics of alignment with gaps is shown to be characteristically different from that of gapless alignment. The optimal scores obtained for uncorrelated sequences obey certain robust scaling laws. Deviation from these scaling laws signals sequence homology, and can be used to guide the empirical selection of scoring parameters for the optimal detection of sequence similarities. This can be accomplished in a computationally efficient way by using a novel approach focusing on the score landscape. Furthermore, by assuming a few gross features characterizing the statistics of underlying sequence-sequence correlations, quantitative criteria are obtained for the choice of optimal scoring parameters: Optimal similarity detection is most likely to occur in a region close to the log side of the log-linear phase transition.

cond-mat.stat-mech↗

arXiv1998

Scaling Laws and Similarity Detection in Sequence Alignment with Gaps

We study the problem of similarity detection by sequence alignment with gaps, using a recently established theoretical framework based on the morphology of alignment paths. Alignments of sequences without mutual correlations are found to have scale-invariant statistics. This is the basis for a scaling theory of alignments of correlated sequences. Using a simple Markov model of evolution, we generate sequences with well-defined mutual correlations and quantify the fidelity of an alignment in an unambiguous way. The scaling theory predicts the dependence of the fidelity on the alignment parameters and on the statistical evolution parameters characterizing the sequence correlations. Specific criteria for the optimal choice of alignment parameters emerge from this theory. The results are verified by extensive numerical simulations.

physics.bio-ph↗

arXiv1997

Quantized Scaling of Growing Surfaces

The Kardar-Parisi-Zhang universality class of stochastic surface growth is studied by exact field-theoretic methods. From previous numerical results, a few qualitative assumptions are inferred. In particular, height correlations should satisfy an operator product expansion and, unlike the correlations in a turbulent fluid, exhibit no multiscaling. These properties impose a quantization condition on the roughness exponent $χ$ and the dynamic exponent $z$. Hence the exact values $χ= 2/5, z = 8/5$ for two-dimensional and $χ= 2/7, z = 12/7$ for three-dimensional surfaces are derived.

cond-mat↗

arXiv1996

The Upper Critical Dimension of the KPZ Equation

The strong-coupling regime of Kardar-Parisi-Zhang surface growth driven by short-ranged noise has an upper critical dimension d_> less or equal to four (where the dynamic exponent z takes the value z (d_>) = 2). To derive this, we use the mapping onto directed polymers with quenched disorder. Two such polymers coupled by a small contact attraction are shown to form a bound state at all temperatures below the roughening temperature of a single polymer. Comparing the singularities of the localization length at and below the critical temperature yields d_> \leq 4.

cond-mat↗

arXiv1996

Vicinal Surfaces and the Calogero-Sutherland Model

A miscut (vicinal) crystal surface can be regarded as an array of meandering but non-crossing steps. Interactions between the steps are shown to induce a faceting transition of the surface between a homogeneous Luttinger liquid state and a low-temperature regime consisting of local step clusters in coexistence with ideal facets. This morphological transition is governed by a hitherto neglected critical line of the well-known Calogero-Sutherland model. Its exact solution yields expressions for measurable quantities that compare favorably with recent experiments on Si surfaces.

cond-mat↗

arXiv1996

Directed polymers in high dimensions

We study directed polymers subject to a quenched random potential in d transversal dimensions. This system is closely related to the Kardar-Parisi-Zhang equation of nonlinear stochastic growth. By a careful analysis of the perturbation theory we show that physical quantities develop singular behavior for d to 4. For example, the universal finite size amplitude of the free energy at the roughening transition is proportional to (4-d)^(1/2). This shows that the dimension d=4 plays a special role for this system and points towards d=4 as the upper critical dimension of the Kardar-Parisi-Zhang problem.

cond-mat↗

arXiv1995

Similarity-Detection and Localization

The detection of similarities between long DNA and protein sequences is studied using concepts of statistical physics. It is shown that mutual similarities can be detected by sequence alignment methods only if their amount exceeds a threshold value. The onset of detection is a continuous phase transition which can be viewed as a localization-delocalization transition. The ``fidelity'' of the alignment is the order parameter of that transition; it leads to criteria for the selection of optimal alignment parameters.

cond-mat↗

arXiv1995

On the Renormalization of the Kardar-Parisi-Zhang equation

The Kardar-Parisi-Zhang (KPZ) equation of nonlinear stochastic growth in d dimensions is studied using the mapping onto a system of directed polymers in a quenched random medium. The polymer problem is renormalized exactly in a minimally subtracted perturbation expansion about d = 2. For the KPZ roughening transition in dimensions d > 2, this renormalization group yields the dynamic exponent z* = 2 and the roughness exponent chi* = 0, which are exact to all orders in epsilon = (2 - d)/2. The expansion becomes singular in d = 4, which is hence identified with the upper critical dimension of the KPZ equation. The implications of this perturbation theory for the strong-coupling phase are discussed. In particular, it is shown that the correlation functions and the coupling constant defined in minimal subtraction develop an essential singularity at the strong-coupling fixed point.

cond-mat↗

arXiv1994

Fermions in a random medium

We study the continuum field theory for an ensemble of directed polymers r_i (t) in 1+d' dimensions that live in a medium with quenched point disorder and interact via short-ranged pair forces g Ψ(r_i - r_j). In the strong-disorder (or low-temperature) regime, such forces are found to be relevant in any dimension d' below the upper critical dimension for a single line. Attractive forces generate a bound state with localization length ξ_\perp \sim |g|^{-ν_\perp}; repulsive forces lead to mutual avoidance with a pair distribution function P(r_i - r_j) \sim |r_i - r_j|^θreminiscent of interacting fermions. In the experimentally important dimension d' = 2, we obtain ν_\perp \approx 0.8 and θ\approx 2.4 .

cond-mat↗

arXiv1992

Exact Critical Exponents of the Staircase Model

The staircase model is a recently discovered one-parameter family of integrable two-dimensional continuum field theories. We analyze the novel critical behavior of this model, seen as a perturbation of a minimal conformal theory M_p: the leading thermodynamic singularities are simultaneously governed by all fixed points M_p, M_{p-1}, ..., M_3. The exponents of the magnetic susceptibility and the specific heat are obtained exactly. Various corrections to scaling are discussed, among them a new type specific to crossover phenomena between critical fixed points.

hep-th↗

arXiv1991

Multiple Crossover Phenomena and Scale Hopping in Two Dimensions

We study the renormalization group for nearly marginal perturbations of a minimal conformal field theory M_p with p >> 1. To leading order in perturbation theory, we find a unique one-parameter family of ``hopping trajectories'' that is characterized by a staircase-like renormalization group flow of the C-function and the anomalous dimensions and that is related to a recently solved factorizable scattering theory. We argue that this system is described by interactions of the form t phi_{(1,3)} - t' ϕ_{(3,1)} . As a function of the relevant parameter t, it undergoes a phase transition with new critical exponents simultaneously governed by all fixed points M_p, M_{p-1}, ..., M_3. Integrable lattice models represent different phases of the same integrable system that are distinguished by the sign of the irrelevant parameter t'.

hep-th↗