Putative xylosyltransferase genes in <Emphasis Type="Italic">Trichomonas vaginalis</Emphasis>

Protein xylosyltransferases are the group of enzymes which are involved in transferring xylose from UDP-d-xylose to serine residue in a protein. These enzymes are commonly found in multicellular organisms and in some unicellular organisms. Previously we had identified the xylosyltransferase (XT) genes in EST sequence of a unicellular organism Trichomonas vaginalis through in silico approach based on the sequence homology. To corroborate if these genes are putative XT genes, we designed a workflow based on the sequence characteristics of xylosyltransferase, to verify if any of the putative XT gene sequences have sequence motifs. The XT genes in T. vaginalis predicted by Hidden Markov Model (HMM) were further analyzed with PfamHMM to identify if each putative sequence belongs to a known protein family, with TMHMM to examine whether the predicted XTs are Golgi xylosyltransferases and with MEME to find out the conserved motifs. The results confirmed our earlier study that these XTs are related to N-linked XTs in plants. To confirm the in silico results further, we analyzed the N-linked glycans of T. vaginalis and the empirical data also confirmed the computational analysis.     

Bottom-up development of multicellular digital organisms

How multicellular creatures can be developed from single cells into multicellular forms is a basic question in research into artificial life. In this paper, we propose a possible anser to that question by developing multicellular digital organisms from singe-cell digital organisms. We have done experiments on a computer. First we defined a model of a single-cell organism which has open-ended evolvability and a self-replicating mechanism, so these single-cell digital organisms can develop into multicellular creatures which have better adaptability than single-cell ones under certain environments. The phenomena of cellular differentiation and cell self-organization were observed during the development of the multicellular digital organisms. This work was presented in part at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

Dominating,weakly stable,and uncovered sets: Properties and generalizations

We consider the problem of collective choice in a tournament, i.e., when the majority relation, which plays the role of the collective preference system on this set of alternatives, can be represented by a complete asymmetric oriented graph. We compare three solutions of the collective choice problem: minimal dominating, uncovered, and minimal weakly stable sets. We construct generalizations of the minimal dominating set and find out, with their help, how the system of dominating sets looks like in the general case. We formulate a criterion that determines whether an alternative belongs to a minimal weakly stable set. We find out how minimal weakly stable sets relate to uncovered sets. Based on the notion of stability of an alternative and the set of alternatives we construct generalizations for the notions of uncovered and weakly stable sets—the classes of k-stable alternatives and k-stable sets. We prove inclusion relations between these classes.     

MAKING WAVES: THE PARADIGMS OF DEVELOPMENTAL BIOLOGY AND THEIR IMPACT ON ARTIFICIAL LIFE AND EMBRYONICS

Artificial life ("Alife") is purported to subsume real life, but in practice life-as-it-could-be is not based on life-as-we-know-it, but rather on life-as-we-don't-know-it. In terms of developmental biology, this means that we have yet to decide which of numerous paradigms for the embryogenesis of organisms is correct, if any. Two paradigms are compared and contrasted: positionalinformation and differentiation waves.These provide very different models for the nascent field of embryonics, the construction of computers and robots based on ideas from embryology. The behavioral component of Alife is usually thought about in terms of neural networks. Yet bacteria, single-cell ciliates such as Paramecium, and multicellular organisms, such as the ciliated placazoan Trichoplax adhaerens, have reasonably rich behavioral repertoires without nervous systems at all. It is therefore suggested that if Alife is to imitate and go beyond real life, then simulations of these organisms may be the place to begin.     

Emergence and Adaptation

I investigate the relationship between adaptation, as defined in evolutionary theory through natural selection, and the concept of emergence. I argue that there is an essential correlation between the former, and “emergence” defined in the field of algorithmic simulations. I first show that the computational concept of emergence (in terms of incompressible simulation) can be correlated with a causal criterion of emergence (in terms of the specificity of the explanation of global patterns). On this ground, I argue that emergence in general involves some sort of selective processes. Finally, I show that a second criterion, concerning novel explanatory regularities following the emergence of a pattern, captures the robustness of emergence displayed by some cases of emergence (according to the first criterion). Emergent processes fulfilling both criteria are therefore exemplified in evolutionary biology by some so-called “innovations”, and mostly by the new units of fitness or new kinds of adaptations (like sexual reproduction, multicellular organisms, cells, societies) sometimes called “major transitions in evolution”, that recent research programs (Maynard-Smith and Szathmary 1995; Michod 1999) aims at explaining.

Numerical analysis on electroosmotic flows in a microchannel with rectangle-waved surface roughness using the Poisson–Nernst–Planck model

The present study has numerically investigated two-dimensional electroosmotic flows in a microchannel with dielectric walls of rectangle-waved surface roughness to understand the roughness effect. For the study, numerical simulations are performed by employing the Nernst–Planck equation for the ionic species and the Poisson equation for the electric potential, together with the traditional Navier–Stokes equation. Results show that the steady electroosmotic flow and ionic-species transport in a microscale channel are well predicted by the Poisson–Nernst–Planck model and depend significantly on the shape of surface roughness such as the amplitude and periodic length of wall wave. It is found that the fluid flows along the surface of waved wall without involving any flow separation because of the very strong normal component of EDL (electric double layer) electric field. The flow rate decreases exponentially with the amplitude of wall wave, whereas it increases linearly with the periodic length. It is mainly due to the fact that the external electric-potential distribution plays a crucial role in driving the electroosmotic flow through a microscale channel with surface roughness. Finally, the present results using the Poisson–Nernst–Planck model are compared with those using the traditional Poisson–Boltzmann model which may be valid in these scales.     

DNA chips for species identification and biological phylogenies

The codeword design problem is an important problem in DNA computing and its applications. Several theoretical analyses as well as practical solutions for short oligonucleotides (up to 20-mers) have been generated recently. These solutions have, in turn, suggested new applications to DNA-based indexing and natural language processing, in addition to the obvious applications to the problems of reliability and scalability that generated them. Here we continue the exploration of this type of DNA-based indexing for biological applications and show that DNA noncrosshybridizing (nxh) sets can be successfully applied to infer ab initio phylogenetic trees by providing a way to measure distances among different genomes indexed by sets of short oligonucleotides selected so as to minimize crosshybridization. These phylogenies are solidly established and well accepted in biology. The new technique is much more effective in terms of signal-to-noise ratio, cost and time than current methods. Second, it is demonstrated that DNA indexing does provide novel and principled insights into the phylogenesis of organisms hitherto inaccessible by current methods, such as a prediction of the origin of the Salmonella plasmid 50 as being acquired horizontally, likely from some bacteria somewhat related to Yesinia. Finally, DNA indexing can be scaled up to newly available universal DNA chips readily available both in vitro and in silico. In particular, we show how a recently obtained such set of nxh 16-mers can be used as a universal coordinate system in DNA spaces to characterize very large groups (families, genera, and even phylla) of organisms on a uniform biomarker reference system, a veritable and comprehensive “Atlas of Life”, as it is or as it could be on earth.     

Emergence of Collective Behavior in Evolving Populations of Flying Agents

We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and the other a relatively un-constrained system in which the behavior of agents is governed by evolved computer programs. The first system demonstrates the evolution of a form of multicellular organization, while the second demonstrates the evolution of a form of altruistic food sharing. In this article we describe both systems in detail, document the emergence of collective behavior, and argue that these systems present new opportunities for the study of group dynamics in an evolutionary context. We also provide a brief overview of the breve simulation environment in which the systems were produced, and of breve’s facilities for the rapid, exploratory development of visualization strategies for artificial life.     

Advanced hybrid-flux approach for output bounds of electro-osmotic flows: adaptive refinement and direct equilibrating strategies

Fluidic flow and species transport in integrated microfluidic devices can readily be simulated with computational fluid dynamics. Nevertheless, the common practice to evaluate the solution accuracy is to decrease the discretization size (i.e., mesh size) until the value of the quantity of interest (termed “output” here-in) does not change within a fixed tolerance. For systems of partial differential equations such as the ones needed to be solved for electro-osmotic flows, this procedure is inappropriate due to the resulting large computation cost when dealing with finer discretizations. Furthermore, in a design environment, when investigating many geometries and flow configurations, the numerical uncertainty in the output may not allow the designer to select the best design. In this paper, we present a numerical technique that is particularly appropriate to provide certainty information for outputs of electro-osmotic microflows. The method uses an a-posteriori error estimation technique termed the bound method to provide fast, inexpensive, and reliable bounds to the “output”, therefore, alleviating the need to systematically run different meshes. To demonstrate the usefulness of the bound method, the electro-osmotic flow applied to the cross-intersection in microchannel configuration is analyzed. The bound method presented in this paper is also extend to use an adaptive refinement strategy to sharpen the bounds, the direct equilibrating strategy to calculate the ‘hybrid-flux’ very efficiently, and parallel local computations to speed up the fine h-mesh computations.     

When MHD-based microfluidics is equivalent to pressure-driven flow

Magneto-hydrodynamics (MHD) provides a convenient, programmable means for propelling liquids and controlling fluid flow in microfluidic devices without a need for mechanical pumps and valves. When the magnetic field is uniform and the electric field in the electrolyte solution is confined to a plane that is perpendicular to the direction of the magnetic field, the Lorentz body force is irrotational and one can define a “Lorentz” potential. Since the MHD-induced flow field under these circumstances is identical to that of pressure-driven flow, one can utilize the large available body of knowledge about pressure-driven flows to predict MHD flows and infer MHD flow patterns. In this note, we prove the equivalence between MHD flows and pressure-driven flows under certain conditions other than flow in straight conduits with rectangular cross sections. We determine the velocity profile and the efficiency of MHD pumps, accounting for current transport in the electrolyte solutions. Then, we demonstrate how data available for pressure-driven flow can be utilized to study various MHD flows, in particular, in a conduit patterned with pillars such as may be useful for liquid chromatography and chemical reactors. In addition, we examine the effect of interior obstacles on the electric current flow in the conduit and show the existence of a particular pillar geometry that maximizes the current.     

Multiprocessor scheduling by generalized extremal optimization

We propose a solution of the multiprocessor scheduling problem based on applying a relatively new metaheuristic technique, called Generalized Extremal Optimization (GEO). GEO is inspired by a simple coevolutionary model known as the Bak–Sneppen model. The model describes an ecosystem consisting of N species. Evolution in this model is driven by a process in which the weakest species in the ecosystem, together with its nearest neighbors, is always forced to mutate. This process shows the characteristics of a phenomenon called punctuated equilibrium, which is observed in evolutionary biology. We interpret the multiprocessor scheduling problem in terms of the Bak–Sneppen model and apply the GEO algorithm to solve the problem. We show that the proposed optimization technique is simple and yet outperforms genetic algorithm-based and swarm algorithm-based approaches to the multiprocessor scheduling problem.     

Relational retrieval using a combination of path-constrained random walks

Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval or named entity recognition (NER) to be formulated as typed proximity queries in the graph. One popular proximity measure is called Random Walk with Restart (RWR), and much work has been done on the supervised learning of RWR measures by associating each edge label with a parameter. In this paper, we describe a novel learnable proximity measure which instead uses one weight per edge label sequence: proximity is defined by a weighted combination of simple “path experts”, each corresponding to following a particular sequence of labeled edges. Experiments on eight tasks in two subdomains of biology show that the new learning method significantly outperforms the RWR model (both trained and untrained). We also extend the method to support two additional types of experts to model intrinsic properties of entities: query-independent experts, which generalize the PageRank measure, and popular entity experts which allow rankings to be adjusted for particular entities that are especially important.     

The right tool for the wrong task? Match and mismatch between first and second stimulus in double stimulation

Using Vygotsky’s notion of double stimulation as an analytical tool, we discuss the complex relationship between tasks, tools, and agency in CSCL environments. Empirically we examine how learners in a Norwegian senior high school class learning English as a foreign language approach and respond to an open-ended and collectively oriented task using a wiki. Our findings show that collectively oriented knowledge and language production takes place locally in small groups as well as in the larger collective of the class, and that learners find it difficult to maintain awareness of both levels of activity. However, when facing a breakdown in the wiki application, learners sustained strategies that carried many of the characteristics of collective production. We argue that there is a need to further theorize the task-tool relationship in activities involving collective knowledge production and that we need to align pedagogical as well as technological designs in order to give support for such efforts.     

Representation of shift-invariant operators onL 2 byH ∞ transfer functions: An elementary proof,a generalization toL p,and a counterexample forL ∞

We give an elementary proof of the well-known fact that shift-invariant operators onL ²[0, ∞) are represented by transfer functions which are bounded and analytic on the right open half-plane. We prove a generalization to Banach space-valuedL ^p -functions, where 1≤p<∞. We show that the result no longer holds forp=∞. This research was supported partially by the Weizmann Fellowship, and partially by the Air Force Office of Scientific Research under Contract F49620-86-C-0111.     

High survivability of a large colony through a small-world relationship

In this article, energy trophallaxis, i.e., distributed autonomous energy management methodology inspired by social insects and bat behavior, and its advantages, are shown by a series of computer simulations to address the survivability of organized groups of agents in a dynamic environment with uncertainty. The uncertainty of the agents’ organizational behavior is represented by two Lévy distributions. By carefully controlling energy donation behavior based on these distributions, we can examine the survivability of a larger group that traditional methods cannot analyze. As a result, even a small degree of friendship throughout the organization makes the group’s survivability improve dramatically.     

Collective Tree Spanners in Graphs with Bounded Parameters

In this paper we study collective additive tree spanners for special families of graphs including planar graphs, graphs with bounded genus, graphs with bounded tree-width, graphs with bounded clique-width, and graphs with bounded chordality. We say that a graph G=(V,E) admits a system of μ collective additive tree r -spanners if there is a system $\mathcal{T}(G)In this paper we study collective additive tree spanners for special families of graphs including planar graphs, graphs with bounded genus, graphs with bounded tree-width, graphs with bounded clique-width, and graphs with bounded chordality. We say that a graph G=(V,E) admits a system of μ collective additive tree r -spanners if there is a system T(G)\mathcal{T}(G) of at most μ spanning trees of G such that for any two vertices x,y of G a spanning tree T ? T(G)T\in\mathcal{T}(G) exists such that d _T (x,y)≤d _G (x,y)+r. We describe a general method for constructing a “small” system of collective additive tree r-spanners with small values of r for “well” decomposable graphs, and as a byproduct show (among other results) that any weighted planar graph admits a system of O(?n)O(\sqrt{n}) collective additive tree 0-spanners, any weighted graph with tree-width at most k−1 admits a system of klog ₂ n collective additive tree 0-spanners, any weighted graph with clique-width at most k admits a system of klog _3/2 n collective additive tree (2w)(2\mathsf{w}) -spanners, and any weighted graph with size of largest induced cycle at most c admits a system of log ₂ n collective additive tree (2?c/2?w)(2\lfloor c/2\rfloor\mathsf{w}) -spanners and a system of 4log ₂ n collective additive tree (2(?c/3?+1)w)(2(\lfloor c/3\rfloor +1)\mathsf {w}) -spanners (here, w\mathsf{w} is the maximum edge weight in G). The latter result is refined for weighted weakly chordal graphs: any such graph admits a system of 4log ₂ n collective additive tree (2w)(2\mathsf{w}) -spanners. Furthermore, based on this collection of trees, we derive a compact and efficient routing scheme for those families of graphs.     

Global observability of flows on the torus: An application of number theory

Kronecker's theorem is used to show that the irrational flows on then-dimensional torus are globally observed by a large class of continuous functions. These results are used to study the observability of Riccati flows on the Grassman manifolds.Supported in part by NASA Grant # NAG 2-203.     

Optimizing mixing in channel flows: kinematic aspects associated with secondary flows in the cross-section

We consider an Eulerian predictor of optimal mixing appropriate for steady, three-dimensional channel flow of the type that is commonly used in a variety of microfluidic mixing applications. This Eulerian indicator is applied to a kinematic model of the channel flow that allows one to control the flow structure of the secondary flows and the number of distinct secondary flows. The cases of two and three distinct secondary flows are considered and the Eulerian indicator predicts the optimal flow structure in the two secondary flow case and in the three secondary flow case that result in the best mixing. Moreover, it is shown that the case of three secondary flows mixes “optimally” (i.e., faster and more completely) than the case of two secondary flows. An explanation of this difference is given in terms of the Eulerian flow structure.