다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

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The Structure and Function of Complex Networks

Background on genetic algorithms, LISP, and genetic programming hierarchical problem-solving introduction to automatically-defined functions - the two-boxes problem problems that straddle the breakeven point for computational effort Boolean parity functions determining the architecture of the program the lawnmower problem the bumblebee problem the increasing benefits of ADFs as problems are scaled up finding an impulse response function artificial ant on the San Mateo trail obstacle-avoiding robot the minesweeper problem automatic discovery of detectors for letter recognition flushes and four-of-a-kinds in a pinochle deck introduction to biochemistry and molecular biology prediction of transmembrane domains in proteins prediction of omega loops in proteins lookahead version of the transmembrane problem evolutionary selection of the architecture of the program evolution of primitives and sufficiency evolutionary selection of terminals evolution of closure simultaneous evolution of architecture, primitive functions, terminals, sufficiency, and closure the role of representation and the lens effect Appendices: list of special symbols list of special functions list of type fonts default parameters computer implementation annotated bibliography of genetic programming electronic mailing list and public repository

Genetic Programming: On the Programming of Computers by Means of Natural Selection

An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.

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Ant system: optimization by a colony of cooperating agents

The recent availability of complete cell lineages from live imaging data opens the way to novel methodologies
for the automated analysis of cell dynamics in animal embryogenesis. We propose a method for the calcula-
tion of measure-based dissimilarities between cells. These dissimilarity measures allow the use of clustering
algorithms for the inference of time-persistent patterns. The method is applied to the digital cell lineages
reconstructed from live zebrafish embryos imaged from 6 to 13 hours post fertilization. We show that the
position and velocity of cells are sufficient to identify relevant morphological features including bilateral sym-
metry and coherent cell domains. The method is flexible enough to readily integrate larger sets of measures
opening the way to the automated identification of morphogenetic fields.

Cell Trajectory Clustering: Towards the Automated Identification of Morphogenetic Fields in Animal Embryogenesis.

The intrinsic complexity of biological systems creates huge amounts of unlabeled experimental data. The exploitation of such data can be achieved by performing active machine learning accompanied by a high-level symbolic expert who defines categories and their best boundaries using as little data as possible. We present a global strategy for designing active machine learning methods suited for the observation and analysis of complex systems, such as embryonic development. We developed a procedure that uses all available knowledge, whether gathered manually or automatically, and is able to readjust when new data is provided. We show that it is a powerful method for the investigation of the morphogenetic features of embryogenesis and specifically mitosis detection. It will make possible to properly reconstruct the in vivo cell morphodynamics, a main challenge of the post-genomic era.

Global Strategy of Active Machine Learning for Complex Systems: Embryogenesis Application on Cell Division Detection

Le but de ce papier est de montrer que classificateurs connexionnistes et classificateurs logiques sont fonctionnellement equivalents. Les classificateurs connexionnistes sont construits comme composition entre une memoire associative et une fonction de decision. Les modeles de memoires associatives etudiees dans ce papier sont des perceptrons multicouches et des modeles de Hopfield. Par l'operation de composition avec une fonction de decision, une memoire associative peut toujours etre transformee en un classificateur connexionniste. Les classificateurs logiques sont definis comme des ensembles de regles logiques qui envoient un espace d'entrees booleennes dans un espace de sorties booleennes. De tels classificateurs logiques peuvent constituer la base de connaissance d'un systeme-expert. Des methodes pour extraire un classificateur logique equivalent a un perceptron multi-couches suivi d'une fonction de decision sont egalement presentees. Celles-ci comprennent (i) la definition d'un domaine de validite pour le classificateur connexionniste, (ii) la detection d'invariances parmi les variables d'entree et (iii) l'extraction de regles equivalentes.

Equivalences entre classificateurs connexionnistes et classificateurs logiques

We present a method for hierarchic categorization and taxonomy evolution description. We focus on the structure of epistemic communities (ECs), or groups of agents sharing common knowledge concerns. Introducing a formal framework based on Galois lattices, we categorize ECs in an automated and hierarchically structured way and propose criteria for selecting the most relevant epistemic communities - for instance, ECs gathering a certain proportion of agents and thus prototypical of major fields. This process produces a manageable, insightful taxonomy of the community. Then, the longitudinal study of these static pictures makes possible an historical description. In particular, we capture stylized facts such as field progress, decline, specialization, interaction (merging or splitting), and paradigm emergence. The detection of such patterns in social networks could fruitfully be applied to other contexts.

Lattices for Dynamic, Hierarchic & Overlapping Categorization: the Case of Epistemic Communities

It is quite correct, as Ripps points out [1], that catalysis is a local process and thus cannot depend on the topology of the membrane as a whole. Our reason for positing that the reaction A + A! B only occurs inside the volume enclosed by the membrane is this: We imagined that the C molecules in the membrane are asymmetric, and that only the inner surface is catalytic. (This implies that if the membrane were turned inside out, to form an ‘‘inverse micelle,’’ catalysis would only occur on the outer surface, an arrangement that would obviously not be viable.) Actually, in the equations as they stand, catalysis of the reaction A + A ! B is indeed independent of the topology of the membrane (this is why, in Model 1 where B molecules are confined within the putative volume of the automaton whatever the size of the holes, the automaton will regenerate even if there is only a small fragment of membrane). We did not, however, make explicit our assumption about the asymmetry of the C molecules, and thus Ripps’ comment is quite justified. In any event, as Ripps also points out in the second part of his comment, it would make practically no difference if the outer surface of the membrane did also catalyze the reaction A + A! B. In this case, exactly as Ripps says, the B molecules would simply diffuse away; it is only inside the volume enclosed by the membrane that they can accumulate.

Paul Bourgine

Papers

Cell Trajectory Clustering: Towards the Automated Identification of Morphogenetic Fields in Animal Embryogenesis.

Global Strategy of Active Machine Learning for Complex Systems: Embryogenesis Application on Cell Division Detection

Equivalences entre classificateurs connexionnistes et classificateurs logiques

Lattices for Dynamic, Hierarchic & Overlapping Categorization: the Case of Epistemic Communities

Reply to Ripps