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have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of

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Factors that affect he probability of genetic transformation f Escherichia coli by plasmids have been evaluated. A set of conditions is described under which about one in every 400 plasmid molecules produces a transformed cell. These conditions include cell growth in medium containing elevated levels of Mg 2+. and incubation of the cells at 0 ~ in a solution of Mn 2+, ("a 2+, Rb + or K +, dimethyl sulfoxide, dithiothreitol, and hexamine cobalt (III). Transibrmation efficiency declines linearly with increasing plasmid size. Relaxed and supercoiled plasmids transfol'm with similar probabilities. Non-transforming DNAs compete consistent with mass. No significant variation is observed between competing DNAs of difi~rent source, complexity, length or form. Competition with both transforming and non-transforming plasmids indicates that each cell is capable of taking up many DNA molecules, and that the establishment of a transformation event is neither helped nor hindered significantly by the presence of multiple plasmids. 1. Introduct ion Both gram-posit ive and gram-negative bacteria can take up and stably establish

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

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Copyright c ○ 2005 by Cambridge University Press. This material is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University

The prediction of a protein's conformation from its aminoacid sequence is one of the most prominent problems in computational biology. Here, we focus on a widely studied abstraction of this problem, the two dimensional hydrophobic-polar (2D HP) protein folding problem.

Agent software is a rapidly developing area of research. However, the overuse of the word ‘agent ’ has tended to mask the fact that, in reality, there is a truly heterogeneous body of research being carried out under this banner. This overview paper presents a typology of agents. Next, it places agents in context, defines them and then goes on, inter alia, to overview critically the rationales, hypotheses, goals, challenges and state-of-the-art demonstrators of the various agent types in our typology. Hence, it attempts to make explicit much of what is usually implicit in the agents literature. It also proceeds to overview some other general issues which pertain to all the types of agents in the typology. This paper largely reviews software agents, and it also contains some strong opinions that are not necessarily widely accepted by the agent community. 1 1

problem simplified models such as hydrophobic-polar (HP) model have become one of the major tools for studying protein structure. Various optimization methods have been applied on folding problem including Monte Carlo methods, evolutionary algorithm, ant colony optimization algorithm. In this work we