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The proceedings contain 21 papers. The special focus in this conference is on Formal Modeling. The topics include: From service identification to service selection: An interleaved perspective;towards a system model for ensembles;algorithmic aspects of risk management;parameterized metareasoning in membership equational logic;fast sort computations for order-sorted matching and unification;Solving the first verified software competition problems using PVS;towards a maude formal environment;multisimulations: Towards next generation integrated simulation environments;semantics, simulation, and formal analysis of modeling languages for embedded systems in real-time maude;honoring carolyn talcott’s contributions to science;computational biology: A programming perspective;applications of pathway logic modeling to target identification;ten years of analyzing actors: Rebeca experience;mathematical models of object-based distributed systems;From explicit to symbolic types for communication protocols in CCS;Abstract LR-parsing;fractionated software for networked cyber-physical systems: Research directions and long-term vision;model feasible interactions in distributed real-time systems;puff, the magic protocol.

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Fuzzy logic point of view applied to diseases caused by dynamic mutations

Fuzzy logic point of view applied to diseases caused by dyna...

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International symposium on computational intelligence and Informatics

作者： A. Savić K. Jovanović J. Mihailović K. Radotić Institute for multidisciplinary research Belgrade Serbia Faculty of Biology University of Belgrade Belgrade Serbia Faculty of Physical Chemistry University of Belgrade Belgrade Serbia

For the first time, this paper tries to explain the origins of diseases caused by unstable DNA repeats, known as dynamic mutations. It is common to find fairly simplified correlation between the number of DNA repeats and severity of diseases. By examining the case studies, it is possible to see that simplified model does not reflect real condition of the patients, so we have proposed more complex model which involves gender, immunological condition, age of onset and analysis of family tree. Conclusions are related to known molecular biology phenomenon such as DNA methylation, histone binding and RNA secondary structure.

关键词： Diseases DNA Mathematical model Fuzzy logic Artificial intelligence Medical diagnostic imaging

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Parallel Algorithms for Bayesian Networks Structure Learning with Applications to Systems biology

Parallel Algorithms for Bayesian Networks Structure Learning...

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ieee International symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Olga Nikolova Bioinformatics and Computational Biology Department of Computer Engineering Iowa State University Ames IA USA

Bayesian networks (BN) are probabilistic graphical models which are widely utilized in modeling complex biological interactions in the cell. Learning the structure of a BN is an NP-hard problem and existing exact and heuristic solutions do not scale to large enough domains to allow for meaningful modeling of many biological processes. In this work, we present efficient parallel algorithms which push the scale of both exact and heuristic BN structure learning. We demonstrate the applicability of our methods by implementations on an IBM Blue Gene/L and an AMD Opteron cluster, and discuss their significance for future applications to systems biology.

关键词： Parallel algorithms Hypercubes Program processors Bayesian methods Lattices computational modeling Markov processes

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WaveMap: Interactively discovering features from protein flexibility matrices using wavelet-based visual analytics

WaveMap: Interactively discovering features from protein fle...

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13th Eurographics / ieee symposium on Visualization, EuroVis 2011

作者： Barlowe, Scott Liu, Yujie Yang, Jing Livesay, Dennis R. Jacobs, Donald J. Mottonen, James Verma, Deeptak Dept. of Computer Science University of North Carolina Charlotte NC United States Dept. of Bioinformatics and Genomics University of North Carolina Charlotte NC United States Dept. of Physics and Optical Science University of North Carolina Charlotte NC United States

The knowledge gained from biology datasets can streamline and speed-up pharmaceutical development. However, computational models generate so much information regarding protein behavior that large-scale analysis by traditional methods is almost impossible. The volume of data produced makes the transition from data to knowledge difficult and hinders biomedical advances. In this work, we present a novel visual analytics approach named WaveMap for exploring data generated by a protein flexibility model. WaveMap integrates wavelet analysis, visualizations, and interactions to facilitate the browsing, feature identification, and comparison of protein attributes represented by two-dimensional plots. We have implemented a fully working prototype of WaveMap and illustrate its usefulness through expert evaluation and an example scenario. © 2011 The Author(s) Journal compilation © 2011 The Eurographics Association and Blackwell Publishing Ltd. Published by Blackwell Publishing.

关键词： Pattern recognition

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An effective network-based Intrusion Detection using Conserved Self Pattern Recognition Algorithm augmented with near-deterministic detector generation

An effective network-based Intrusion Detection using Conserv...

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ieee symposium on computational intelligence in Cyber Security, CICS

作者： Senhua Yu Dipankar Dasgupta Department of Computer Science University of Memphis Memphis TN USA

The Human Immune System (HIS) employs multilevel defense against harmful and unseen pathogens through innate and adaptive immunity. Innate immunity protects the body from the known invaders whereas adaptive immunity develops a memory of past encounter and has the ability to learn about previously unknown pathogens. These salient features of the HIS are inspiring the researchers in the area of intrusion detection to develop automated and adaptive defensive tools. This paper presents a new variant of Conserved Self Pattern Recognition Algorithm (CSPRA) called CSPRA-ID (CSPRA for Intrusion Detection). The CSPRA-ID is given the capability of effectively identifying known intrusions by utilizing the knowledge of well-known attacks to build a conserved self pattern (APC detector) while it retains the ability to detect novel intrusions because of the nature of one-class classification of the T detectors. Furthermore, the T detectors in the CSPRA-ID are generated with a novel near-deterministic scheme that is proposed in this paper. The near-deterministic generation scheme places the detector with Brute Force method to guarantee the next detector to be very foreign to the existing detector. Moreover, the placement of the variable-sized detector is online determined during the Monte Carlo estimate of detector coverage and thus the detectors with an optimal distribution are generated without any additional optimization step. A comparative study between CSPRA-ID and one-class SVM shows that the CSPRA-ID is promising on DARPA network intrusion data in terms of detection accuracy and computation efficiency.

关键词： Detectors Testing Iris Intrusion detection Monte Carlo methods bioinformatics Algorithm design and analysis

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Computing the Tree of Life: Leveraging the Power of Desktop and Service Grids

Computing the Tree of Life: Leveraging the Power of Desktop ...

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ieee International symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Adam L. Bazinet Michael P. Cummings Center of Bioinformatics and Computational Biology University of Maryland College Park MD USA

The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests.

关键词： Runtime computational modeling Phylogeny Grid computing Lattices Software Vegetation

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Insect navigation and communication in flight and migration: A potential model for joining and collision avoidance in MAVs and mobile robots fleet control

Insect navigation and communication in flight and migration:...

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2011 ieee Aerospace Conference, AERO 2011

作者： Ma, Zhanshan Krings, Axel W. Millar, Richard Wang, Feng Chao, Jun Computational Biology and Bioinformatics Lab. KIZ Chinese Academy of Sciences China Computer Science Department University of Idaho Moscow ID 83843 United States Department of Systems Engineering Naval Postgraduate School Patuxent River NAS MD United States Computer Science Department Kunming Univ. of Science and Technology Kunming 650223 China Chinese Academy of Sciences Kunming 650223 China Computer Science Dept. iBEST University of Idaho United States

ISBN: (纸本)9781424473502

The human being should be awarded the championship of navigation on the planet, on the virtues that they not only have invented and manufactured the compass, GPS, aircraft, vessel, spacecraft, but also have demonstrated exceptional non-instrumental navigation skills. The Austronesian expansion from the Asian mainland into the Pacific performed by the Pacific navigators, who eventually populated the most remote islands of the Pacific about 4000 years ago, is a vivid example (Wehner 1998). However, animals, especially flying birds and insects are strong contenders. Monarch butterflies can migrate up to 2000 miles from their reproductive sites in the eastern US and Canada to their over-wintering sites in the forests of Mexico, and it is postulated that they may possess a biological equivalent of a low-resolution GPS system that is based on the magnetic field of the earth. In fact, even the long-legged ants (Cataglyphis fortis) in the Saharan desert use the dead-reckoning navigation strategy, which is attributed to the Polynesians, but the ants apparently have acquired the capability much earlier, given the relative short evolutionary history of humans. In this article, we briefly review the state-of-the-art research on insect navigation and communication used in flight and communication, with the objective to inspire cross-disciplinary studies in aerospace engineering, biology and computer science. After a brief review, we overview and identify seven cross-disciplinary research topics that may draw on inspirations from insect navigation and communication in flight and migration. These topics include: ants colony inspired swarm intelligence, honeybee inspired group decision-making, insect sociobiology, MAV/mobile robot flight control and remote control of insect flights, optimal migration strategy, Quorum sensing, and joining and collision avoidance for MAV fleet control. An interesting question one may pose is: given the rich and advanced navigation and communication t

关键词： Global positioning system

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The role of reward structure, coordination mechanism and net return in the evolution of cooperation

The role of reward structure, coordination mechanism and net...

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ieee symposium on computational intelligence and Games, CIG

作者： Padmini Rajagopalan Aditya Rawal Risto Miikkulainen Marc A. Wiseman Kay E. Holekamp Department of Computer Science University of Texas at Austin Austin TX USA Department of Zoology Michigan State University East Lansing MI USA

biology can offer insight into how realistic artificial agents and complex interactions between them can be created. For instance, spotted hyenas of Western Africa typically hunt alone, but cooperate once in a while to catch zebras. Using hyenas as motivation, this paper evaluates three potential factors that affect the evolution of cooperation in a team of game agents: reward structure (i.e. whether fitness reward is given to an individual agent or shared by the team), coordination mechanism (i.e. stigmergic vs. direct communication), and net return (i.e. the size of reward relative to the difficulty of obtaining it). Through neuroevolution using Multi-Component ESP [1], three predators were evolved in a field containing multiple fixed-behavior prey. Six such experiments show that (1) although shared reward strongly promotes cooperation, it is not strictly necessary for evolving cooperation; (2) although stigmergic coordination works well in simple, unambiguous tasks (i.e. with a single prey), direct communication is more effective in more complex tasks (i.e. with multiple prey); and (3) the predators evolve to hunt alone or cooperatively based on which approach results in higher net return. Insights from these computational simulations can be used to develop more intelligent behaviors for game agents in the future.

关键词： Neurons Predator prey systems Games Biological neural networks computational modeling Conferences Computer architecture

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