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检索条件"任意字段=IEEE Computational Systems Bioinformatics Conference"

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Proceedings of the International Joint conference on Neural Networks 2005 (ieee Cat. No. 05CH37663C)

Proceedings of the International Joint Conference on Neural ...

引用

International Joint conference on Neural Networks (IJCNN)

The following topics are dealt with: neurodynamics and intentional dynamic systems; neural networks applications to bioinformatics; information-theoretic and Bayesian learning; ICA and PCA; models of neurons, local circuits and systems; evolvable and emergent neural systems; control and system identification; spiking neurons; computational neurogenetic modeling; advancements in adaptive resonance theory; genomics applications; proteomics and neuroinformatics and data mining, text and pattern recognition.

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Data Mining in situ gene expression patterns at cellular resolution

Data Mining in situ gene expression patterns at cellular res...

引用

ieee computational systems bioinformatics conference, CSB Workshops and Poster Abstracts

作者： J. Carson T. Ju C. Thaller M. Bello I. Kakadiaris J. Warren G. Eichele W. Chiu National Center for Macromolecular Imaging Baylor University College of Medicine Houston TX USA Department of Computer Science Rice University Houston TX USA Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor University College of Medicine Houston TX USA Visual Computing Lab Department of Computer Science University of Houston Houston TX USA Max-Planck-Institut of Experimental Endocrinology Hanover Germany

Non-radioactive in situ hybridization (ISH) is a powerful technique for revealing gene expression in individual cells, the level of detail necessary for investigating how genes control cell type identity, cell differentiation, and cell-cell signaling. Although the availability of robotic ISH enables the expeditious determination of expression patterns for thousands of genes in serially sectioned tissues, a large collection of ISH images is, per se, of limited benefit. However, via accurate detection of expression strength and spatial normalization of expression location across different specimens, ISH images become a minable resource of annotated gene expression capable of advancing functional genomics in a mode similar to DNA sequence databases. We have developed computational methods to automate robotic ISH image annotation and applied these to over 200 genes throughout the postnatal mouse brain. Gene expression strengths were quantified for each cell tissue section images, and these images were subjected to atlas-based segmentation using a series of subdivision mesh maps that comprise our atlas of the postnatal mouse brain. With this common geometric representation of gene expression, patterns are automatically annotated and spatial searches success fully find the genes expressed in a similar fashion to custom query patterns. Cluster analysis of spatially normalized expression patterns identifies potential relationships in gene networks. Annotated gene expression patterns and query interfaces are publicly accessible at wv/spl bsol/w. geneattas. org.

关键词： Data mining Gene expression Mice Signal resolution Robots Genomics bioinformatics DNA Sequences Image databases

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A learned comparative expression measure for Affymetrix genechip DNA microarrays

A learned comparative expression measure for Affymetrix gene...

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Proceedings of the ieee computational systems bioinformatics conference, CSB

作者： W. Sheffler E. Upfal J. Sedivy W.S. Noble Department of Genome Sciences University of Washington USA Department of Computer Science Brown University USA Department of Molecular and Cell Biology and Biochemistry Brown University USA Department of Genome Sciences Department of Computer Science and Engineering University of Washington USA

Perhaps the most common question that a microarray study can ask is, "Between two given biological conditions, which genes exhibit changed expression levels?" Existing methods for answering this question either generate a comparative measure based upon a static model, or take an indirect approach, first estimating absolute expression levels and then comparing the estimated levels to one another. We present a method for detecting changes in gene expression between two samples based on data from Affymetrix GeneChips. Using a library of over 200,000 known cases of differential expression, we create a learned comparative expression measure (LCEM) based on classification of probe-level data patterns as changed or unchanged. LCEM uses perfect match probe data only; mismatch probe values did not prove to be useful in this context. LCEM is particularly powerful in the case of small microarry studies, in which a regression-based method such as RMA cannot generalize, and in detecting small expression changes. At the levels of selectivity that are typical in microarray analysis, the LCEM shows a lower false discovery rate than either MAS5 or RMA trained from a single chip. When many chips are available to RMA, LCEM performs better on two out of the three data sets, and nearly as well on the third. Performance of the MAS5 log ratio statistic was notably bad on all datasets.

关键词： DNA Probes bioinformatics Support vector machines Testing Semiconductor device measurement Genomics Computer science Gene expression Statistics

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Effective Constrained Dynamic Simulation Using Implicit Constraint Enforcement

Effective Constrained Dynamic Simulation Using Implicit Cons...

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ieee International conference on Robotics and Automation (ICRA)

作者： Min Hong Min-Hyung Choi Sunhwa Jung S. Welch J. Trapp Bioinformatics University of Colorado Denver and Health Sciences Center Denver CO USA Computer Science and Engineering University of Colorado Denver and Health Sciences Center Denver CO USA Mechanical Engineering University of Colorado Denver and Health Sciences Center Denver CO USA

Stable and effective enforcement of hard constraints is one of the crucial components in controlling physics-based dynamic simulation systems. The conventional explicit Baumgarte constraint stabilization confines the time step to be within a stability limit and requires users to pick problem-dependent coefficients to achieve fast convergence or to prevent oscillations. The recently proposed post-stabilization method has shown a successful constraint drift reduction but it does not guarantee the physically correct behavior of motion and requires additional computational cost to decrease the constraint errors. This paper presents our new implicit constraint enforcement technique that is stable over large time steps and does not require problem dependent stabilization parameters. This new implicit constraint enforcement method uses the future time step to estimate the correct magnitude of the constraint forces, resulting in better stability over bigger time steps. More importantly, the proposed method generates physically conforming constraint forces while minimizing the constraint drifts, resulting in physically correct motion. Its asymptotic computational complexity is same as the explicit Baumgarte method. It can be easily integrated into various constrained dynamic systems including rigid body or deformable structure applications. This paper describes a formulation of implicit constraint enforcement and an accumulated constraint error and dynamic behavior analysis for comparison with existing methods.

关键词： Stability computational efficiency Convergence Error correction Lagrangian functions computational modeling bioinformatics Mechanical engineering computational complexity Robots

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Towards a computational Ontology of Mind

Towards a Computational Ontology of Mind

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ieee conference on Aerospace

作者： R. Ferrario A. Oltramari Laboratorio di Ontologia Applicata ISTC-CNR Italy Dipartimento di Scienze della Cognizione e della Formazione Universitá di Trento Trento Italy

The main goal of this paper is a preliminary characterization of the categories of the realm of the mental, able to fit and integrate the foundational ontology DOLCE (a Descriptive Ontology for Linguistic and Cognitive Engineering); we call this module COM (computational Ontology of Mind). The idea of COM emerges from the need of a conceptual clarification from the standpoint of formal ontology of the entities that play a role in agent technologies for information systems. Based on philosophical tradition, we have singled out a central relation in the realm of the mental: aboutness. In our proposal aboutness connects a mental state with a mental object, at a certain time, and with respect to a given intentional agent. Furthermore, we envisage a generalization of this framework to mental processes and events. Thus, in the paper we give a first analysis of these entities, mainly focused on mental objects and their characteristics. We are also specifying the basic features of mental states and intentional agents, exploiting ontological categories and relations implemented in DOLCE

关键词： Ontologies Information systems Biological system modeling computational biology Laboratories Uniform resource locators Proposals Cultural differences Electronic commerce bioinformatics

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Enhanced MVDR beamforming implementation with arbitrary linear arrays on DS/CDMA

Enhanced MVDR beamforming implementation with arbitrary line...

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ieee/ACES International conference on Wireless Communications and Applied computational Electromagnetics

作者： KyungSeok Kim Yong-Seok Choi Chang-Joo Kim Ik-Guen Choi Division of Bionics and Bioinformatics Chonbuk National University of Korea South Korea

ISBN: (纸本)0780390687

The efficient scheme for enhancing the performance of the MVDR beamforming for DS/CDMA systems is proposed. The main focus of the proposed scheme is to enhance the practical estimation of an array response vector for the MVDR beamforming on the arbitrary geometry structure of antenna arrays. Thus, the proposed scheme used the real Toeplitz-plus-Hankel approximation (RTHA) scheme to obtain the covariance matrix having the theoretical property of an overall noise-free signal. Computer simulation results are presented to show the effectiveness of the proposed scheme.

关键词： Array signal processing Multiaccess communication Linear antenna arrays Antenna arrays Adaptive arrays Covariance matrix Signal processing algorithms Multiple access interference Base stations Baseband

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An immune model and its application to a mobile robot simulator

An immune model and its application to a mobile robot simula...

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ieee International conference on Robotics and Biomimetics

作者： Tao Gong Sigma Xi Zixing Cai College of Information Science and Engineering Central South University Changsha China

Immune computation is burgeoning bioinformatics technique inspired from the natural immune system and can solve the information security problems such as antivirus and fault detection. And the immune model is a crucial problem of the artificial immune system. In this paper, an immune model was proposed for the application of a mobile robot simulator, which was infected by some worms, such the love worm and the happy-time worm. The immune model was comprised of three tiers, including the inherent immune tier, the adaptive immune tier and the parallel computing tier. This immune model was built on the theories of the natural immune system and had many excellent features, such as adaptability, immunity, memory, learning, and robustness. And the application example of the immune model in the mobile robot simulator showed, the artificial immune system can detect, recognize, learn and eliminate computer viruses, and can detect and repair faults such as software bugs, and so the immune computation is an excellent approach for antivirus security. Moreover, the application fields and prospect of the immune computation would be rich and successful in the near future

关键词： Mobile robots Immune system computational modeling Fault detection Computer worms Artificial immune systems Application software bioinformatics Information security Parallel processing

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Consistency, feasibility and multiplicity of fluxes in metabolic pathways

Consistency, feasibility and multiplicity of fluxes in metab...

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ieee International conference on systems Engineering

作者： R. Nigam W.W. Hansen Experimental Physics Laboratory University of Stanford Stanford CA USA

A simple test to check the consistency of large scale stoichiometric matrices in metabolic pathways is presented. Once the flux obtained is consistent, a systematic method is developed to examine the structure of multiple solutions in the metabolic network. Many of these multiple solutions are thermodynamically infeasible, hence a computational method is developed which is computationally intensive when we have to generate feasible multiple solutions. Changing certain fluxes, for example the glucose intake affects the growth of the cell or knocking out a particular gene can affect other fluxes, to explain such features we examine the sensitivity of fluxes to change in controllable fluxes. This technique has been applied to the metabolic network of Escherichia coli.

关键词： Biochemistry Thermodynamics System testing Sugar Steady-state Physics Laboratories Large-scale systems Genomics bioinformatics

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Identifying candidate genes using the BioWarehouse: a case study

Identifying candidate genes using the BioWarehouse: a case s...

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ieee International conference on systems Engineering

作者： Yannick Pouliot T.J. Lee V. Wagner P.D. Karp Bioinformatics Research Group Menlo Park CA USA

The BioWarehouse is an open source data warehousing environment focused on supporting bioinformatics databases (DBs). Operating on the MySQL or Oracle relational database management systems (RDBMSs), BioWarehouse integrates public source DBs such as Swiss-Prot and GenBank into a unified normalized schema operating under a single DB management system. BioWarehouse also imposes partial semantic normalization on the source data, thus decreasing semantic heterogeneity and facilitating multi-DB queries using the Structured Query Language (SQL). As an application case study of the BioWarehouse, we have identified candidate genes for "orphan" activities, defined as activities for which no cognate gene sequences exist. 1,356 (36%) of enzymatic activities that have been assigned an enzyme commission (EC) number are orphans (Karp, 2004). Such high prevalence is problematic, given that many of these activities are decades old and often perform essential functions. Most notably, the existence of orphans introduces gaps in sequence data that significantly limit the accuracy of genome annotation and metabolic pathway prediction. Fortunately, with more than 200 hundred genomes sequenced to completion, and with the availability of systems such as BioWarehouse, the computational identification of candidate genes associated with orphan activities can be envisioned. The BioWarehouse's conglomeration of databases, combined with Oracle 10g's native integration of analytical tools into SQL queries (such as the basic local alignment search tool (BLAST) and POSIX regular expressions), enabled us to identify a small number of high-confidence candidate genes associated with a specific orphan activity. We describe the complex queries used in this work to illustrate the value of the data warehousing approach to bioinformatics research.

关键词： Computer aided software engineering bioinformatics Biochemistry Genomics Warehousing Relational databases Organisms Database languages Java Uniform resource locators

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Exploring chemical space with computers: challenges and opportunities

Exploring chemical space with computers: challenges and oppo...

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International Joint conference on Neural Networks (IJCNN)

作者： P. Baldi School of Information and Computer Science Department of Biological Chemistry Director Institute for Genomics and Bioinformatics University of California Irvine Irvine CA USA

Summary form only given. Small molecules with at most a few dozen atoms play a fundamental role in organic chemistry and biology. They can be used as combinatorial building blocks for chemical synthesis, as molecular probes for perturbing and analyzing biological systems, and for the screening/design/discovery of new drugs. As datasets of small molecules become increasingly available, it becomes important to develop computational methods for the classification and analysis of small molecules and in particular for the prediction of their physical, chemical, and biological properties. We describe datasets and machine learning methods, in particular kernel methods, for chemical molecules represented by 1D strings, 2D graphs of bonds, and 3D structures. We demonstrate state-of-the-art results for the prediction of physical, chemical, or biological properties including the prediction of toxicity and anti-cancer activity. More broadly, we will discuss some of the challenges and opportunities for computer science, AI, and machine learning in chemistry.

关键词： Space exploration Biology computing Chemistry Chemical analysis Biochemical analysis Probes Biological systems Drugs Physics computing Learning systems

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