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SinicView: an interactive visualization tool for comparison of multiple sequence alignment results

SinicView: an interactive visualization tool for comparison ...

引用

ieee computational systems bioinformatics conference, csb Workshops and Poster Abstracts

作者： Arthur Chun-Chieh Shih D.T. Lee Laurent Lin Chin-Lin Peng Shiang-Heng Chen Chun-Yi Wong Meng-Yuan Chou Tze-Chang Shiao Institute of Information Science and Genomics Research Center Academia Sinica Taiwan

In the initial stage of sequence analysis, a biologist is first faced with the questions about how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question about whether unaligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. In this paper, we present a versatile alignment visualization system, called SinicView, (for sequence-aligning innovative and interactive comparison viewer), which allows users to efficiently compare and evaluate assorted alignment results obtained by different tools. SinicView calculates similarity of the alignment outputs under a sliding window using the sum-of-pairs method and provides scoring profiles of each set of aligned sequences. Combined with the annotations information, the user can visually compare alignment results either in graphic scoring profiles or in plain text format of the aligned nucleotides. With SinicView. users can use their own data sequences to compare various alignment tools or scoring systems and select the most suitable one to perform alignment and sequence analysis. SinicView is avaiable for free download from http://***/.

关键词： Visualization bioinformatics Genomics Information analysis Graphics Information science Biology Performance analysis Graphical user interfaces User interfaces

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The significance of linearity of quantities in electrophoresed and blotted materials demonstrated by BandScan/spl copy/ - an analytical program

The significance of linearity of quantities in electrophores...

引用

ieee computational systems bioinformatics conference, csb Workshops and Poster Abstracts

作者： R.S. Gunasekera H. Damodaran Y. Rajakarunanayake K. Hyland Department of Biology University of Houston Victoria TX USA San Ramon CA USA Institute of Metabolic Disease Baylor University Medical Center Dallas TX USA

There is still an undervalued need for quantitation in the biological, biochemical, and the molecular genetic sciences. Quantitation of electroblotted materials such as DNA, RNA, and proteins and the quantitation of molecular weights in electrophoresed gels is often necessary to an undistorted analysis. Quantitation would ensure, for instance, that the quantities of the substances being assayed fall within the linear range of that method by which they are being studied, once the linear range has been determined by a linearity study: the common phenomenon of saturation and its reverse, insufficient samples, could be easily detected. A biological data representation program is discussed that converts the results of gels and blots to numerical values and presents these values in a graphical display that is amenable to meaningful comparisons. The main goal of this work is to be able to quantitate electrophoresed and blotted molecular and biochemical results while insuring that the samples processed are within the linear range of the methods employed. This study demonstrates errors that can occur when a linearity study is not conducted. Versatile, easy-to-use quantitative graphics programs, such as the BandScan program, can further pipe numerical output to spreadsheets or statistical packages and provide the bridge between modern computation and traditional wet lab techniques. This analytical bioinformatics program that allows for statistical analysis is also a valuable tool for teaching purposes in bioinformatics and Molecular Biology. BandScan is available free for academic institutions and class room work from the corresponding author.

关键词： Linearity Biological materials bioinformatics Biology Genetics DNA RNA Proteins Displays Graphics

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Cell phenotype classification based on 3D cell image analysis

Cell phenotype classification based on 3D cell image analysi...

引用

ieee computational systems bioinformatics conference, csb Workshops and Poster Abstracts

作者： F. Long H. Peng D. Sudar S. Lelievre D. Knowles Life Sciences /Genomics Division Lawrence Berkeley National Laboratory Berkeley CA USA Basic Medical Sciences Purdue University West Lafayette IN USA

Summary form only given. The accuracy of the histological classification of cells plays a determining role in disease diagnosis and treatment. Recent studies have shown that the distribution of chromatin-associated proteins reflects alterations in cell phenotype. Using 3D fluorescence images of cultured human breast epithelial cells with multiple known phenotypes, we have developed an automated method to classify the phenotype of epithelial cells based on their nuclear protein distribution. Features which describe the distribution of specific nuclear proteins are first measured, on a per nucleus basis, by our local bright feature (LBF) analysis technique. Features from thousands of nuclei with multiple, known phenotypes were then grouped by a novel voting-based clustering method into a number of clusters of similar pattern. This allows us to establish the statistical link between clusters and the phenotypes of the cells. Finally, we used this statistical link to predict the probable phenotype of individual or groups of nuclei. The results show that the combined use of 3D confocal imaging, image feature analysis, and clustering analysis provides an efficient way to predict the phenotype of epithelial cells based on the nuclear distribution of chromatin-associated proteins.

关键词： Image analysis Proteins bioinformatics Cells (biology) Genomics Biomedical imaging Medical diagnostic imaging Diseases Medical treatment Fluorescence

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Data Mining in situ gene expression patterns at cellular resolution

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

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

Proceedings of the International Joint Conference on Neural ...

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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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Evolving biosciences in multi-agent systems

Evolving biosciences in multi-agent systems

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ieee/WIC/ACM International conference on Intelligent Agent Technology (IAT)

作者： V.E. Mujica-V D. Sisalem R. Popescu-Zeletin Fraunhofer Fokus Institute Berlin Germany

This paper proposes a strong research interest in a field related to bioinformatics and computational biology in a multi-agent system (MAS). We promote the use of evolutionary computation within intelligent multi-agent systems taking particularly the enhancement of the neuron routing algorithm (NEURAL) in mobile ad hoc network (MANET). More precisely, we develop an intelligent mobile agent called the neural agent which significantly improves the performance of neural. Results demonstrated that the neural agent leads to significant benefits in the average end-to-end delay and the packet delivery ratio of the routing protocol.

关键词： Multiagent systems computational intelligence Mobile ad hoc networks bioinformatics computational biology Evolutionary computation Intelligent systems Intelligent networks Neurons Routing

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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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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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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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