Ao / Rieger / Chen Advances in Computational Algorithms and Data Analysis

1. Auflage 2008
ISBN: 978-1-4020-8919-0
Verlag: Springer Netherland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 588 Seiten, Web PDF

Reihe: Computer Science

offers state of the art  tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.

Zielgruppe

Research

Autoren/Hrsg.

Ao, Sio-Iong

Rieger, Burghard B.

Chen, Su-Shing

Inhaltsverzeichnis

Scaling Exponent for the Healthy and Diseased Heartbeat.- CLUSTAG & WCLUSTAG: Hierarchical Clustering Algorithms for Efficient Tag-SNP Selection.- The Effects of Gene Recruitment on the Evolvability and Robustness of Pattern-Forming Gene Networks.- Comprehensive Genetic Database of Expressed Sequence Tags for Coccolithophorids.- Hybrid Intelligent Regressions with Neural Network and Fuzzy Clustering.- Design of DroDeASys (Drowsy Detection and Alarming System).- The Calculation of Axisymmetric Duct Geometries for Incompressible Rotational Flow with Blockage Effects and Body Forces.- Fault Tolerant Cache Schemes.- Reversible Binary Coded Decimal Adders using Toffoli Gates.- Sparse Matrix Computational Techniques in Concept Decomposition Matrix Approximation.- Transferable E-cheques: An Application of Forward-Secure Serial Multi-signatures.- A Hidden Markov Model based Speech Recognition Approach to Automated Cryptanalysis of Two Time Pads.- A Reconfigurable and Modular Open Architecture Controller: The New Frontiers.- An Adaptive Machine Vision System for Parts Assembly Inspection.- Tactile Sensing-based Control System for Dexterous Robot Manipulation.- A Novel Kinematic Model for Rough Terrain Robots.- Behavior Emergence in Autonomous Robot Control by Means of Evolutionary Neural Networks.- Swarm Economics.- Machines Imitating Humans.- Reinforced ART (ReART) for Online Neural Control.- The Bump Hunting by the Decision Tree with the Genetic Algorithm.- Machine Learning Approaches for the Inversion of the Radiative Transfer Equation.- Enhancing the Performance of Entropy Algorithm using Minimum Tree in Decision Tree Classifier.- Numerical Analysis of Large Diameter Butterfly Valve.- Axial Crushing of Thin-Walled Columns with Octagonal Section: Modeling and Design.- A FastState Estimation Method for DC Motors.- Flatness based GPI Control for Flexible Robots.- Estimation of Mass-Spring-Dumper Systems.- MIMO PID Controller Synthesis with Closed-Loop Pole Assignment.- Robust Design of Motor PWM Control using Modeling and Simulation.- Modeling, Control and Simulation of a Novel Mobile Robotic System.- All Circuits Enumeration in Macro-Econometric Models.- Noise and Vibration Modeling for Anti-Lock Brake Systems.- Investigation of Single Phase Approximation and Mixture Model on Flow Behaviour and Heat Transfer of a Ferrofluid using CFD Simulation.- Two Level Parallel Grammatical Evolution.- Genetic Algorithms for Scenario Generation in Stochastic Programming.- New Approach of Recurrent Neural Network Weight Initialization.- GAHC: Hybrid Genetic Algorithm.- Forecasting Inflation with the Influence of Globalization using Artificial Neural Network-based Thin and Thick Models.- Pan-Tilt Motion Estimation Using Superposition-Type Spherical Compound-Like Eye.

Leseproben

Abstract Coccolithophorids are unicellular, marine, golden-brown, single-celled algae (Haptophyta) commonly found in near-surface waters in patchy distributions. They belong to the Phytoplankton family that is known to be responsible for much of the earth reproduction. Phytoplankton, just like plants live based on the energy obtained by Photosynthesis which produces oxygen. Substantial amount of oxygen in the earth’s atmosphere is produced by Phytoplankton through Photosynthesis.

The single-celled Emiliana Huxleyi is the most commonly known specie of Coccolithophorids and is known for extracting bicarbonate (HCO3) from its environment and producing calcium carbonate to form Coccoliths. Coccolithophorids are one of the world’s primary producers, contributing about 15% of the average oceanic phytoplankton biomass to the oceans. They produce elaborate, minute calcite platelets (Coccoliths), covering the cell to form a Coccosphere and supplying up to 60% of the bulk pelagic calcite deposited on the sea floors. In order to understand the genetics of Coccolithophorid and the complexities of their biochemical reactions, we decided to build a database to store a complete pro- file of these organisms’ genomes. Although a variety of such databases currently exist, (http://www.geneservice.co.uk/home/) none have yet been developed to comprehensively address the sequencing efforts underway by the Coccolithophorid research community. This database is called CocooExpress and is available to public (http://bioinfo.csusm.edu) for both data queries and sequence contribution.

Keywords Marinealga·Coccolithophorids·EmilianaHuxleyi ·ExpressedSequence Tags · Relational database · Entity Relationship Diagram

4.1 Introduction

Within the past decade many organisms have been examined and their DNA sequences were decoded. These DNA sequences are stored in databases and are used to solve many of the biological mysteries such as determining genes that code for proteins. There are several tools developed every year to contribute to these efforts and make break through where not possible before due to limitation of technology. CoccoExpress is a project dedicated to creating such one tool to serve as database and search engine of genetic data of Coccolithophorids, a family of species known for their unique ability to produce calcium carbonate platelets. Through extensive research, increasing number of sequences of this family is extracted. This project was initiated to create a tool to maintain this data and allow a meaningful representation of it by building relational structure among different sets of data.

CoccoExpress contains over 120,000 ESTs from Emiliania huxleyi. Emiliania Huxleyi (Ehux) is the most commonly known species of Coccolithophorids and was selected for whole genome sequencing by the Joint Genome Institute (JGI). The sequences are obtained through a number of experiments and collected by the researchers at California State University San Marcos. As explained in [1–3], each EST sequence is a single pass read from a randomly selected cDNA clones. ESTs can be assembled into either overlapping (contigs) or non-overlapping (singletons or singlets). Cluster analysis reveals the most likely arrangement of these fragments.