LEADER 05623nam 22006854a 450 001 9910143576103321 005 20170815112111.0 010 $a1-280-46270-1 010 $a9786610462704 010 $a0-470-36220-0 010 $a0-471-75650-4 010 $a0-471-75649-0 035 $a(CKB)1000000000355188 035 $a(EBL)261003 035 $a(OCoLC)77371248 035 $a(SSID)ssj0000217942 035 $a(PQKBManifestationID)11186871 035 $a(PQKBTitleCode)TC0000217942 035 $a(PQKBWorkID)10212464 035 $a(PQKB)11051224 035 $a(MiAaPQ)EBC261003 035 $a(EXLCZ)991000000000355188 100 $a20050413d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aParallel computing for bioinformatics and computational biology$b[electronic resource] $emodels, enabling technologies, and case studies /$fedited by Albert Y. Zomaya 210 $aHoboken, N.J. $cWiley-Interscience$dc2006 215 $a1 online resource (814 p.) 225 1 $aWiley series on parallel and distributed computing 300 $aDescription based upon print version of record. 311 $a0-471-71848-3 320 $aIncludes bibliographical references and index. 327 $aPARALLEL COMPUTING FOR BIOINFORMATICS AND COMPUTATIONAL BIOLOGY; CONTENTS; Preface; Contributors; Acknowledgments; PART I ALGORITHMS AND MODELS; 1 Parallel and Evolutionary Approaches to Computational Biology; 1.1 Introduction; 1.2 Bioinformatics; 1.3 Evolutionary Computation Applied to Computational Biology; 1.4 Conclusions; References; 2 Parallel Monte Carlo Simulation of HIV Molecular Evolution in Response to Immune Surveillance; 2.1 Introduction; 2.2 The Problem; 2.3 The Model; 2.4 Parallelization with MPI; 2.5 Parallel Random Number Generation; 2.6 Preliminary Simulation Results 327 $a2.7 Future DirectionsReferences; 3 Differential Evolutionary Algorithms for In Vivo Dynamic Analysis of Glycolysis and Pentose Phosphate Pathway in Escherichia coli; 3.1 Introduction; 3.2 Mathematical Model; 3.3 Estimation of the Parameters of the Model; 3.4 Kinetic Parameter Estimation by DE; 3.5 Simulation and Results; 3.6 Stability Analysis; 3.7 Control Characteristic; 3.8 Conclusions; References; 4 Compute-Intensive Simulations for Cellular Models; 4.1 Introduction; 4.2 Simulation Methods for Stochastic Chemical Kinetics; 4.3 Aspects of Biology - Genetic Regulation 327 $a4.4 Parallel Computing for Biological Systems4.5 Parallel Simulations; 4.6 Spatial Modeling of Cellular Systems; 4.7 Modeling Colonies of Cells; References; 5 Parallel Computation in Simulating Diffusion and Deformation in Human Brain; 5.1 Introduction; 5.2 Anisotropic Diffusion Simulation in White Matter Tractography; 5.3 Brain Deformation Simulation in Image-Guided Neurosurgery; 5.4 Summary; References; PART II SEQUENCE ANALYSIS AND MICROARRAYS; 6 Computational Molecular Biology; 6.1 Introduction; 6.2 Basic Concepts in Molecular Biology; 6.3 Global and Local Biological Sequence Alignment 327 $a6.4 Heuristic Approaches for Biological Sequence Comparison6.5 Parallel and Distributed Sequence Comparison; 6.6 Conclusions; References; 7 Special-Purpose Computing for Biological Sequence Analysis; 7.1 Introduction; 7.2 Hybrid Parallel Computer; 7.3 Dynamic Programming Communication Pattern; 7.4 Performance Evaluation; 7.5 Future Work and Open Problems; 7.6 Tutorial; References; 8 Multiple Sequence Alignment in Parallel on a Cluster of Workstations; 8.1 Introduction; 8.2 CLUSTAL W; 8.3 Implementation; 8.4 Results; 8.5 Conclusion; References 327 $a9 Searching Sequence Databases Using High-Performance BLASTs9.1 Introduction; 9.2 Basic Blast Algorithm; 9.3 Blast Usage and Performance Factors; 9.4 High Performance BLASTs; 9.5 Comparing BLAST Performance; 9.6 UMD-BLAST; 9.7 Future Directions; 9.8 Related Work; 9.9 Summary; References; 10 Parallel Implementations of Local Sequence Alignment: Hardware and Software; 10.1 Introduction; 10.2 Sequence Alignment Primer; 10.3 Smith-Waterman Algorithm; 10.4 FASTA; 10.5 BLAST; 10.6 HMMER - Hidden Markov Models; 10.7 ClustalW; 10.8 Specialized Hardware: FPGA; 10.9 Conclusion; References 327 $a11 Parallel Computing in the Analysis of Gene Expression Relationships 330 $aDiscover how to streamline complex bioinformatics applications with parallel computingThis publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution.A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster 410 0$aWiley series on parallel and distributed computing. 606 $aBioinformatics 606 $aComputational biology 606 $aParallel processing (Electronic computers) 608 $aElectronic books. 615 0$aBioinformatics. 615 0$aComputational biology. 615 0$aParallel processing (Electronic computers) 676 $a570.285435 676 $a572.8/0285 701 $aZomaya$b Albert Y$0521938 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143576103321 996 $aParallel computing for bioinformatics and computational biology$92171179 997 $aUNINA LEADER 05202nam 2200721 a 450 001 9910971650603321 005 20200520144314.0 010 $a9786610964338 010 $a9781280964336 010 $a1280964332 010 $a9780080469973 010 $a0080469973 035 $a(CKB)1000000000349975 035 $a(EBL)286648 035 $a(OCoLC)437176584 035 $a(SSID)ssj0000102839 035 $a(PQKBManifestationID)11122482 035 $a(PQKBTitleCode)TC0000102839 035 $a(PQKBWorkID)10061029 035 $a(PQKB)10775749 035 $a(Au-PeEL)EBL286648 035 $a(CaPaEBR)ebr10167026 035 $a(CaONFJC)MIL96433 035 $a(CaSebORM)9780080469973 035 $a(MiAaPQ)EBC286648 035 $a(PPN)170237923 035 $a(FR-PaCSA)40000596 035 $a(FRCYB40000596)40000596 035 $a(EXLCZ)991000000000349975 100 $a20030522d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalog interfacing to embedded microprocessor systems /$fStuart R. Ball 205 $a2nd ed. 210 $aAmsterdam ;$aBoston $cNewnes$dc2004 215 $a1 online resource (335 p.) 225 1 $aEmbedded technology series 300 $aRev. ed. of: Analog inter-facing to embedded microprocessors. 2001. 300 $aIncludes index. 311 08$a9780750677233 311 08$a0750677236 327 $aCover; TOCContents; Preface; CH1. System Design; Dynamic Range; Calibration; Bandwidth; Processor Throughput; Avoiding Excess Speed; Other System Considerations; Sample Rate and Aliasing; CH2. Analog-to-Digital Converters; ADCs; Types of ADCs; ADC Comparison; Sample and Hold; Real Parts; Microprocessor Interfacing; Clocked Interfaces; Serial Interfaces; Multichannel ADCs; Internal Microcontroller ADCs; Codecs; Interrupt Rates; Dual-Function Pins on Microcontrollers; Design Checklist; CH3. Sensors; Temperature Sensors; Optical Sensors; CCDs; Magnetic Sensors; Motion/Acceleration Sensors 327 $aStrain GaugesCH4. Time-Based Measurements; Measuring Period versus Frequency; Mixing; Voltage-to-Frequency Converters; Clock Resolution and Range; Extending Accuracy with Limited Resolution; CH5. Output Control Methods; Open-Loop Control; Negative Feedback and Control; Microprocessor-Based Systems; On-Off Control; Overshoot; Proportional Control; Proportional, Integral, Derivative Control; Motor Control; Predictive Control; Measuring and Analyzing Control Loops; PID Software Examples; Things to Remember in Control Design; CH6. Solenoids, Relays, and Other Analog Outputs; Solenoids; Heaters 327 $aCoolersLEDs; DACs; Digital Potentiometers; Analog Switches; CH7. Motors; Stepper Motors; DC Motors; Tradeoffs between Motors; Power-Up Issues; Motor Torque; A Real-World Stepper Application; CH8. Electromagnetic Interference; Ground Loops; Electrostatic Discharge; CH9. High-Precision Applications; Input Offset Voltage; Input Resistance; Frequency Characteristics; Temperature Effects in Resistors; Voltage References; Temperature Effects in General; Noise and Grounding; Printed Circuit Board Layout; Statistical Tolerancing; Supply-Based References; Summary; CH10. Standard Interfaces 327 $aIEEE 1451.2Fieldbus; CH11. Analog Toolbox; Microcontroller Supply and Reference; Resistor Networks; Multiple Input Control; AC Control; Voltage Monitors and Supervisory Circuits; Driving Bipolar Transistors; Driving MOSFETs; Reading Negative Voltages; Example Control System; Appendix A Opamp Basics; Opamp Configurations; General Opamp Design Equations; Nonresistive Elements; Reversing the Inputs; Comparators; Hysteresis; Instrumentation Amplifiers; Appendix B Pulse Width Modulation; Why PWM?; Real Parts; Frequency Limitations; Resolution Limitations; Power-Supply Considerations; PWM and EMI 327 $aAudio ApplicationsPWM Hardware; PWM Software; Appendix C Useful URLs; Semiconductors; Motors; Other; Appendix D Python Code for Chapter 11; Excel Data for Chapter 4; Glossary; IDXIndex 330 $aAnalog Interfacing to Embedded Microprocessors addresses the technologies and methods used in interfacing analog devices to microprocessors, providing in-depth coverage of practical control applications, op amp examples, and much more. A companion to the author's popular Embedded Microprocessor Systems: Real World Design, this new embedded systems book focuses on measurement and control of analog quantities in embedded systems that are required to interface to the real world. At a time when modern electronic systems are increasingly digital, a comprehensive source on interfacing the re 410 0$aEmbedded technology series. 606 $aEmbedded computer systems$xDesign and construction 615 0$aEmbedded computer systems$xDesign and construction. 676 $a004.16 700 $aBall$b Stuart R.$f1956-$0320860 701 $aBall$b Stuart R.$f1956-$0320860 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910971650603321 996 $aAnalog interfacing to embedded microprocessor systems$94335799 997 $aUNINA