Pubbl/distr/stampa	London, : Imperial College Press, c2004
Descrizione fisica	1 online resource (254 p.)
Disciplina	610.28
Altri autori (Persone)	CerrolazaM
Soggetto topico	Bioengineering - Computer simulation Computational biology
ISBN	1-281-86646-6 9786611866464 1-86094-540-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Computational Bioengineering: Current Trends and Applications; Preface; CONTENTS; The Living Human Project: The Grand Challenge of European Biomechanics? Marco Viceconti, Fulvia Taddei, Alessandro Chiarini, Alberto Leardini and Debora Testi; Use of Explicit FE in the Pre-clinical Testing of Total Knee Replacement Mark Taylor, Rachel Tan, Jason Halloran and Paul Rullkoetter; The Plumbing of Long Bones S. C. Cowin; An Analysis of the Performance of Meshless Methods in Biomechanics M. Doblare, E. Cueto, B. Calvo, M. A . Martinez, J . M. Garcia and E. Pena Assessment of Plaque Stability Based on High-Resolution Magnetic Resonance Imaging of Human Atherosclerotic Lesions and Computational Mechanical Analysis Christian A . J. Schulze-Bauer, Michael StadleComputational Mechanobiology P. J. Prendergast; Optimization Models in the Simulation of the Bone Adaptation Process H. Rodrigues and P. R. Fernandes; Analysis of Blood Flow in Arteries by Means of Hagen - Poiseuille's Model J . Wojnarowski Thermomechanics of Bone-Implant Interfaces after Cemented Joint Arthroplasty: Theoretical Models and Computational Aspects L. R. Rakotomanana and N. A. RamanirakaAnalysis of Transient Blood Flow Passing through Mechanical Heart Valves by Lattice Boltzmann Methods O. Pelliccioni, M. Cerrolaza and M. Herrera
Record Nr.	UNINA-9910783483003321

Edizione	[1st ed.]
Pubbl/distr/stampa	London, : Imperial College Press, c2004
Descrizione fisica	1 online resource (254 p.)
Disciplina	610.28
Altri autori (Persone)	CerrolazaM
Soggetto topico	Bioengineering - Computer simulation Computational biology
ISBN	1-281-86646-6 9786611866464 1-86094-540-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Computational Bioengineering: Current Trends and Applications; Preface; CONTENTS; The Living Human Project: The Grand Challenge of European Biomechanics? Marco Viceconti, Fulvia Taddei, Alessandro Chiarini, Alberto Leardini and Debora Testi; Use of Explicit FE in the Pre-clinical Testing of Total Knee Replacement Mark Taylor, Rachel Tan, Jason Halloran and Paul Rullkoetter; The Plumbing of Long Bones S. C. Cowin; An Analysis of the Performance of Meshless Methods in Biomechanics M. Doblare, E. Cueto, B. Calvo, M. A . Martinez, J . M. Garcia and E. Pena Assessment of Plaque Stability Based on High-Resolution Magnetic Resonance Imaging of Human Atherosclerotic Lesions and Computational Mechanical Analysis Christian A . J. Schulze-Bauer, Michael StadleComputational Mechanobiology P. J. Prendergast; Optimization Models in the Simulation of the Bone Adaptation Process H. Rodrigues and P. R. Fernandes; Analysis of Blood Flow in Arteries by Means of Hagen - Poiseuille's Model J . Wojnarowski Thermomechanics of Bone-Implant Interfaces after Cemented Joint Arthroplasty: Theoretical Models and Computational Aspects L. R. Rakotomanana and N. A. RamanirakaAnalysis of Transient Blood Flow Passing through Mechanical Heart Valves by Lattice Boltzmann Methods O. Pelliccioni, M. Cerrolaza and M. Herrera
Record Nr.	UNINA-9910824226203321

Pubbl/distr/stampa	London, : Imperial College Press, c2012
Descrizione fisica	1 online resource (318 p.)
Disciplina	006.3
Altri autori (Persone)	LamH. K NguyenHung T LingSteve S. H
Soggetto topico	Computational intelligence Artificial intelligence
Soggetto genere / forma	Electronic books.
ISBN	1-283-59351-3 9786613905963 1-84816-692-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Preface; Contents; Evolutionary Computation and its Applications; 1. Maximal Margin Algorithms for Pose Estimation Ying Guo and Jiaming Li; Contents; 1.1. Introduction; 1.2. Pose Detection Algorithm; 1.2.1. Procedure of pose detection; 1.2.2. Eigen Pose Space; 1.3. Maximal Margin Algorithms for Classification; 1.3.1. Support vector machines; 1.3.2. Boosting; 1.3.3. Soft margin AdaBoost; 1.3.4. Margin distribution; 1.4. Experiments and Discussions; 1.4.1. Data preparation; 1.4.2. Data preprocessing; 1.4.3. Experiment results of Group A; 1.4.4. Margin distribution graphs 1.4.5. Experiment results of Group B1.5. Conclusion; References; 2. Polynomial Modeling in a Dynamic Environment based on a Particle Swarm Optimization Kit Yan Chan and Tharam S. Dillon; Contents; 2.1. Introduction; 2.2. PSO for Polynomial Modeling; 2.3. PSO vs. GP; References; 3. Restoration of Half-toned Color-quantized Images Using Particle Swarm Optimization with Multi-wavelet Mutation Frank H.F. Leung, Benny C.W. Yeung and Y.H. Chan; Contents; 3.1. Introduction; 3.2. Color Quantization With Half-toning; 3.3. Formulation of Restoration Algorithm 3.3.1. PSO with multi-wavelet mutation (MWPSO)3.3.2. The tness function; 3.3.3. Restoration with MWPSO; 3.3.4. Experimental setup; 3.4. Result and Analysis; 3.5. Conclusion; References; Fuzzy Logics and their Applications; 4. Hypoglycemia Detection for Insulin-dependent Diabetes Mellitus: Evolved Fuzzy Inference System Approach S.H. Ling, P.P. San and H.T. Nguyen; Contents; 4.1. Introduction; 4.2. Hypoglycemia Detection System: Evolved Fuzzy Inference System Approach; 4.2.1. Fuzzy inference system; 4.2.1.1. Fuzzification; 4.2.1.2. Fuzzy reasoning; 4.2.1.3. Defuzzification 4.2.2. Particle swarm optimization with wavelet mutation4.2.2.1. Wavelet mutation; 4.2.3. Choosing the HPSOWM parameters; 4.2.4. Fitness function and training; 4.3. Results and Discussion; 4.4. Conclusion; References; Neural Networks and their Applications; 5. Study of Limit Cycle Behavior of Weights of Perceptron C.Y.F. Ho and B.W.K. Ling; Contents; 5.1. Introduction; 5.2. Notations; 5.3. Global Boundness Property; 5.4. Limit Cycle Behavior; 5.5. Application of Perceptron Exhibiting Limit Cycle Behavior; 5.6. Conclusion; References 6. Artificial Neural Network Modeling with Application to Nonlinear Dynamics Yi ZhaoContents; 6.1. Introduction; 6.2. Model Structure; 6.3. Avoid Overfitting by Model Selection; 6.3.1. How it works; 6.3.2. Case study; A. Computational experiments; B. Experimental data; 6.4. Surrogate Data Method for Model Residual; 6.4.1. Linear surrogate data; 6.4.2. Systematic flowchart; 6.4.3. Identification of model residual; 6.4.4. Further investigation; 6.5. The Diploid Model Based on Neural Networks; 6.6. Conclusion; Acknowledgments; References 7. Solving Eigen-problems of Matrices by Neural Networks Yiguang Liu, Zhisheng You, Bingbing Liu and Jiliu Zhou
Record Nr.	UNINA-9910464980803321

Autore	Owens, Robert G.
Pubbl/distr/stampa	London : Imperial College Press, c2002
Descrizione fisica	XVII, 417 p. : ill. ; 27 cm
Altri autori (Persone)	Phillips, Timothy N.
Soggetto non controllato	Reologia computazionale
ISBN	1-86094-186-9
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-990008503540403321

Pubbl/distr/stampa	London, : Imperial College Press
Descrizione fisica	1 online resource (472 p.)
Disciplina	572.80285
Altri autori (Persone)	MarksteinPeter XuYing <1960->
Collana	Series on Advances in Bioinformatics and Computational Biology Series on advances in bioinformatics and computational biology
Soggetto topico	Bioinformatics Biological systems - Computer simulation Biological systems - Simulation methods Computational biology
Soggetto genere / forma	Electronic books.
ISBN	1-281-86759-4 9786611867591 1-86094-873-1
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	CONTENTS; Preface; Committees; Referees; Keynote Address; Quantitative Aspects of Gene Regulation in Bacteria: Amplification. Threshold, and Combinatorial Control Terry Hwa; Whole-Genome Analysis of Dorsal Gradient Thresholds in the Drosophila Embryo Julia ZeitlingeK Rob Zinzen, Dmitri Papatsenko et al.; Invited Talks; Learning Predictive Models of Gene Regulation Christina Leslie; The Phylofacts Phylogenomic Encyclopedias: Structural Phylogenomic Analysis Across the Tree of Life Kimmen Golander; Mapping and Analysis of the Human Interactome Network Kavitha Venkatesan; 1. INTRODUCTION Gene-Centered Protein-DNA lnteractome Mapping A.J. Marian WalhoutProteomics; Algorithm for Peptide Sequencing by Tandem Mass Spectrometry Based on Better Preprocessing and Anti-S ymmetric Computational Model Kang Ning and Hon Wai Leong; 1. INTRODUCTION; Preprocessing to remove noisy peaks; The anti-symmetric problem; 2. ANALYSIS OF PROBLEMS AND CURRENT ALGORITHMS; 2.1. General Terminologies; 2.2. Datasets; 2.3. Problems Analysis; 3. NEW COMPUTATIONAL MODELS AND ALGORITHM; 3.1. Preprocessing to remove noisy peaks and introduce pseudo peaks; 3.2. The Anti-symmetric Problem 3.3. Novel Peptide Sequencing Algorithm4. EXPERIMENTS; 4.1. Experiment Settings; 4.2. Results; 5. CONCLUSIONS; References; Algorithms for Selecting Breakpoint Locations to Optimize Diversity in Protein Engineering by Site-Directed Protein Recombination Wei Zheng, Xiaoduan Ye, Alan A4 Friedman and Chris Bailey-Kellogg; 1. INTRODUCTION; 2. METHODS; 2.1. Library Diversity; 2.2. Metrics for Breakpoint Selection; 2.3. Dynamic Programming for Breakpoint Selection; 3. RESULTS A N D DISCUSSION; 4. CONCLUSION; ACKNOWLEDGMENTS; References An Algorithmic Approach to Automated High-Throughput Identification of Disulfide Connectivity in Proteins Using Tandem Mass Spectrometry Timothy Lee, Rahul Singh, Ten-Yang Yen and Bruce Macher1. INTRODUCTION; 1.1. Comparison of the Proposed Approach with Related Works; 2. THE PROPOSED METHOD; 2.1. Problem Formulation; 2.2. Algorithmic Framework; 2.2.1. Finding the MS spectrum match; 2.2.2. Finding the MS/MS spectrum match; 2.2.3. Finding a perfect matching of maximum weight for a fully connected graph; 2.2.4. Consideration of missed proteolytic cleavages and intra-molecular bonded cysteines 2.2.5. Peak finding in the presence of noise2.2.6. Addressing isotopic variation and neutral loss; 2.2.7. Interpretation of peaks given charge state uncertainty; 2.2.8. Overall complexity; 3. EXPERIMENTAL RESULTS; 3.1. Description of the Data and Experimental Procedures; 3.2. Summary of Results; 3.2.1. Analysis of the effect of varying threshold t on results; 3.2.2. Comparison with MS2Assign program; 4. CONCLUSIONS AND DISCUSSION; Acknowledgments; References; Biomedical Application; Cancer Molecular Pattern Discovery by Subspace Consensus Kernel Classification Xiaoxu Hun; 1. INTRODUCTION 1 .1. Nonnegative matrix factorization
Record Nr.	UNINA-9910451116403321