BIOMAT 2007 : International Symposium on Mathematical and Computational Biology, Armacao dos Buzios, Rio de Janeiro, Brazil, 24-29 Novermber 2007 / edited by Rubem P Mondaini, Rui Dilao.

Format:

Book

Conference/Event

Contributor:

Dilão, Rui.

Mondaini, Rubem P.

Conference Name:

International Symposium on Mathematical and Computational Biology (2007 : Rio de Janeiro, Brazil)

International Symposium on Mathematical and Computational Biology

Language:

English

Subjects (All):

Biology--Mathematical models--Congresses.

Biology.

Biomathematics--Congresses.

Biomathematics.

Physical Description:

1 online resource (400 p.)

Place of Publication:

Hackensack, NJ : World Scientific, c2008.

Language Note:

English

Summary:

The present volume contains the contributions of the keynote speakers of the BIOMAT 2007 Symposium as well as selected contributed papers in the areas of mathematical biology, biological physics, biophysics and bioinformatics. It contains new results on some aspects of Lotka-Volterra equations, the proposal of using differential geometry to model neurosurgical tools, recent data on epidemiological modeling, pattern recognition and comprehensive reviews on the structure of proteins, the folding problem and the influence of Allee effects on population dynamics.This book contains some original re

Contents:

CONTENTS; Preface; Editorial Board of the BIOMAT Consortium; Protein Structure and Function; Systems Protein folding as a physical stochastic process. Kerson Huang; 1. Introduction; 2. Protein Basics; 2.1. The protein chain; 2.2. Secondary and tertiary structures; 2.3. Hydrophobic effect; 2.4. Folding stages; 2.5. Statistical nature of the folding process; 3. Stochastic Process; 3.1. Stochastic variable; 3.2. Brownian motion; 3.3. Monte Carlo; 4. CSAW; 5. Implementation of CSAW; 6. Exploratory Runs; 7. Folding Pathways and Energy Landscape; 8. Nucleation and Growth of an Alpha Helix

9. All-atom Model10. Discussion and Outlook; References; Optimal methods for re-ordering data matrices in systems biology and drug discovery applications. Peter A. DiMaggio Jr., Scott R. McAllister, Christodoulos A. Floudas, Xiao-Jiang Feng, Joshua D. Rabinowitz, Herschel A. Rabitz; 1. Introduction; 2. Mathematical Models; 2.1. Variable Definitions for Re-ordering; 2.2. Objective Functions; 2.3. Models for Optimal Re-ordering; 2.3.1. Network Flow Model: Dense Data Matrices; 2.3.2. TSP Model: Dense Data Matrices; 2.3.3. Assignment Problem Model: Sparse Data Matrices

2.4. Iterative Framework for Biclustering Dense Data3. Results and Discussion; 3.1. Metabolite Concentration Data: Dense Data Matrix; 3.1.1. Results for Other Biclustering Algorithms; 3.2. Colon Cancer Data: Dense Data Matrix; 3.3. Percent Inhibition Data: Sparse Data Matrix; 3.3.1. Iterative Synthesis Strategy; 4. Conclusions; Acknowledgements; References; The solution of the distance geometry problem in protein modeling via geometric buildup. Di Wu, Zhijun Wu, Yaxiang Yuan; 1. Distance Based Protein Modeling; 2. The Distance Geometry Problem; 2.1. Problems with Exact Distances

2.2. Problems with Sparse Distances2.3. Problems with Inexact Distances; 3. The Geometric Buildup Approach; 3.1. The General Algorithm; 3.2. Control of Numerical Errors; 3.3. Rigid vs. Unique Buildup; 3.4. Tolerance of Inexact Distances; 4. Concluding Remarks; Acknowledgments; References; The differential geometry of proteins and its applications to structure determination. Alain Goriely, Andrew Hausrath, Sebastien Neukirch; 1. Introduction; 2. Methods; 2.1. Curvatures to curve; 2.2. Curves from atomic models; 2.3. Atomic models from curves; 2.4. Polyhelices; 2.5. Embedding methods

3. Fold Space Exploration3.1. Protein Quality Functions; 3.2. The fold spaces of polyhelices; 3.3. Modeling helical bundle and -barrel membrane proteins; 4. Protein Design; 4.1. Creation of structure specification and optimization tools; 5. Continuum Mechanics of Biological Structures; 5.1. Continuum elastic theory of coiled-coils; 5.2. Modeling the open and closed states of the CusCFBA bacterial efflux complex; 5.3. Modeling oligomerization states of Adiponectin; 6. Conclusions; Acknowledgments; References; Modeling Physiological Disorders

Mathematical and computational modeling of physiological disorders: A case study of the IUPS human physiome project and aneurysmal models. Alexander R. Oshmyansky, Philip K. Maini

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

9786611960926

9781281960924

1281960926

9789812812339

9812812334