UID:
almafu_9958131492402883
Umfang:
1 online resource (711 p.)
Ausgabe:
1st ed.
ISBN:
9786612699801
,
9781282699809
,
1282699806
,
9780080962801
,
0080962807
Serie:
Methods in enzymology ; 467
Inhalt:
The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with previous and forthcoming Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to
Anmerkung:
Description based upon print version of record.
,
Front Cover; Methods in Enzymology; Copyright; Contents; Contributors; Preface; Chapter 1: Correlation Analysis: A Tool for Comparing Relaxation-Type Models to Experimental Data; 1. Introduction; 2. Scatter Plots and Correlation Analysis; 3. Example 1: Relaxation Oscillations; 4. Example 2: Square Wave Bursting; 5. Example 3: Elliptic Bursting; 6. Example 4: Using Correlation Analysis on Experimental Data; 7. Summary; Appendix: Algorithm for the Determination of Phase Durations During Bursting; Acknowledgment; References
,
Chapter 2: Trait Variability of Cancer Cells Quantified by High-Content Automated Microscopy of Single Cells1. Introduction; 2. Background; 3. Experimental and Computational Workflow; 4. Application to Traits Relevant to Cancer Progression; 5. Conclusions; Acknowledgments; References; Chapter 3: Matrix Factorization for Recovery of Biological Processes from Microarray Data; 1. Introduction; 2. Overview of Methods; 3. Application to the Rosetta Compendium; 4. Results of Analyses; 5. Discussion; References; Chapter 4: Modeling and Simulation of the Immune System as a Self-Regulating Network
,
1. Introduction2. Mathematical Modeling of the Immune Network; 3. Two Examples of Models to Understand T Cell Regulation; 4. How to Implement Mathematical Models in Computer Simulations; 5. Concluding Remarks; Acknowledgments; References; Chapter 5: Entropy Demystified: The ""Thermo""-dynamics of Stochastically Fluctuating Systems; 1. Introduction; 2. Energy; 3. Entropy and ""Thermo""-dynamics of Markov Processes; 4. A Three-State Two-Cycle Motor Protein; 5. Phosphorylation-Dephosphorylation Cycle Kinetics; 6. Summary and Challenges; References
,
Chapter 6: Effect of Kinetics on Sedimentation Velocity Profiles and the Role of Intermediates1. Introduction; 2. Methods; 3. ABCD Systems; 4. Monomer-Tetramer Model; 5. Summary; Acknowledgments; References; Chapter 7: Algebraic Models of Biochemical Networks; 1. Introduction; 2. Computational Systems Biology; 3. Network Inference; 4. Reverse-Engineering of Discrete Models: An Example; 5. Discussion; References; Chapter 8: High-Throughput Computing in the Sciences; 1. What is an HTC Application?; 2. HTC Technologies; 3. High-Throughput Computing Examples; 4. Advanced Topics; 5. Summary
,
ReferencesChapter 9: Large Scale Transcriptome Data Integration Across Multiple Tissues to Decipher Stem Cell Signatures; 1. Introduction; 2. Systems and Data Sources; 3. Data Integration; 4. Artificial Neural Network Training and Validation; 5. Future Development and Enhancement Plans; Acknowledgments; References; Chapter 10: DynaFit-A Software Package for Enzymology; 1. Introduction; 2.Equilibrium Binding Studies; 3. Initial Rates of Enzyme Reactions; 4. Time Course of Enzyme Reactions; 5. General Methods and Algorithms; 6. Concluding Remarks; Acknowledgments; References
,
Chapter 11: Discrete Dynamic Modeling of Cellular Signaling Networks
,
English
Weitere Ausg.:
ISBN 9780123750235
Weitere Ausg.:
ISBN 0123750237
Sprache:
Englisch
Bookmarklink
