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The Resource Computer methods, Part B, edited by Michael L. Johnson, Ludwig Brand, (electronic resource)
Computer methods, Part B, edited by Michael L. Johnson, Ludwig Brand, (electronic resource)
Resource Information
The item Computer methods, Part B, edited by Michael L. Johnson, Ludwig Brand, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Computer methods, Part B, edited by Michael L. Johnson, Ludwig Brand, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 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
 Language

 eng
 eng
 Edition
 1st ed.
 Extent
 1 online resource (711 p.)
 Note
 Description based upon print version of record
 Contents

 Front Cover; Methods in Enzymology; Copyright; Contents; Contributors; Preface; Chapter 1: Correlation Analysis: A Tool for Comparing RelaxationType 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 HighContent 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 SelfRegulating 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 ThreeState TwoCycle Motor Protein; 5. PhosphorylationDephosphorylation 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. MonomerTetramer Model; 5. Summary; Acknowledgments; References; Chapter 7: Algebraic Models of Biochemical Networks; 1. Introduction; 2. Computational Systems Biology; 3. Network Inference; 4. ReverseEngineering of Discrete Models: An Example; 5. Discussion; References; Chapter 8: HighThroughput Computing in the Sciences; 1. What is an HTC Application?; 2. HTC Technologies; 3. HighThroughput 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: DynaFitA 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
 Isbn
 9780080962801
 Label
 Computer methods, Part B
 Title
 Computer methods
 Title number
 Part B
 Statement of responsibility
 edited by Michael L. Johnson, Ludwig Brand
 Language

 eng
 eng
 Summary
 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
 Cataloging source
 MiAaPQ
 Dewey number

 610.28
 610.727
 Illustrations
 illustrations
 Index
 index present
 Language note
 English
 LC call number
 R856
 LC item number
 .C66b 2009
 Literary form
 non fiction
 Nature of contents

 dictionaries
 bibliography
 http://library.link/vocab/relatedWorkOrContributorDate
 1947
 http://library.link/vocab/relatedWorkOrContributorName

 Johnson, Michael L.
 Brand, Ludwig
 Series statement
 Methods in enzymology
 Series volume
 467
 http://library.link/vocab/subjectName

 Biomedical engineering
 Bioengineering
 Label
 Computer methods, Part B, edited by Michael L. Johnson, Ludwig Brand, (electronic resource)
 Note
 Description based upon print version of record
 Bibliography note
 Includes bibliographical references and index
 Carrier category
 online resource
 Carrier category code

 cr
 Content category
 text
 Content type code

 txt
 Contents

 Front Cover; Methods in Enzymology; Copyright; Contents; Contributors; Preface; Chapter 1: Correlation Analysis: A Tool for Comparing RelaxationType 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 HighContent 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 SelfRegulating 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 ThreeState TwoCycle Motor Protein; 5. PhosphorylationDephosphorylation 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. MonomerTetramer Model; 5. Summary; Acknowledgments; References; Chapter 7: Algebraic Models of Biochemical Networks; 1. Introduction; 2. Computational Systems Biology; 3. Network Inference; 4. ReverseEngineering of Discrete Models: An Example; 5. Discussion; References; Chapter 8: HighThroughput Computing in the Sciences; 1. What is an HTC Application?; 2. HTC Technologies; 3. HighThroughput 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: DynaFitA 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
 Dimensions
 unknown
 Edition
 1st ed.
 Extent
 1 online resource (711 p.)
 Form of item
 online
 Isbn
 9780080962801
 Media category
 computer
 Media type code

 c
 Specific material designation
 remote
 System control number

 (EBL)631960
 (OCoLC)700703770
 (SSID)ssj0000492668
 (PQKBManifestationID)12121925
 (PQKBTitleCode)TC0000492668
 (PQKBWorkID)10500113
 (PQKB)11391970
 (MiAaPQ)EBC631960
 (EXLCZ)992500000000003177
 Label
 Computer methods, Part B, edited by Michael L. Johnson, Ludwig Brand, (electronic resource)
 Note
 Description based upon print version of record
 Bibliography note
 Includes bibliographical references and index
 Carrier category
 online resource
 Carrier category code

 cr
 Content category
 text
 Content type code

 txt
 Contents

 Front Cover; Methods in Enzymology; Copyright; Contents; Contributors; Preface; Chapter 1: Correlation Analysis: A Tool for Comparing RelaxationType 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 HighContent 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 SelfRegulating 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 ThreeState TwoCycle Motor Protein; 5. PhosphorylationDephosphorylation 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. MonomerTetramer Model; 5. Summary; Acknowledgments; References; Chapter 7: Algebraic Models of Biochemical Networks; 1. Introduction; 2. Computational Systems Biology; 3. Network Inference; 4. ReverseEngineering of Discrete Models: An Example; 5. Discussion; References; Chapter 8: HighThroughput Computing in the Sciences; 1. What is an HTC Application?; 2. HTC Technologies; 3. HighThroughput 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: DynaFitA 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
 Dimensions
 unknown
 Edition
 1st ed.
 Extent
 1 online resource (711 p.)
 Form of item
 online
 Isbn
 9780080962801
 Media category
 computer
 Media type code

 c
 Specific material designation
 remote
 System control number

 (EBL)631960
 (OCoLC)700703770
 (SSID)ssj0000492668
 (PQKBManifestationID)12121925
 (PQKBTitleCode)TC0000492668
 (PQKBWorkID)10500113
 (PQKB)11391970
 (MiAaPQ)EBC631960
 (EXLCZ)992500000000003177
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