Handbook of cancer models with applications:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific
2008
|
| Schriftenreihe: | Series in mathematical biology and medicine
9 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XXIV, 567 S. Ill., graph. Darst. |
| ISBN: | 9812779477 9789812779472 |
Internformat
MARC
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|---|---|---|---|
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| 007 | t | ||
| 008 | 090305s2008 si ad|| |||| 00||| eng d | ||
| 010 | |a 2008276488 | ||
| 020 | |a 9812779477 |9 981-277-947-7 | ||
| 020 | |a 9789812779472 |9 978-981-277-947-2 | ||
| 035 | |a (OCoLC)191658529 | ||
| 035 | |a (DE-599)BVBBV035348409 | ||
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| 245 | 1 | 0 | |a Handbook of cancer models with applications |c ed. by Wai-Yuan Tan ... |
| 264 | 1 | |a Singapore |b World Scientific |c 2008 | |
| 300 | |a XXIV, 567 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Series in mathematical biology and medicine |v 9 | |
| 500 | |a Includes bibliographical references and index | ||
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Cancer |x Mathematical models | |
| 650 | 4 | |a Cancer |x Computer simulation | |
| 650 | 0 | 7 | |a Krebs |g Medizin |0 (DE-588)4073781-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Mathematisches Modell |0 (DE-588)4114528-8 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Krebs |g Medizin |0 (DE-588)4073781-0 |D s |
| 689 | 0 | 1 | |a Mathematisches Modell |0 (DE-588)4114528-8 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Tan, Wai-Yuan |e Sonstige |4 oth | |
| 830 | 0 | |a Series in mathematical biology and medicine |v 9 |w (DE-604)BV011085890 |9 9 | |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017152600&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-017152600 | ||
Datensatz im Suchindex
| _version_ | 1804138667859509248 |
|---|---|
| adam_text | CONTENTS
Contributors
xvii
Preface
xxiii
1.
Oncogenetic Trees
1
Aniko Szabo and Kenneth M. Boucher
1.
Introduction
......................... 1
2.
Definitions and Basic Results
................ 2
2.1.
Description of the Data
............... 2
2.2.
The Oncogenetic Tree Model
............ 3
2.2.1.
Error model
................ 5
3.
Reconstruction
....................... 5
4.
Sample Size Estimation
................... 11
5.
Parameter Estimation
.................... 13
6.
Example: Renal Carcinoma Development
......... 14
7.
Properties of the Oncogenetic Tree Estimator:
A Simulation Study
..................... 15
7.1.
Simulating Data Based on a Given Tree
...... 16
7.2.
Probability of Correct Reconstruction
....... 16
7.3.
Sample Size for High Probability of Reconstruction
17
8.
Goodness of Fit
....................... 19
8.1.
Bootstrap Estimate of Reconstruction Confidence
. 19
8.2.
Analysis of the Stable Portions
........... 19
9.
Discussion
......................... 22
References
............................ 23
rá
Contents
2.
Stochastic Multistage Cancer Models: A Fresh Look
at an Old Approach
25
Qi Zheng
1.
Introduction
......................... 25
2.
Basic Definitions and Notation
............... 26
3.
Mathematical Details
.................... 32
4.
Concluding Remarks
.................... 41
Acknowledgments
........................ 42
References
............................ 42
3.
Cancer Biology, Cancer Models and Some New
Approaches to Carcinogenesis
45
Wai
Y. Tan, Chao
W.
Chen and Li J. Zhang
1.
Introduction
......................... 45
2.
Some Recent Cancer Biology for Modeling
Carcinogenesis
....................... 47
2.1.
The Multi-Staging Nature of Carcinogenesis
.... 49
2.2.
The Sequential Nature
............... 50
2.3.
The Genetic Changes and Cancer Genes
...... 53
2.4.
Cell Cycle and Carcinogenesis
........... 55
2.5.
Epigenetic and Cancer
............... 57
2.6.
Telomere, Immortalization and Cancer
....... 60
2.7.
Single Pathway versus Multiple Pathways
of Carcinogenesis
.................. 61
3.
Some General Stochastic Models of Carcinogenesis
. ... 64
3.1.
The Extended Multi-Event Model of
Carcinogenesis
................... 64
3.2.
The Mixed Models of Carcinogenesis
....... 65
4.
Some New Approaches for Analyzing Stochastic
Models of Carcinogenesis
................. 66
4.1.
Stochastic Differential Equations
.......... 67
4.2.
The Probability Distribution of T(f)
......... 69
4.3.
Probability Distribution of the State Variables
... 69
Contents
vii
5.
A State
Space Model for the Extended Multi-Event
Model of Carcinogenesis
.................. 70
5.1.
The Stochastic System Model, the Augmented State
Variables and Probability Distribution
....... 71
5.2.
The Observation Model and the Probability
Distribution of Cancer Incidence
.......... 72
5.3.
The Posterior Distribution of the Unknown
Parameters and State Variables
........... 74
5.4.
The Generalized Bayesian Method for Estimating
Unknown Parameters and State Variables
..... 75
6.
Analysis of British Physician Data of Lung Cancer
and Smoking
........................ 76
7.
Conclusions and Summary
................. 83
Acknowledgments
........................ 83
References
............................ 84
4.
Modeling the Effects of Radiation on Cell Cycle
Regulation and Carcinogenesis
91
William D. Hazelton
1.
Introduction
......................... 92
1.1.
Multistage Carcinogenesis Models
......... 92
1.2.
Analyses of Environmentally Exposed Cohorts
. . 93
2.
Modeling Biological Mechanisms
............. 95
2.1.
A Combined Cell Cycle and Multistage Clonal
Expansion Model
.................. 95
3.
Summary
.......................... 102
Acknowledgments
........................ 103
References
............................ 103
Appendix
............................. 104
5.
Cancer Models, Ionizing Radiation, and Genomic
Instability: A Review
109
Mark P. Little
1.
Introduction
......................... 109
2.
Annitage-Doll Multi-Stage Model
............. 113
ущ
Contents
3.
Two-Mutation Model
.................... 119
4.
Generalized MVK and Multi-Stage Models
........ 123
5.
Multiple Pathway Models
................. 128
5.1.
Multiple Pathway Models Incorporating
Genomic Instability
................. 129
6.
Discussion and Conclusions
................ 133
Acknowledgments
........................ 138
References
............................ 138
6.
Distribution of the Sizes of
Métastases:
Mathematical
and
Biomedical
Considerations
149
Leonid
Hanin
1.
Introduction
......................... 149
2.
The Model
......................... 155
2.1.
Tumor Latency
................... 155
2.2.
Primary Tumor Growth
............... 155
2.3.
Metastasis Formation
................ 155
2.4.
Timeline of the Natural History of Metastatic
Cancer and
Observables
............... 156
2.5.
Secondary Metastasis
................ 157
2.6.
Metastasis Growth
................. 157
2.7.
Metastasis Detection
................ 158
2.8.
Effects of Treatment
................. 158
3.
Distribution of the Sizes of Detectable
Métastases
..... 158
4.
Distribution of the Sizes of Detectable
Métastases
for Exponentially Growing Tumors
............ 162
4.1.
Model Specification and Results
.......... 162
4.2.
Model Identification
................. 165
Acknowledgments
........................ 167
References
............................ 168
7.
Mathematical Models of Cancer and their Relevant Insights
173
Evans Afenya
1.
Introduction
.........................173
2.
Cancer Models
....................... 176
Contents ix
2.1. Models
of Leukemia
................ 177
2.2.
Cell Kinetics
.................... 195
3.
Cancer Treatment Models
................. 200
3.1.
Optimal Control Models
.............. 201
4.
Parameter Estimation
.................... 210
5.
Concluding Remarks
.................... 211
References
............................ 213
8.
Major Epigenetic Hypotheses of Carcinogenesis Revisited
225
King-Thom Chung
1.
Introduction
......................... 226
2.
Why are Epigenetic Factors Important?
.......... 230
3.
The Warburg s Hypothesis
................. 232
4.
The Linus Pauling Hypothesis: Vitamin
С
and Cancer
. . . 233
5.
Szent-Györgyi (Bioelectronic)
Hypothesis
......... 236
6.
Micronutrients and Cancer
................. 238
7.
NAD Deficiency as a Factor in Carcinogenesis
...... 242
8.
GAP Junction Intercellular Communication (GJIC)
and Cancer
......................... 251
9.
Viral Infections and Cancer
................. 254
10.
Other Epigenetic Hypotheses
................ 259
11.
Concluding Remarks and Perspectives
........... 262
Acknowledgments
........................ 265
References
............................ 266
9.
Induction and Repair of
DNA
Damage Formed
by Energetic Electrons and Light Ions
291
Robert
D
.
Stewart and Vladimir A. Semenenko
1.
Dosimetrie
Quantities and Units
.............. 291
1.1.
Absorbed Dose
................... 291
1.2.
Linear Energy Transfer (LET)
........... 292
1.3.
Microdosimetry
................... 294
2.
Induction of
DNA
Damage
................. 297
2.1.
Classification of
DNA
Damage
........... 297
2.2.
Mechanisms
..................... 297
2.3.
Initial Yield and Characteristics
........... 300
x
Contents
3.
Repair of Base Damage
and Single-Strand Breaks
.....303
3.1.
Mechanisms
.....................303
3.2.
Excision Repair Outcomes and Kinetics
......304
3.3.
Point Mutations Arising from Base Damage
and Single-Strand Breaks
..............307
4.
Repair of Double-Strand Breaks
..............308
4.1.
Mechanisms
.....................308
4.2.
Repair Kinetics, Chromosome Aberrations
and Small-Scale Mutations
............. 310
Acknowledgments
........................ 314
References
............................ 314
Appendix
............................. 319
10.
Radiation-Induced Bystander Effects
323
Linda C. DeVeaux
1.
Bystander Effects
......................323
1.1.
Introduction
..................... 323
1.2.
Definition of Bystander Effects
........... 325
1.3.
History of Bystander Effects
............ 326
1.4.
Bystander
Endpoints................ 328
1.5.
Transmission of Signal
............... 330
1.6.
Identification of Signal
............... 331
1.7.
Status of Sending and Receiving Cells
....... 333
1.8.
Dependence on Radiation Type
........... 335
1.9.
Bystander Effects and Cancer Risk
......... 336
1.10.
Evolutionary Considerations of Bystander Effects
. 336
2.
Summary
.......................... 338
Acknowledgments
........................ 338
References
............................ 338
11.
A Stochastic Model of Human Colon Cancer Involving
Multiple Pathways
345
Wai Y. Tan, Li J. Zhang,
Chao
W.
Chen and J. M. Zhu
1.
Introduction
.........................345
2.
A Brief Summary of Colon Cancer Biology
........347
Contents xi
2.1. The LOH
Pathway of Human Colon Cancer
(The
APC-ß -
Catenin
-
Tcf
-
myc
Pathway)
. . 347
2.2.
The MSI (Micro-Satellite Instability) Pathway
of Human Colon Cancer
.............. 349
3.
The Stochastic
Mul
ti-Stage Model of Carcinogenesis
. . . 352
3.1.
Stochastic Equations of State Variables
....... 353
3.2.
The Expected Number of Ij(t)
........... 354
3.3.
The Probability Distribution of the Number
of Detectable Tumors
................ 355
4.
A Statistical Model and the Probability Distribution
of Cancer Incidence Data
.................. 356
4.1.
Data Augmentation and the Expanded Model
... 358
4.2.
The Genetic Parameters
............... 359
5.
The State Space Model and the Generalized Bayesian
Approach for Estimating the Unknown Parameters
.... 361
5.1.
The Prior Distribution of the Parameters
...... 361
5.2.
The Posterior Distribution of the Parameters
Given {Y,Z}
..................... 362
5.3.
The Multi-Level Gibbs Sampling Procedure
for Estimating Parameters
.............. 363
5.4.
The Genetic Algorithm
............... 364
6.
Application and Results
................... 364
7.
Conclusions and Discussion
................ 370
Acknowledgments
........................ 371
References
............................ 371
12.
Cancer Risk Assessment of Environmental Agents by
Stochastic and State Space Models of Carcinogenesis
375
Wai
Y. Tan, Chao
W.
Chen and Li J. Zhang
1.
Introduction
......................... 375
2.
A General Stochastic Model of Carcinogenesis
...... 377
2.1.
The Stochastic Difference Equations for State
Variables
....................... 380
2.2.
The Probability of Developing Cancer Tumors
... 381
2.3.
Probability Distribution of the State Variables
... 381
3.
The Data for Risk Assessment of Environmental Agents
. 382
xjj Contents
4.
State Space Models of Carcinogenesis and the Prediction
of State Variables
......................383
5.
A State Space Model for Cancer Risk Assessment
.....384
5.1.
The Stochastic System Model and Probability
Distributions
....................384
5.2.
The Observation Model
...............385
6.
The Genetic Algorithm and the Predicted Inference
Procedures
.........................386
6.1.
The Genetic Algorithm
...............386
6.2.
The Predictive Inference Procedures
........387
7.
Developing Confidence Intervals for Probabilities
of Developing Cancer by Genetic Algorithm
........388
8.
Developing Dose-Response Curves of Environmental
Agents by Genetic Algorithm
................388
9.
An Application and Illustration
...............389
10.
Conclusions
.........................394
Acknowledgments
........................394
References
............................394
13.
Stochastic Models for Preneoplastic Lesions and Their
Application for Cancer Risk Assessment
397
Annette
Kopp-Schneider,
Iris
Burkholder, Jutta Groos
and
Lutz Edler
1.
Introduction
.........................397
2.
Modeling Preneoplastic Lesions
..............401
2.1.
The Multistage Model with Clonal Expansion
of Intermediate Cells
................401
2.2.
A Geometric Model for Colonies of Intermediate
Cells
.........................405
2.3.
Comparison of Multistage and Color-Shift Model
. 406
3.
Application of Carcinogenesis Models to Preneoplastic
Lesion Data
.........................408
3.1.
Mouse Skin Carcinogenesis: Testing Biological
Hypotheses about Papilloma and Carcinoma
Formation
......................408
Contents xiii
3.2.
Liver Focal Lesion Data: Testing Hypotheses about
FAH
Formation and Phenotype Change
...... 411
3.3.
Liver Focal Lesion Data: Dose-Response Analyses
412
4.
Discussion
......................... 416
Acknowledgments
........................ 418
References
............................ 418
Appendix A: Basic Ideas of the Color-Shift Model
....... 422
Appendix B: Likelihood Functions
................ 423
Appendix
B(l):
Likelihood Function for Skin Papilloma
and Carcinoma Data
................ 423
Appendix
В
(2):
Likelihood Function for Liver
Focal Lesion Data
.................. 424
14.
Drug Resistance in Cancer Models
425
Jarosław
Smieja
1.
Introduction
......................... 425
2.
Biological Background
................... 426
3.
Preliminaries for Mathematical Models
.......... 429
4.
Drug Resistance and a Single Chemotherapeutic Agent
. . 431
4.1.
A Simple, Two-Compartmental Model
....... 431
4.2.
Evolution of Drug Resistance Stemming
from Gene Amplification
.............. 434
4.3.
Partial Sensitivity of the Resistant
Subpopulation
. 439
4.4.
Phase-Specific Chemotherapy
........... 440
4.5.
General Compartrnental Model
........... 442
5.
Multidrag Therapy and Drag Resistance
.......... 447
5.1.
A Two-Compartmental Model
........... 448
5.2.
A Four-Compartmental Model
........... 448
6.
Concluding Remarks
.................... 449
Acknowledgments
........................ 451
References
............................ 452
15.
Bladder Cancer Screening by Magnetic Resonance Imaging
457
Lihong Li, Zigang Wang and Zhengrong Liang
1.
Introduction
......................... 458
јцУ
Contents
2.
Methods
...........................
459
2.1.
MR Image Protocols
................ 459
2.2.
Image Segmentation
................ 461
2.3.
Interactive Visualization System
.......... 462
2.4.
Detection of Bladder Lesions
............ 463
3.
Results
........................... 465
4.
Discussion and Conclusions
................ 466
Acknowledgments
........................ 467
References
............................ 468
16.
Mathematical Framework and Wavelets Applications
in Proteomics for Cancer Study
471
Don Hong and Yu Shyr
1.
Introduction
.........................471
2.
Mathematical Representation and Preprocessing
of MaldiMSData
...................... 475
2.1.
Mathematical Model for MALDI-TOF MS Data
.. 476
2.1.1.
Baseline correction and normalization
. . 479
2.1.2.
Spectra registration and peak alignment
. 480
3.
Multiscale Tools
...................... 482
3.1.
Wavelets and WaveSpec Software
......... 483
3.2.
Diffusion Maps
................... 488
4.
Clustering and Cancer Data Classifications
........ 489
Acknowledgments
........................ 496
References
............................ 496
17.
Advanced Statistical Methods for the Design and
Analysis of Tumor Xenograft Experiments
501
Ming Tan and Hong-Bin Fang
1.
Introduction
.........................502
2.
Design of Experiments for Combination Studies
......504
2.1.
Fixed-Ratio Design and Ray Design
........ 506
2.2.
Abdelbasit-Plackett Optimal Experimental Design
. 506
2.3.
Uniform Experimental Design
........... 507
3.
Statistical Analysis for Tumor Growth
........... 509
Contents xv
3.1.
Statistical
Models.................. 510
3.2. Parameter
Estimation via the ECM Algorithm
. . . 512
4.
Comparison of Treatment Effects
.............. 514
4.1.
Quasi
ŕ-Test
Based on the EM Algorithm
...... 515
4.2.
BayesianTest
.................... 516
5.
Summary and Discussion
.................. 516
Acknowledgments
........................ 518
References
............................ 518
18.
Analysis of Occult Tumor Studies
521
SheshN.Rai
1.
Introduction
......................... 521
2.
A Review of the Literature
................. 523
3.
Preliminary Considerations
................. 527
3.1.
Constructing the Likelihood Function
....... 530
3.2.
Non-Parametric Settings
.............. 531
3.3.
Fitting the Semi-Parametric Model
......... 534
4.
Interval Estimation
..................... 539
5.
Testing Tumor Lethality and Carcinogenic Effect
..... 543
6.
Two Examples
....................... 546
7.
Discussion
......................... 556
References
............................ 560
Index
563
|
| any_adam_object | 1 |
| building | Verbundindex |
| bvnumber | BV035348409 |
| callnumber-first | R - Medicine |
| callnumber-label | RC267 |
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| callnumber-subject | RC - Internal Medicine |
| classification_rvk | XH 1500 |
| ctrlnum | (OCoLC)191658529 (DE-599)BVBBV035348409 |
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| id | DE-604.BV035348409 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:31:50Z |
| institution | BVB |
| isbn | 9812779477 9789812779472 |
| language | English |
| lccn | 2008276488 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017152600 |
| oclc_num | 191658529 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR |
| owner_facet | DE-355 DE-BY-UBR |
| physical | XXIV, 567 S. Ill., graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | World Scientific |
| record_format | marc |
| series | Series in mathematical biology and medicine |
| series2 | Series in mathematical biology and medicine |
| spelling | Handbook of cancer models with applications ed. by Wai-Yuan Tan ... Singapore World Scientific 2008 XXIV, 567 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Series in mathematical biology and medicine 9 Includes bibliographical references and index Mathematisches Modell Cancer Mathematical models Cancer Computer simulation Krebs Medizin (DE-588)4073781-0 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Krebs Medizin (DE-588)4073781-0 s Mathematisches Modell (DE-588)4114528-8 s DE-604 Tan, Wai-Yuan Sonstige oth Series in mathematical biology and medicine 9 (DE-604)BV011085890 9 Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017152600&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Handbook of cancer models with applications Series in mathematical biology and medicine Mathematisches Modell Cancer Mathematical models Cancer Computer simulation Krebs Medizin (DE-588)4073781-0 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| subject_GND | (DE-588)4073781-0 (DE-588)4114528-8 |
| title | Handbook of cancer models with applications |
| title_auth | Handbook of cancer models with applications |
| title_exact_search | Handbook of cancer models with applications |
| title_full | Handbook of cancer models with applications ed. by Wai-Yuan Tan ... |
| title_fullStr | Handbook of cancer models with applications ed. by Wai-Yuan Tan ... |
| title_full_unstemmed | Handbook of cancer models with applications ed. by Wai-Yuan Tan ... |
| title_short | Handbook of cancer models with applications |
| title_sort | handbook of cancer models with applications |
| topic | Mathematisches Modell Cancer Mathematical models Cancer Computer simulation Krebs Medizin (DE-588)4073781-0 gnd Mathematisches Modell (DE-588)4114528-8 gnd |
| topic_facet | Mathematisches Modell Cancer Mathematical models Cancer Computer simulation Krebs Medizin |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017152600&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV011085890 |
| work_keys_str_mv | AT tanwaiyuan handbookofcancermodelswithapplications |