LEADER 05610nam 22006855 450 001 9910254069403321 005 20200703053534.0 010 $a3-319-28095-3 024 7 $a10.1007/978-3-319-28095-0 035 $a(CKB)3710000000685924 035 $a(EBL)4530162 035 $a(DE-He213)978-3-319-28095-0 035 $a(MiAaPQ)EBC4530162 035 $a(PPN)194078698 035 $a(EXLCZ)993710000000685924 100 $a20160519d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSystem Engineering Approach to Planning Anticancer Therapies /$fby Andrzej ?wierniak, Marek Kimmel, Jaroslaw Smieja, Krzysztof Puszynski, Krzysztof Psiuk-Maksymowicz 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (241 p.) 300 $aDescription based upon print version of record. 311 $a3-319-28093-7 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aIntroduction -- Cell Cycle as an Object of Control -- Therapy Optimization in Population Dynamics Models -- Structured Models and Their Use in Modeling Anticancer Therapies -- Signaling Pathways Dynamics and Cancer Treatment -- Model Identification and Parameter Estimation -- Appendixes: Stability and Controllability of Dynamical Systems -- Pontryagin Maximum Principle and Optimal Control -- Bifurcation Analysis -- Numerical Implementation of the Runge Kutta and Gillespie Methods. 330 $aThis book focuses on the analysis of cancer dynamics and the mathematically based synthesis of anticancer therapy. It summarizes the current state-of-the-art in this field and clarifies common misconceptions about mathematical modeling in cancer. Additionally, it encourages closer cooperation between engineers, physicians and mathematicians by showing the clear benefits of this without stating unrealistic goals. Development of therapy protocols is realized from an engineering point of view, such as the search for a solution to a specific control-optimization problem. Since in the case of cancer patients, consecutive measurements providing information about the current state of the disease are not available, the control laws are derived for an open loop structure. Different forms of therapy are incorporated into the models, from chemotherapy and antiangiogenic therapy to immunotherapy and gene therapy, but the class of models introduced is broad enough to incorporate other forms of therapy as well. The book begins with an analysis of cell cycle control, moving on to control effects on cell population and structured models and finally the signaling pathways involved in carcinogenesis and their influence on therapy outcome. It also discusses the incorporation of intracellular processes using signaling pathway models, since the successful treatment of cancer based on analysis of intracellular processes, might soon be a reality. It brings together various aspects of modeling anticancer therapies, which until now have been distributed over a wide range of literature. Written for researchers and graduate students interested in the use of mathematical and engineering tools in biomedicine with special emphasis on applications in cancer diagnosis and treatment, this self-contained book can be easily understood with only a minimal basic knowledge of control and system engineering methods as well as the biology of cancer. Its interdisciplinary character and the authors? extensive experience in cooperating with clinicians and biologists make it interesting reading for researchers from control and system engineering looking for applications of their knowledge. Systems and molecular biologists as well as clinicians will also find new inspiration for their research. 606 $aBiomathematics 606 $aSystem theory 606 $aCancer research 606 $aCell cycle 606 $aDrug resistance 606 $aMathematical and Computational Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/M31000 606 $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070 606 $aCancer Research$3https://scigraph.springernature.com/ontologies/product-market-codes/B11001 606 $aCell Cycle Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/L16030 606 $aDrug Resistance$3https://scigraph.springernature.com/ontologies/product-market-codes/B16020 615 0$aBiomathematics. 615 0$aSystem theory. 615 0$aCancer research. 615 0$aCell cycle. 615 0$aDrug resistance. 615 14$aMathematical and Computational Biology. 615 24$aSystems Theory, Control. 615 24$aCancer Research. 615 24$aCell Cycle Analysis. 615 24$aDrug Resistance. 676 $a616.99406 700 $a?wierniak$b Andrzej$4aut$4http://id.loc.gov/vocabulary/relators/aut$0941784 702 $aKimmel$b Marek$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSmieja$b Jaroslaw$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aPuszynski$b Krzysztof$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aPsiuk-Maksymowicz$b Krzysztof$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910254069403321 996 $aSystem Engineering Approach to Planning Anticancer Therapies$92124858 997 $aUNINA