Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Mathematical Modeling And Computational Predictions In Oncoimmunology
Download Mathematical Modeling And Computational Predictions In Oncoimmunology full books in PDF, epub, and Kindle. Read online Mathematical Modeling And Computational Predictions In Oncoimmunology ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Mathematical Modeling and Computational Predictions in Oncoimmunology by : Vladimir A. Kuznetsov
Download or read book Mathematical Modeling and Computational Predictions in Oncoimmunology written by Vladimir A. Kuznetsov and published by Frontiers Media SA. This book was released on 2024-06-06 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is a complex adaptive dynamic system that causes both local and systemic failures in the patient. Cancer is caused by a number of gain-of-function and loss-of-function events, that lead to cells proliferating without control by the host organism over time. In cancer, the immune system modulates cancer cell population heterogeneity and plays a crucial role in disease outcomes. The immune system itself also generates multiple clones of different cell types, with some clones proliferating quickly and maturing into effector cells. By creating regulatory signals and their networks, and generating effector cells and molecules, the immune system recognizes and kills abnormal cells. Anti-cancer immune mechanisms are realized as multi-layer, nonlinear cellular and molecular interactions. A number of factors determine the outcome of immune system-tumor interactions, including cancer-associated antigens, immune cells, and host organisms.
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by Springer Nature. This book was released on 2021-12-11 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Symposium on Mathematical and Computational Oncology, ISMCO 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 3 full papers and 4 short papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; spatio-temporal tumor modeling and simulation; general cancer computational biology; mathematical modeling for cancer research; computational methods for anticancer drug development.
Book Synopsis Mathematical and Computational Studies on Progress, Prognosis, Prevention and Panacea of Breast Cancer by : Suhrit Dey
Download or read book Mathematical and Computational Studies on Progress, Prognosis, Prevention and Panacea of Breast Cancer written by Suhrit Dey and published by Springer Nature. This book was released on 2022-03-25 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book’s aim is to study the mathematical and computational models to analyze the progress, prognosis, prevention, and panacea of breast cancer. The book discusses application of Markov chains and transient mappings, Charlie–Simpson numerical algorithm, models represented by nonlinear reaction–diffusion-type partial differential equations, and related techniques. The book also attempts to design mathematical model of targeted strategic treatments by using Skilled Killer Drugs (SKD1 and SKD2) to suggest the improvisation of future cancer treatments. Both graduate students and researchers of computational biology and oncologists will benefit by studying this book. Researchers of cancer studies and biological sciences will also find this work helpful.
Book Synopsis Computational Mathematics Modeling in Cancer Analysis by : Wenjian Qin
Download or read book Computational Mathematics Modeling in Cancer Analysis written by Wenjian Qin and published by Springer Nature. This book was released on 2023-10-07 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 14243 constitutes the refereed proceedings of the Second International Workshop, CMMCA 2023, Held in Conjunction with MICCAI 2023, on October 8, 2023, in Vancouver, BC, Canada. The 17 full papers presented were carefully reviewed and selected from 25 submissions. The conference focuses on the discovery of cutting-edge techniques addressing trends and challenges in theoretical, computational, and applied aspects of mathematical cancer data analysis.
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Symposium on Mathematical and Computational Oncology, ISMCO 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 3 full papers and 4 short papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; spatio-temporal tumor modeling and simulation; general cancer computational biology; mathematical modeling for cancer research; computational methods for anticancer drug development.
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by Springer Nature. This book was released on 2020-12-07 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Symposium on Mathematical and Computational Oncology, ISMCO 2020, which was supposed to be held in San Diego, CA, USA, in October 2020, but was instead held virtually due to the COVID-19 pandemic. The 6 full papers and 4 short papers presented together with 1 invited talk were carefully reviewed and selected from 28 submissions. The papers are organized in topical sections named: statistical and machine learning methods for cancer research; mathematical modeling for cancer research; general cancer computational biology; and posters.
Book Synopsis Computational Mathematics Modeling in Cancer Analysis by : Wenjian Qin
Download or read book Computational Mathematics Modeling in Cancer Analysis written by Wenjian Qin and published by Springer Nature. This book was released on 2022-09-22 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.
Book Synopsis An Integrated Approach to Model Cancer Cell Growth and Treatment Response with Multimodal Data Sources by : Kaitlyn Elizabeth Johnson
Download or read book An Integrated Approach to Model Cancer Cell Growth and Treatment Response with Multimodal Data Sources written by Kaitlyn Elizabeth Johnson and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical modeling and computational biology have been used to understand, describe, and predict critical behaviors of cancer progression. Recent technological advancements in the acquisition of single cell resolution data by high-throughput micrographic imaging and by single cell genomics now enable new analyses of cancer cells at the individual cell and cell population levels. This dissertation focuses on the development of math modeling frameworks capable of integrating and improving our utilization of these novel data types. First, we investigate the relevance of deviations from the conventional exponential growth model via an ecological principle known as the Allee effect, in which cancer cells exhibit cooperative growth dynamics at low population densities relevant in tumor initiation and metastases. Using a large number of single cell resolution growth trajectories acquired at low cell densities, we apply a stochastic parameter estimation framework to systematically evaluate the relevance of an Allee effect in a controlled experimental setting. Our findings reveal evidence for cooperative growth even in the presence of optimal space and nutrients, giving us motivation to consider Allee effects in making predictions regarding treatment response and tumor initiation. The remainder of our work focuses on utilizing multimodal data sources to better understand the dynamics of resistance to chemotherapy. We utilize a mathematical model describing the effects of a treatment-induced resistance on a population of cancer cells and seek to utilize available snapshot and longitudinal data to identify the model parameters. Using lineage tracing technologies developed in the Brock lab, the transcriptomic data set is made actionable by developing a classifier capable of predicting whether a cell in a sample is sensitive or resistant to chemotherapy. We apply this to estimate the composition of the population at a few snapshots in time during treatment response and combine this with longitudinal data directly into our model calibration. The explicit incorporation of molecular level data with population-size dynamics data improves the identifiability and predictive power of the mathematical model. We intend this work to be exemplary of ways in which novel methods can improve the use of data to describe, evaluate, predict, and optimize cancer treatments
Book Synopsis Mathematical Modeling and Intelligent Control for Combating Pandemics by : Zakia Hammouch
Download or read book Mathematical Modeling and Intelligent Control for Combating Pandemics written by Zakia Hammouch and published by Springer. This book was released on 2023-10-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributions in this carefully curated volume, present cutting-edge research in applied mathematical modeling for combating COVID-19 and other potential pandemics. Mathematical modeling and intelligent control have emerged as powerful computational models and have shown significant success in combating any pandemic. These models can be used to understand how COVID-19 or other pandemics can spread, analyze data on the incidence of infectious diseases, and predict possible future scenarios concerning pandemics. This book also discusses new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 and other pandemics based on intelligent control systems that assist decision-makers, managers, professionals, and researchers. Much of the book focuses on preparing the scientific community for the next pandemic, particularly the application of mathematical modeling and intelligent control for combating the Monkeypox virus and Langya Henipavirus.
Author :University of Minnesota. Institute for Mathematics and Its Applications Publisher : ISBN 13 : Total Pages :28 pages Book Rating :4.:/5 (123 download)
Book Synopsis Mathematical Modeling and Computer Simulation of the Aging-cancer Interface by : University of Minnesota. Institute for Mathematics and Its Applications
Download or read book Mathematical Modeling and Computer Simulation of the Aging-cancer Interface written by University of Minnesota. Institute for Mathematics and Its Applications and published by . This book was released on 1989 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mathematical and Computational Oncology by : George Bebis
Download or read book Mathematical and Computational Oncology written by George Bebis and published by Springer Nature. This book was released on 2019-11-14 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Symposium on Mathematical and Computational Oncology, ISMCO'2019, held in Lake Tahoe, NV, USA, in October 2019. The 7 full papers presented were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections named: Tumor evolvability and intra-tumor heterogeneity; Imaging and scientific visualization for cancer research; Statistical methods and data mining for cancer research (SMDM); Spatio-temporal tumor modeling and simulation (STTMS).
Book Synopsis Advances in Mathematical and Computational Oncology by : Doron Levy
Download or read book Advances in Mathematical and Computational Oncology written by Doron Levy and published by Frontiers Media SA. This book was released on 2022-05-05 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in mathematical and computational oncology, volume III by : George Bebis
Download or read book Advances in mathematical and computational oncology, volume III written by George Bebis and published by Frontiers Media SA. This book was released on 2023-10-25 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Systems Biology of Cancer by : Emmanuel Barillot
Download or read book Computational Systems Biology of Cancer written by Emmanuel Barillot and published by CRC Press. This book was released on 2012-08-25 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.
Book Synopsis Mathematical Models of Tumor-Immune System Dynamics by : Amina Eladdadi
Download or read book Mathematical Models of Tumor-Immune System Dynamics written by Amina Eladdadi and published by Springer. This book was released on 2014-11-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of papers offers a broad synopsis of state-of-the-art mathematical methods used in modeling the interaction between tumors and the immune system. These papers were presented at the four-day workshop on Mathematical Models of Tumor-Immune System Dynamics held in Sydney, Australia from January 7th to January 10th, 2013. The workshop brought together applied mathematicians, biologists, and clinicians actively working in the field of cancer immunology to share their current research and to increase awareness of the innovative mathematical tools that are applicable to the growing field of cancer immunology. Recent progress in cancer immunology and advances in immunotherapy suggest that the immune system plays a fundamental role in host defense against tumors and could be utilized to prevent or cure cancer. Although theoretical and experimental studies of tumor-immune system dynamics have a long history, there are still many unanswered questions about the mechanisms that govern the interaction between the immune system and a growing tumor. The multidimensional nature of these complex interactions requires a cross-disciplinary approach to capture more realistic dynamics of the essential biology. The papers presented in this volume explore these issues and the results will be of interest to graduate students and researchers in a variety of fields within mathematical and biological sciences.
Book Synopsis Mathematical Models of Cancer and Different Therapies by : Regina Padmanabhan
Download or read book Mathematical Models of Cancer and Different Therapies written by Regina Padmanabhan and published by Springer Nature. This book was released on 2020-10-31 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified framework for various currently available mathematical models that are used to analyze progression and regression in cancer development, and to predict its dynamics with respect to therapeutic interventions. Accurate and reliable model representations of cancer dynamics are milestones in the field of cancer research. Mathematical modeling approaches are becoming increasingly common in cancer research, as these quantitative approaches can help to validate hypotheses concerning cancer dynamics and thus elucidate the complexly interlaced mechanisms involved. Even though the related conceptual and technical information is growing at an exponential rate, the application of said information and realization of useful healthcare devices are lagging behind. In order to remedy this discrepancy, more interdisciplinary research works and course curricula need to be introduced in academic, industrial, and clinical organizations alike. To that end, this book reformulates most of the existing mathematical models as special cases of a general model, allowing readers to easily get an overall idea of cancer dynamics and its modeling. Moreover, the book will help bridge the gap between biologists and engineers, as it brings together cancer dynamics, the main steps involved in mathematical modeling, and control strategies developed for cancer management. This also allows readers in both medical and engineering fields to compare and contrast all the therapy-based models developed to date using a single source, and to identify unexplored research directions.
Book Synopsis Multiscale Cancer Modeling by : Thomas S. Deisboeck
Download or read book Multiscale Cancer Modeling written by Thomas S. Deisboeck and published by CRC Press. This book was released on 2010-12-08 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is a complex disease process that spans multiple scales in space and time. Driven by cutting-edge mathematical and computational techniques, in silico biology provides powerful tools to investigate the mechanistic relationships of genes, cells, and tissues. It enables the creation of experimentally testable hypotheses, the integration of dat
