Community series in unveiling the tumor microenvironment by machine learning to develop new immunotherapeutic strategies, volume II PDF Download
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Author: Ping Zheng
Publisher: Frontiers Media SA
ISBN: 2832541232
Category : Medical
Languages : en
Pages : 383
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Book Description
Author: Ping Zheng
Publisher: Frontiers Media SA
ISBN: 2832541232
Category : Medical
Languages : en
Pages : 383
Get Book Here
Book Description
Author: Nan Zhang
Publisher: Frontiers Media SA
ISBN: 2832533779
Category : Medical
Languages : en
Pages : 295
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Book Description
The tumor microenvironment (TME) plays a critical role in tumor proliferation, progression, and therapeutic responses. TME is a complex network of cancer cells, stromal cells, and, most importantly, infiltrating immune cells. Cancer cells regulate numerous biological functions through direct or indirect interaction with TME components. Emerging evidence suggests that TME crucially influences the response to both chemotherapy and immunotherapy. As scientific research has entered the big data era with the fast development of high-throughput sequencing technologies, machine learning has been gradually widely applied to extract important knowledge from big data bioinformatics. Thus, characterizing the TME landscape in cancer and identifying different immune-related TME phenotypes using machine learning-based bioinformatics analyses, in vitro experiments, and in vivo experiments are of great interest and significance.
Author: Nan Zhang
Publisher: Frontiers Media SA
ISBN: 2832536301
Category : Medical
Languages : en
Pages : 297
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Book Description
The tumor microenvironment (TME) plays a critical role in tumor proliferation, progression, and therapeutic responses. TME is a complex network of cancer cells, stromal cells, and, most importantly, infiltrating immune cells. Cancer cells regulate numerous biological functions through direct or indirect interaction with TME components. Emerging evidence suggests that TME crucially influences the response to both chemotherapy and immunotherapy. As scientific research has entered the big data era with the fast development of high-throughput sequencing technologies, machine learning has been gradually widely applied to extract important knowledge from big data bioinformatics. Thus, characterizing the TME landscape in cancer and identifying different immune-related TME phenotypes using machine learning-based bioinformatics analyses, in vitro experiments, and in vivo experiments are of great interest and significance.
Author: Alice Longobardi Givan
Publisher: John Wiley & Sons
ISBN: 1118688392
Category : Science
Languages : en
Pages : 309
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Book Description
Flow cytometry continually amazes scientists with its ever-expanding utility. Advances in flow cytometry have opened new directions in theoretical science, clinical diagnosis, and medical practice. The new edition of Flow Cytometry: First Principles provides a thorough update of this now classic text, reflecting innovations in the field while outlining the fundamental elements of instrumentation, sample preparation, and data analysis. Flow Cytometry: First Principles, Second Edition explains the basic principles of flow cytometry, surveying its primary scientific and clinical applications and highlighting state-of-the-art techniques at the frontiers of research. This edition contains extensive revisions of all chapters, including new discussions on fluorochrome and laser options for multicolor analysis, an additionalsection on apoptosis in the chapter on DNA, and new chapters onintracellular protein staining and cell sorting, including high-speed sorting and alternative sorting methods, as well as traditional technology. This essential resource: Assumes no prior knowledge of flow cytometry Progresses with an informal, engaging lecture style from simpleto more complex concepts Offers a clear introduction to new vocabulary, principles of instrumentation, and strategies for data analysis Emphasizes the theory relevant to all flow cytometry, with examples from a variety of clinical and scientific fields Flow Cytometry: First Principles, Second Edition provides scientists, clinicians, technologists, and students with the knowledge necessary for beginning the practice of flow cytometry and for understanding related literature.
Author: Emmanuel Barillot
Publisher: CRC Press
ISBN: 1439831440
Category : Science
Languages : en
Pages : 463
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Book Description
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.
Author: Marie-Caroline Dieu-Nosjean
Publisher: Humana Press
ISBN: 9781493987085
Category : Medical
Languages : en
Pages : 289
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Book Description
This volume explores the various methods used to study tertiary lymphoid structures (TLS) in pathological situations. Pre-clinical models are also discussed in detail to show how TLS structure, development, and maintenance can be targeted and studied in vivo. The chapters in this book cover topics such as humans and mice; strategies to quantify TLS in order to use it in stained tissue sections; classifying a gene signature form fixed and paraffin-embedded tissues; and development of murine inflammatory models to help look at TLS in the context of infection or malignancy. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and thorough, Tertiary Lymphoid Structures: Methods and Protocols is a valuable resource that increases the reader’s knowledge on immune functions and how they will pave the way to future therapeutic applications.
Author: Robert A. Mikos
Publisher: Aspen Publishing
ISBN: 1454887958
Category : Law
Languages : en
Pages : 1067
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Book Description
Marijuana Law, Policy, and Authority is a first-of-its-kind law school casebook in a rapidly-emerging and exciting new field. The accessible, comprehensive, and engaging material guides students through the competing approaches to regulating marijuana, the purposes and effects of those approaches, and the legal authorities for choosing among them. The helpful organization intersperses these issues of substantive law, policy, and authority throughout the discussion of users, suppliers, and third parties. Substantive law materials cover either prohibitions or regulations targeting users, suppliers, or third parties. Policy materials cover the goals of marijuana law and policy as well as the research on the impact of different marijuana policies. Authority materials address the different levels of government—federal, state, and local. Notes, questions, and numerous problems in each chapter provide additional thought-provoking material and help to reinforce student learning. Current, news-headlining cases keep the discussion interesting and lively. Key Features: Internationally renowned author Robert Mikos is the premier authority on marijuana law. He draws upon nearly a decade of professional experience teaching, lecturing, consulting, and writing about marijuana law and policy. Three distinct but inter-woven topics are covered: the substantive law governing marijuana; the policy rationales behind and outcomes produced by different approaches to regulating the drug; and the legal authority to regulate the drug. Students are guided through the multi-faceted legal and policy issues now confronting lawyers, lawmakers, judges, and policy analysts working in this emerging field. Written in a style that is familiar to law students, but also accessible to a much broader audience, including graduate and upper level undergraduate students in courses in policy studies, political science, and criminology. Cutting-edge issues are included that are intellectually engaging for students and professors alike—e.g., how are conflicts between state/ federal law resolved? What are the roles of courts and executive officers in terms of policy? Dives deeply into classic legal issues: contract enforceability and powers of court, Congress, and the state. Notes and Questions following cases offer stimulating fodder for discussion.
Author: Janmenjoy Nayak
Publisher: Springer Nature
ISBN: 3030719758
Category : Technology & Engineering
Languages : en
Pages : 461
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Book Description
This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.
Author: Subhas C. Kundu
Publisher: Elsevier
ISBN: 012818129X
Category : Technology & Engineering
Languages : en
Pages : 773
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Book Description
Biomaterials for 3D Tumor Modeling reviews the fundamentals and most relevant areas of the latest advances of research of 3D cancer models, focusing on biomaterials science, tissue engineering, drug delivery and screening aspects. The book reviews advanced fundamental topics, including the causes of cancer, existing cancer models, angiogenesis and inflammation during cancer progression, and metastasis in 3D biomaterials. Then, the most relevant biomaterials are reviewed, including methods for engineering and fabrication of biomaterials. 3D models for key biological systems and types of cancer are also discussed, including lung, liver, oral, prostate, pancreatic, ovarian, bone and pediatric cancer. This book is suitable for those working in the disciplines of materials science, biochemistry, genetics, molecular biology, drug delivery and regenerative medicine. - Reviews key biomaterials topics, including synthetic biomaterials, hydrogels, e-spun materials and nanoparticles - Provides a comprehensive overview of 3D cancer models for key biological systems and cancer types - Includes an overview of advanced fundamental concepts for an interdisciplinary audience in materials science, biochemistry, regenerative medicine and drug delivery
Author: Issam El Naqa
Publisher: CRC Press
ISBN: 0429840357
Category : Science
Languages : en
Pages : 392
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Book Description
This book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life. It contains coverage of the relevant data sources available for model construction (panomics), ranging from clinical or preclinical resources to basic patient and treatment characteristics, medical imaging (radiomics), and molecular biological markers such as those involved in genomics, proteomics and metabolomics. It also includes discussions on the varying methodologies for predictive model building with analytical and data-driven approaches. This book is primarily intended to act as a tutorial for newcomers to the field of outcome modeling, as it includes in-depth how-to recipes on modeling artistry while providing sufficient instruction on how such models can approximate the physical and biological realities of clinical treatment. The book will also be of value to seasoned practitioners as a reference on the varying aspects of outcome modeling and their current applications. Features: Covers top-down approaches applying statistical, machine learning, and big data analytics and bottom-up approaches using first principles and multi-scale techniques, including numerical simulations based on Monte Carlo and automata techniques Provides an overview of the available software tools and resources for outcome model development and evaluation, and includes hands-on detailed examples throughout Presents a diverse selection of the common applications of outcome modeling in a wide variety of areas: treatment planning in radiotherapy, chemotherapy and immunotherapy, utility-based and biomarker applications, particle therapy modeling, oncological surgery, and the design of adaptive and SMART clinical trials
