Computational tools in inferring cancer tissue-of-origin and molecular classification towards personalized cancer therapy, Volume II PDF Download

Author: Min Tang
Publisher: Frontiers Media SA
ISBN: 288971408X
Category : Science
Languages : en
Pages : 138

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Author: Min Tang
Publisher: Frontiers Media SA
ISBN: 2832555012
Category : Science
Languages : en
Pages : 324

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Book Description
Our second Research Topic in this series, Computational tools in inferring cancer tissue-of-origin and molecular classification towards personalized cancer therapy, Volume II (https://fro.ntiers.in/14361) has over 8 accepted articles and further manuscripts currently under review. Due to the continued success of these Research Topics and the interest in the subject, we will launch a third volume on the same topic. Inferring cancer tissue-of-origin and molecular classification are two critical problems in personalized cancer therapy. It is known that there are about 5% cancers of unknown primary (CUP) site. These kinds of patients are under empirical chemotherapy, which leads to a very low survival rate. Thus, it is important to infer cancer tissue-of-origin. However, experimental methods usually fail to identify the exact tissue-of-origin even after the death of a patient, which provides a need for computational methods especially in the era of big biomedical data. Based on the finding that gene expressions of metastasis cancer cells are more similar to those of original tissue than metastasis tissue, there have been a few computational methods developed in this area. However, the accuracy of the methods is yet to be improved to assure a clinical usage. In addition to CUP, inferring cancer tissue-of-origin is also important in avoiding misdiagnosis even if the cancer origin is known.

Author: United States. Public Health Service. Office of the Surgeon General
Publisher:
ISBN:
Category : Government publications
Languages : en
Pages : 728

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This report considers the biological and behavioral mechanisms that may underlie the pathogenicity of tobacco smoke. Many Surgeon General's reports have considered research findings on mechanisms in assessing the biological plausibility of associations observed in epidemiologic studies. Mechanisms of disease are important because they may provide plausibility, which is one of the guideline criteria for assessing evidence on causation. This report specifically reviews the evidence on the potential mechanisms by which smoking causes diseases and considers whether a mechanism is likely to be operative in the production of human disease by tobacco smoke. This evidence is relevant to understanding how smoking causes disease, to identifying those who may be particularly susceptible, and to assessing the potential risks of tobacco products.

Author: Macfarlane Burnet
Publisher: Elsevier
ISBN: 1483159221
Category : Medical
Languages : en
Pages : 289

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Immunological Surveillance

Author: Kenneth K.W. To
Publisher: Academic Press
ISBN: 0128199032
Category : Science
Languages : en
Pages : 460

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Drug Repurposing in Cancer Therapy: Approaches and Applications provides comprehensive and updated information from experts in basic science research and clinical practice on how existing drugs can be repurposed for cancer treatment. The book summarizes successful stories that may assist researchers in the field to better design their studies for new repurposing projects. Sections discuss specific topics such as in silico prediction and high throughput screening of repurposed drugs, drug repurposing for overcoming chemoresistance and eradicating cancer stem cells, and clinical investigation on combination of repurposed drug and anticancer therapy. Cancer researchers, oncologists, pharmacologists and several members of biomedical field who are interested in learning more about the use of existing drugs for different purposes in cancer therapy will find this to be a valuable resource. - Presents a systematic and up-to-date collection of the research underpinning the various drug repurposing approaches for a quick, but in-depth understanding on current trends in drug repurposing research - Brings better understanding of the drug repurposing process in a holistic way, combining both basic and clinical sciences - Encompasses a collection of successful stories of drug repurposing for cancer therapy in different cancer types

Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309224187
Category : Science
Languages : en
Pages : 354

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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Author: Emmanuel Barillot
Publisher: CRC Press
ISBN: 1439831440
Category : Science
Languages : en
Pages : 463

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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: Utku Kose
Publisher: Springer Nature
ISBN: 9811563217
Category : Technology & Engineering
Languages : en
Pages : 311

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This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.

Author: King K. Holmes
Publisher: World Bank Publications
ISBN: 1464805253
Category : Medical
Languages : en
Pages : 1027

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Infectious diseases are the leading cause of death globally, particularly among children and young adults. The spread of new pathogens and the threat of antimicrobial resistance pose particular challenges in combating these diseases. Major Infectious Diseases identifies feasible, cost-effective packages of interventions and strategies across delivery platforms to prevent and treat HIV/AIDS, other sexually transmitted infections, tuberculosis, malaria, adult febrile illness, viral hepatitis, and neglected tropical diseases. The volume emphasizes the need to effectively address emerging antimicrobial resistance, strengthen health systems, and increase access to care. The attainable goals are to reduce incidence, develop innovative approaches, and optimize existing tools in resource-constrained settings.

Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385

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Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data