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An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer.
Research and Clinical Applications of Targeting Gastric Neoplasms provides a comprehensive overview of gastrointestinal cancers, covering preclinical research and clinical findings related to risk factors, current treatment regimens (including immunotherapy), screening/detection methods, etiology of disease, precision medicine and future perspectives. Gastrointestinal cancers rank among the most lethal and common worldwide, and as such, there is intense research into their diverse causes and treatment options. This reference provides a consolidation of the research, making it a perfect resource for basic science and clinical researchers as well as oncologists who work in gastroenterology and GI tract cancer fields. Provides comprehensive coverage of preclinical research and the clinical aspects of gastric cancer Presents future perspectives from leading researchers in the field who provide the potential for furthering research topics Combines the expertise of researchers in GI tracts, cancer, immunity, immunology, infectious disease and microbiology for an interdisciplinary approach
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.
This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.
Principles and Applications of Molecular Diagnostics serves as a comprehensive guide for clinical laboratory professionals applying molecular technology to clinical diagnosis. The first half of the book covers principles and analytical concepts in molecular diagnostics such as genomes and variants, nucleic acids isolation and amplification methods, and measurement techniques, circulating tumor cells, and plasma DNA; the second half presents clinical applications of molecular diagnostics in genetic disease, infectious disease, hematopoietic malignancies, solid tumors, prenatal diagnosis, pharmacogenetics, and identity testing. A thorough yet succinct guide to using molecular testing technology, Principles and Applications of Molecular Diagnostics is an essential resource for laboratory professionals, biologists, chemists, pharmaceutical and biotech researchers, and manufacturers of molecular diagnostics kits and instruments. - Explains the principles and tools of molecular biology - Describes standard and state-of-the-art molecular techniques for obtaining qualitative and quantitative results - Provides a detailed description of current molecular applications used to solve diagnostics tasks
Studies of mammary gland biology are critically important given the prevalence of breast cancer in the population. There are many other reasons to study this organ, however. It represents an excellent model system for research into developmental mechanisms, gene regulation, tissue organization, hormonal action, secretion, and stem cell biology, revealing general principles that can be extended to other organs and tissues. This book provides valuable lessons for all cell, developmental, and cancer biologists.
Modeling is fast becoming fundamental to understanding the processes that define biological systems. High-throughput technologies are producing increasing quantities of data that require an ever-expanding toolset for their effective analysis and interpretation. Analysis of high-throughput data in the context of a molecular interaction network is particularly informative as it has the potential to reveal the most relevant network modules with respect to a phenotype or biological process of interest.Analysis of Biological Systems collects classical material on analysis, modeling and simulation, thereby acting as a unique point of reference. The joint application of statistical techniques to extract knowledge from big data and map it into mechanistic models is a current challenge of the field, and the reader will learn how to build and use models even if they have no computing or math background. An in-depth analysis of the currently available technologies, and a comparison between them, is also included. Unlike other reference books, this in-depth analysis is extended even to the field of language-based modeling. The overall result is an indispensable, self-contained and systematic approach to a rapidly expanding field of science.
Highlighting recent advances in our understanding of breast cancer, this book is intended for a wide audience as a reference book. Included are reviews of genetics, epigenetics, various aspects of cell and molecular biology, and several other areas of breast cancer that are aimed at determining new intervention sites for treatments and cures of the disease. The chapters are written by internationally recognized experts and include reviews of key topics in breast cancer research. Each chapter highlights the new aspects of specific research topics and the various impacts of designing new strategies as well as identifies new targets for therapeutic intervention. The topics addressed are selected to be of interest to patients, scientists, students, teachers, and anyone else interested in expanding their knowledge of breast cancer imaging, diagnostics, therapeutics, or basic biomedical research on breast cancer.