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Application of Bioinformatics in Cancers

Application of Bioinformatics in Cancers
Author: Chad Brenner
Publisher: MDPI
Total Pages: 418
Release: 2019-11-20
Genre: Medical
ISBN: 3039217887
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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.

Application of Bioinformatics in Cancers

Application of Bioinformatics in Cancers
Author: J. Chad Brenner
Publisher:
Total Pages: 418
Release: 2019
Genre: Biotechnology
ISBN: 9783039217892
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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.

Cancer Bioinformatics

Cancer Bioinformatics
Author: Ying Xu
Publisher: Springer
Total Pages: 386
Release: 2014-08-30
Genre: Computers
ISBN: 1493913816
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This book provides a framework for computational researchers studying the basics of cancer through comparative analyses of omic data. It discusses how key cancer pathways can be analyzed and discovered to derive new insights into the disease and identifies diagnostic and prognostic markers for cancer. Chapters explain the basic cancer biology and how cancer develops, including the many potential survival routes. The examination of gene-expression patterns uncovers commonalities across multiple cancers and specific characteristics of individual cancer types. The authors also treat cancer as an evolving complex system, explore future case studies, and summarize the essential online data sources. Cancer Bioinformatics is designed for practitioners and researchers working in cancer research and bioinformatics. It is also suitable as a secondary textbook for advanced-level students studying computer science, biostatistics or biomedicine.

Cancer Bioinformatics

Cancer Bioinformatics
Author:
Publisher: BoD – Books on Demand
Total Pages: 172
Release: 2022-09-28
Genre: Medical
ISBN: 1839691077
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This book discusses the application of bioinformatics in cancer disease management. It covers general aspects of cancer as a disease but also as a success story in the translation of omics data in clinical settings. It provides an overview of the specific applications of bioinformatics tools in cancer epidemiology, prevention, and screening and in the identification of novel genetic and molecular biomarkers involved in cancer development. This is accomplished through the inclusion of numerous examples of the use of bioinformatics in precision oncology.

Handbook of Research on Natural Products and Their Bioactive Compounds as Cancer Therapeutics

Handbook of Research on Natural Products and Their Bioactive Compounds as Cancer Therapeutics
Author: Pandurangan, Ashok Kumar
Publisher: IGI Global
Total Pages: 643
Release: 2022-03-18
Genre: Medical
ISBN: 1799892603
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Many chemotherapeutic agents are available in today’s market that are highly effective against a variety of cancer types; however, the major drawbacks of these chemotherapeutic agents are the many side effects. As an alternative to these chemotherapeutic agents, there are a number of natural agents that are effective against cancer that have been tested in preclinical and clinical models over the years. These natural products must be documented and discussed in order to provide a thorough overview of all the options available for cancer treatment. The Handbook of Research on Natural Products and Their Bioactive Compounds as Cancer Therapeutics emphasizes the list of natural agents against all types of cancers and discusses the current state of research in the fields of natural products and their derivatives against cancer in preclinical and clinical models. This book also provides insight into the applications of meditation and mindfulness-based interventions in clinical and non-clinical conditions. Covering topics such as cancer therapy, antioxidants, and flavonoids, it is ideal for students, research scholars, academicians, professors, scientists, oncologists, doctors, and medical practitioners.

Cancer Systems Biology, Bioinformatics and Medicine

Cancer Systems Biology, Bioinformatics and Medicine
Author: Alfredo Cesario
Publisher: Springer Science & Business Media
Total Pages: 496
Release: 2011-08-21
Genre: Medical
ISBN: 9400715676
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This teaching monograph on systems approaches to cancer research and clinical applications provides a unique synthesis, by world-class scientists and doctors, of laboratory, computational, and clinical methods, thereby establishing the foundations for major advances not possible with current methods. Specifically, the book: 1) Sets the stage by describing the basis of systems biology and bioinformatics approaches, and the clinical background of cancer in a systems context; 2) Summarizes the laboratory, clinical, data systems analysis and bioinformatics tools, along with infrastructure and resources required; 3) Demonstrates the application of these tools to cancer research; 4) Extends these tools and methods to clinical diagnosis, drug development and treatment applications; and 5) Finishes by exploring longer term perspectives and providing conclusions. This book reviews the state-of-the-art, and goes beyond into new applications. It is written and highly referenced as a textbook and practical guide aimed at students, academics, doctors, clinicians, industrialists and managers in cancer research and therapeutic applications. Ideally, it will set the stage for integration of available knowledge to optimize communication between basic and clinical researchers involved in the ultimate fight against cancer, whatever the field of specific interest, whatever the area of activity within translational research.

Cancer Bioinformatics

Cancer Bioinformatics
Author: Sylvia Nagl
Publisher:
Total Pages: 320
Release: 2006-03-06
Genre: Medical
ISBN:
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"The development and application of bioinformatics tools to basic and translational cancer research is, in fact, a rapidly expanding field that deserves a timely review. Therefore, a publication of this type is needed. The editors have done an excellent job in recruiting well-established scientists to author the various chapters of the book." —Dieter Naf, Jackson Laboratory, USA Cancer bioinformatics is now emerging as a new interdisciplinary field, which is facilitating an unprecedented synthesis of knowledge arising from the life and clinical sciences. This groundbreaking title provides a comprehensive and up-to-date account of the enormous range of bioinformatics for cancer therapy development from the laboratory to clinical trials. It functions as a guide to integrated data exploitation and synergistic knowledge discovery, and support the consolidation of the interdisciplinary research community involved.

The Applications of Bioinformatics in Cancer Detection

The Applications of Bioinformatics in Cancer Detection
Author: Asad Umar
Publisher:
Total Pages: 296
Release: 2004
Genre: Medical
ISBN:
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The state of the science of bioinformatics - that is, application of computer processes to solving biological problems - and its potential for assisting early cancer detection, risk assessment, and risk reduction form the focus of this volume.

Biomedical Data Mining for Information Retrieval

Biomedical Data Mining for Information Retrieval
Author: Sujata Dash
Publisher: John Wiley & Sons
Total Pages: 450
Release: 2021-08-24
Genre: Computers
ISBN: 111971124X
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BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Computational Biology

Computational Biology
Author: Tuan Pham
Publisher: Springer Science & Business Media
Total Pages: 309
Release: 2009-09-23
Genre: Medical
ISBN: 1441908110
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This volume covers techniques in computational biology and their applications in oncology. It details advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, and image and pattern analysis applied to cancer research.