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Author: Liang Cheng
Publisher: Frontiers Media SA
ISBN: 283251314X
Category : Medical
Languages : en
Pages : 349
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Book Description
Author: Liang Cheng
Publisher: Frontiers Media SA
ISBN: 283251314X
Category : Medical
Languages : en
Pages : 349
Get Book Here
Book Description
Author: Chunquan Li
Publisher: Frontiers Media SA
ISBN: 2832516246
Category : Science
Languages : en
Pages : 272
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Book Description
Author: Ming Jun Zheng
Publisher: Frontiers Media SA
ISBN: 2832542565
Category : Science
Languages : en
Pages : 342
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Author: Lixin Cheng
Publisher: Frontiers Media SA
ISBN: 283253175X
Category : Science
Languages : en
Pages : 757
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Book Description
This Research Topic is part of a series with, "Bioinformatics Analysis of Omics Data for Biomarker Identification in Clinical Research - Volume I" (https://www.frontiersin.org/research-topics/13816/bioinformatics-analysis-of-omics-data-for-biomarker-identification-in-clinical-research) The advances and the decreasing cost of omics data enable profiling of disease molecular features at different levels, including bulk tissues, animal models, and single cells. Large volumes of omics data enhance the ability to search for information for preclinical study and provide the opportunity to leverage them to understand disease mechanisms, identify molecular targets for therapy, and detect biomarkers of treatment response. Identification of stable, predictive, and interpretable biomarkers is a significant step towards personalized medicine and therapy. Omics data from genomics, transcriptomics, proteomics, epigenomics, metagenomics, and metabolomics help to determine biomarkers for prognostic and diagnostic applications. Preprocessing of omics data is of vital importance as it aims to eliminate systematic experimental bias and technical variation while preserving biological variation. Dozens of normalization methods for correcting experimental variation and bias in omics data have been developed during the last two decades, while only a few consider the skewness between different sample states, such as the extensive over-repression of genes in cancers. The choice of normalization methods determines the fate of identified biomarkers or molecular signatures. From these considerations, the development of appropriate normalization methods or preprocessing strategies may promote biomarker identification and facilitate clinical decision-making.
Author: Charles Swanton
Publisher: Perspectives Cshl
ISBN: 9781621821434
Category : Medical
Languages : en
Pages : 350
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Book Description
Tumor progression is driven by mutations that confer growth advantages to different subpopulations of cancer cells. As a tumor grows, these subpopulations expand, accumulate new mutations, and are subjected to selective pressures from the environment, including anticancer interventions. This process, termed clonal evolution, can lead to the emergence of therapy-resistant tumors and poses a major challenge for cancer eradication efforts. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine examines cancer progression as an evolutionary process and explores how this way of looking at cancer may lead to more effective strategies for managing and treating it. The contributors review efforts to characterize the subclonal architecture and dynamics of tumors, understand the roles of chromosomal instability, driver mutations, and mutation order, and determine how cancer cells respond to selective pressures imposed by anticancer agents, immune cells, and other components of the tumor microenvironment. They compare cancer evolution to organismal evolution and describe how ecological theories and mathematical models are being used to understand the complex dynamics between a tumor and its microenvironment during cancer progression. The authors also discuss improved methods to monitor tumor evolution (e.g., liquid biopsies) and the development of more effective strategies for managing and treating cancers (e.g., immunotherapies). This volume will therefore serve as a vital reference for all cancer biologists as well as anyone seeking to improve clinical outcomes for patients with cancer.
Author: Chad Brenner
Publisher: MDPI
ISBN: 3039217887
Category : Medical
Languages : en
Pages : 418
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Book Description
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.
Author: S. Brünner
Publisher: Springer Science & Business Media
ISBN: 364282031X
Category : Medical
Languages : en
Pages : 253
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Book Description
The enormous expansion seen over the last decade in the mammo graphic detection of breast cancer lesions, especially the use of screen ing procedures for the early detection of clinically unsuspected tumors, has made it necessary to summarize the experience made by various centers in the world. The 2nd International Copenhagen Symposium on Detection of Breast Cancer afforded an opportunity of gathering scientists from all over the world to discuss the various problems of early breast cancer detection with special reference to screening procedures. This book forms a synthesis of the information presented by leading scientists from many of the world's mammo graphic centers, particularly those in Sweden and the USA. Hence, the reader will have the opportunity to study the outstanding work carried out by various institutes and centers of breast cancer screening. It is our sincere hope that a study of this volume will encourage other scientists to join in the work on screening procedures. S. Brunner B. Langfeldt P. E. Andersen Contents S. A. Feig: 1 Hypothetical Breast Cancer Risk from Mammography S. A. Feig: Benefits and Risks of Mammography 11 R. L. Egan and M. B. McSweeney: Multicentric Breast Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . 28 M. B. McSweeney and R. L. Egan: Breast Cancer in the Younger Patient: A Preliminary Report 36 M. B. McSweeney and R. L. Egan: Bilateral Breast Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . ' 41 N. Bjurstam: The Radiographic Appearance of Normal and Metastatic Axillary Lymph Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 M. Moskowitz, S. A. Feig, C. Cole-Beuglet, S. H.
Author: Utku Kose
Publisher: Springer Nature
ISBN: 9811563217
Category : Technology & Engineering
Languages : en
Pages : 311
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Book Description
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: Jiajie Peng
Publisher: Frontiers Media SA
ISBN: 2889761746
Category : Science
Languages : en
Pages : 160
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Book Description
Author: Liang Cheng
Publisher: Frontiers Media SA
ISBN: 2832507387
Category : Science
Languages : en
Pages : 793
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Book Description
