Author: Werner Dubitzky
Publisher: Springer Science & Business Media
ISBN: 0387475095
Category : Science
Languages : en
Pages : 300
Book Description
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.
Fundamentals of Data Mining in Genomics and Proteomics
Author: Werner Dubitzky
Publisher: Springer Science & Business Media
ISBN: 0387475095
Category : Science
Languages : en
Pages : 300
Book Description
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.
Publisher: Springer Science & Business Media
ISBN: 0387475095
Category : Science
Languages : en
Pages : 300
Book Description
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Elena Marchiori
Publisher: Springer Science & Business Media
ISBN: 3540787569
Category : Computers
Languages : en
Pages : 222
Book Description
This book constitutes the refereed proceedings of the 6th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2008, held in Naples, Italy, in March 2008 colocated with the Evo* 2008 events. The 18 revised full papers were carefully reviewed and selected from 63 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.
Publisher: Springer Science & Business Media
ISBN: 3540787569
Category : Computers
Languages : en
Pages : 222
Book Description
This book constitutes the refereed proceedings of the 6th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2008, held in Naples, Italy, in March 2008 colocated with the Evo* 2008 events. The 18 revised full papers were carefully reviewed and selected from 63 submissions. EvoBio is the premiere European event for experts in computer science meeting with experts in bioinformatics and the biological sciences, all interested in the interface between evolutionary computation, machine learning, data mining, bioinformatics, and computational biology. Topics addressed by the papers include biomarker discovery, cell simulation and modeling, ecological modeling, uxomics, gene networks, biotechnology, metabolomics, microarray analysis, phylogenetics, protein interactions, proteomics, sequence analysis and alignment, as well as systems biology.
Medical Applications of Mass Spectrometry
Author: Karoly Vekey
Publisher: Elsevier
ISBN: 0080554652
Category : Science
Languages : en
Pages : 607
Book Description
Mass spectrometry is fast becoming an indispensable field for medical professionals. The mass spectrometric analysis of metabolites and proteins promises to revolutionize medical research and clinical diagnostics. As this technology rapidly enters the medical field, practicing professionals and students need to prepare to take full advantage of its capabilities. Medical Applications of Mass Spectrometry addresses the key issues in the medical applications of mass spectrometry at the level appropriate for the intended readership. It will go a long way to help the utilization of mass spectrometry in medicine.The book comprises five parts. A general overview is followed by a description of the basic sampling and separation methods in analytical chemistry. In the second part a solid foundation in mass spectrometry and modern techniques of data analysis is presented. The third part explains how mass spectrometry is used in exploring various classes of biomolecules, including proteins and lipids. In the fourth section mass spectrometry is introduced as a diagnostic tool in clinical treatment, infectious pathogen research, neonatal diagnostics, cancer, brain and allergy research, as well as in various fields of medicine: cardiology, pulmonology, neurology, psychiatric diseases, hemato-oncology, urologic diseases, gastrointestinal diseases, gynecology and pediatrics. The fifth part covers emerging applications in biomarker discovery and in mass spectrometric imaging.* Provides a broad look at how the medical field is benefiting from advances in mass spectrometry.* Guides the reader from basic principles and methods to cutting edge applications.* There is NO comparable book on the market to fill this fast growing field.
Publisher: Elsevier
ISBN: 0080554652
Category : Science
Languages : en
Pages : 607
Book Description
Mass spectrometry is fast becoming an indispensable field for medical professionals. The mass spectrometric analysis of metabolites and proteins promises to revolutionize medical research and clinical diagnostics. As this technology rapidly enters the medical field, practicing professionals and students need to prepare to take full advantage of its capabilities. Medical Applications of Mass Spectrometry addresses the key issues in the medical applications of mass spectrometry at the level appropriate for the intended readership. It will go a long way to help the utilization of mass spectrometry in medicine.The book comprises five parts. A general overview is followed by a description of the basic sampling and separation methods in analytical chemistry. In the second part a solid foundation in mass spectrometry and modern techniques of data analysis is presented. The third part explains how mass spectrometry is used in exploring various classes of biomolecules, including proteins and lipids. In the fourth section mass spectrometry is introduced as a diagnostic tool in clinical treatment, infectious pathogen research, neonatal diagnostics, cancer, brain and allergy research, as well as in various fields of medicine: cardiology, pulmonology, neurology, psychiatric diseases, hemato-oncology, urologic diseases, gastrointestinal diseases, gynecology and pediatrics. The fifth part covers emerging applications in biomarker discovery and in mass spectrometric imaging.* Provides a broad look at how the medical field is benefiting from advances in mass spectrometry.* Guides the reader from basic principles and methods to cutting edge applications.* There is NO comparable book on the market to fill this fast growing field.
Advanced Data Mining and Applications
Author: Reda Alhajj
Publisher: Springer Science & Business Media
ISBN: 3540738703
Category : Computers
Languages : en
Pages : 649
Book Description
This book constitutes the refereed proceedings of the Third International Conference on Advanced Data Mining and Applications, ADMA 2007, held in Harbin, China in August 2007. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining.
Publisher: Springer Science & Business Media
ISBN: 3540738703
Category : Computers
Languages : en
Pages : 649
Book Description
This book constitutes the refereed proceedings of the Third International Conference on Advanced Data Mining and Applications, ADMA 2007, held in Harbin, China in August 2007. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining.
Proteomic and Metabolomic Approaches to Biomarker Discovery
Author: Haleem J. Issaq
Publisher: Academic Press
ISBN: 0123947952
Category : Science
Languages : en
Pages : 489
Book Description
Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution. The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis and modeling. This new standard effectively eliminates the differing methodologies used in studies and creates a unified approach. Readers will learn the advantages and disadvantages of the various techniques discussed, as well as potential difficulties inherent to all steps in the biomarker discovery process. A vital resource for biochemists, biologists, analytical chemists, bioanalytical chemists, clinical and medical technicians, researchers in pharmaceuticals, and graduate students, Proteomic and Metabolomic Approaches to Biomarker Discovery provides the information needed to reduce clinical error in the execution of research. - Describes the use of biomarkers to reduce clinical errors in research - Includes techniques from a range of biomarker discoveries - Covers all steps involved in biomarker discovery, from study design to study execution
Publisher: Academic Press
ISBN: 0123947952
Category : Science
Languages : en
Pages : 489
Book Description
Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution. The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis and modeling. This new standard effectively eliminates the differing methodologies used in studies and creates a unified approach. Readers will learn the advantages and disadvantages of the various techniques discussed, as well as potential difficulties inherent to all steps in the biomarker discovery process. A vital resource for biochemists, biologists, analytical chemists, bioanalytical chemists, clinical and medical technicians, researchers in pharmaceuticals, and graduate students, Proteomic and Metabolomic Approaches to Biomarker Discovery provides the information needed to reduce clinical error in the execution of research. - Describes the use of biomarkers to reduce clinical errors in research - Includes techniques from a range of biomarker discoveries - Covers all steps involved in biomarker discovery, from study design to study execution
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Author: Leonardo Vanneschi
Publisher: Springer
ISBN: 3642371892
Category : Computers
Languages : en
Pages : 226
Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.
Publisher: Springer
ISBN: 3642371892
Category : Computers
Languages : en
Pages : 226
Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.
Tumor Markers
Author: Eleftherios P. Diamandis
Publisher: Amer. Assoc. for Clinical Chemistry
ISBN: 9781890883713
Category : Medical
Languages : en
Pages : 584
Book Description
Publisher: Amer. Assoc. for Clinical Chemistry
ISBN: 9781890883713
Category : Medical
Languages : en
Pages : 584
Book Description
Data Mining for Biomarker Discovery
Author: Panos M. Pardalos
Publisher: Springer Science & Business Media
ISBN: 1461421071
Category : Business & Economics
Languages : en
Pages : 256
Book Description
Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.
Publisher: Springer Science & Business Media
ISBN: 1461421071
Category : Business & Economics
Languages : en
Pages : 256
Book Description
Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.
Cancer Metabolomics 2018
Author: Paula Guedes De Pinho
Publisher: MDPI
ISBN: 3039213458
Category : Medical
Languages : en
Pages : 184
Book Description
The metabolomics approach, defined as the study of all endogenously-produced low-molecular-weight compounds, appeared as a promising strategy to define new cancer biomarkers. Information obtained from metabolomic data can help to highlight disrupted cellular pathways and, consequently, contribute to the development of new-targeted therapies and the optimization of therapeutics. Therefore, metabolomic research may be more clinically translatable than other omics approaches, since metabolites are closely related to the phenotype and the metabolome is sensitive to many factors. Metabolomics seems promising to identify key metabolic pathways characterizing features of pathological and physiological states. Thus, knowing that tumor metabolism markedly differs from the metabolism of normal cells, the use of metabolomics is ideally suited for biomarker research. Some works have already focused on the application of metabolomic approaches to different cancers, namely lung, breast and liver, using urine, exhaled breath and blood. In this Special Issue we contribute to a more complete understanding of cancer disease using metabolomics approaches.
Publisher: MDPI
ISBN: 3039213458
Category : Medical
Languages : en
Pages : 184
Book Description
The metabolomics approach, defined as the study of all endogenously-produced low-molecular-weight compounds, appeared as a promising strategy to define new cancer biomarkers. Information obtained from metabolomic data can help to highlight disrupted cellular pathways and, consequently, contribute to the development of new-targeted therapies and the optimization of therapeutics. Therefore, metabolomic research may be more clinically translatable than other omics approaches, since metabolites are closely related to the phenotype and the metabolome is sensitive to many factors. Metabolomics seems promising to identify key metabolic pathways characterizing features of pathological and physiological states. Thus, knowing that tumor metabolism markedly differs from the metabolism of normal cells, the use of metabolomics is ideally suited for biomarker research. Some works have already focused on the application of metabolomic approaches to different cancers, namely lung, breast and liver, using urine, exhaled breath and blood. In this Special Issue we contribute to a more complete understanding of cancer disease using metabolomics approaches.
Biomedical Data Mining for Information Retrieval
Author: Sujata Dash
Publisher: John Wiley & Sons
ISBN: 1119711266
Category : Computers
Languages : en
Pages : 450
Book Description
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.
Publisher: John Wiley & Sons
ISBN: 1119711266
Category : Computers
Languages : en
Pages : 450
Book Description
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.