Biological And Medical Data Analysis
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Biological And Medical Data Analysis
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Author : José María Barreiro
language : en
Publisher: Springer
Release Date : 2004-12-21
Biological And Medical Data Analysis written by José María Barreiro and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-21 with Medical categories.
Thisyear,the5thInternationalSymposiumonMedicalDataAnalysishasexperimented an apparently slight modi?cation. The word "biological" has been added to the title of the conferences. The motivation for this shift goes beyond the wish to attract a diff- ent kind of professional. It is linked to recent trends to produce a shift within various biomedical areas towards genomics-based research and practice. For instance, medical informaticsandbioinformaticsarebeinglinkedina synergicareadenominatedbiom- ical informatics.Similarly,patient careis beingimproved,leadingto conceptsandareas such as molecular medicine, genomic medicine or personalized healthcare. The resultsfromdifferentgenomeprojects,the advancesin systemsbiologyand the integrative approaches to physiology would not be possible without new approaches in data and information processing. Within this scenario, novel methodologies and tools will beneededtolinkclinicalandgenomicinformation,forinstance,forgeneticclinical trials, integrated data mining of genetic clinical records and clinical databases, or gene expression studies, among others. Genomic medicine presents a series of challenges that need to be addressed by researchers and practitioners. In this sense, this ISBMDA conference aimed to become a place where researchers involved in biomedical research could meet and discuss. For this conference, the classical contents of former ISMDA conferences were updated to incorporate various issues from the biological ?elds. Similarly to the incorporation of these new topics of the conference, data analysts will face, in this world of genomic medicine and related areas, signi?cant challenges in research, education and practice.
Biological And Medical Data Analysis
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Author : Nicos Maglaveras
language : en
Publisher: Springer
Release Date : 2006-11-23
Biological And Medical Data Analysis written by Nicos Maglaveras and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-23 with Medical categories.
This book constitutes the refereed proceedings of the 7th International Symposium on Biological and Medical Data Analysis, ISBMDA 2006, held in Thessaloniki, Greece, December 2006. Coverage in this volume includes functional genomics, sequence analysis, biomedical models, information modeling, biomedical signal processing, biomedical image analysis, biomedical data analysis, as well as decision support systems and diagnostic tools.
Analysis Of Biological Data
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Author : Sanghamitra Bandyopadhyay
language : en
Publisher: World Scientific
Release Date : 2007
Analysis Of Biological Data written by Sanghamitra Bandyopadhyay and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter. Sample Chapter(s). Chapter 1: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (160 KB). Contents: Overview: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (H Tang & S Kim); An Introduction to Soft Computing (A Konar & S Das); Biological Sequence and Structure Analysis: Reconstructing Phylogenies with Memetic Algorithms and Branch-and-Bound (J E Gallardo et al.); Classification of RNA Sequences with Support Vector Machines (J T L Wang & X Wu); Beyond String Algorithms: Protein Sequence Analysis Using Wavelet Transforms (A Krishnan & K-B Li); Filtering Protein Surface Motifs Using Negative Instances of Active Sites Candidates (N L Shrestha & T Ohkawa); Distill: A Machine Learning Approach to Ab Initio Protein Structure Prediction (G Pollastri et al.); In Silico Design of Ligands Using Properties of Target Active Sites (S Bandyopadhyay et al.); Gene Expression and Microarray Data Analysis: Inferring Regulations in a Genomic Network from Gene Expression Profiles (N Noman & H Iba); A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure (K Deb et al.); Feature Selection for Cancer Classification Using Ant Colony Optimization and Support Vector Machines (A Gupta et al.); Sophisticated Methods for Cancer Classification Using Microarray Data (S-B Cho & H-S Park); Multiobjective Evolutionary Approach to Fuzzy Clustering of Microarray Data (A Mukhopadhyay et al.). Readership: Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, artificial intelligence, data mining, machine learning, electrical engineering, system science; researchers in pharmaceutical industries.
Deep Learning In Biology And Medicine
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Author : Davide Bacciu
language : en
Publisher: World Scientific
Release Date : 2022-01-17
Deep Learning In Biology And Medicine written by Davide Bacciu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Computers categories.
Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.
Big Data Analytics In Bioinformatics And Healthcare
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Author : Baoying Wang
language : en
Publisher:
Release Date : 2014-10
Big Data Analytics In Bioinformatics And Healthcare written by Baoying Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10 with Data mining categories.
"This book merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management"--
Biological Data Mining And Its Applications In Healthcare
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Author : Xiaoli Li
language : en
Publisher: World Scientific
Release Date : 2013-11-28
Biological Data Mining And Its Applications In Healthcare written by Xiaoli Li and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-28 with Science categories.
Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.
Database Technology For Life Sciences And Medicine
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Author : Claudia Plant
language : en
Publisher: World Scientific
Release Date : 2010
Database Technology For Life Sciences And Medicine written by Claudia Plant and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
This book presents innovative approaches from database researchers supporting the challenging process of knowledge discovery in biomedicine. Ranging from how to effectively store and organize biomedical data via data quality and case studies to sophisticated data mining methods, this book provides the state-of-the-art of database technology for life sciences and medicine. A valuable source of information for experts in life sciences who want to be updated about the possibilities of database technology in their field, this volume will also be inspiring for students and researchers in informatics who are keen to contribute to this emerging field of interdisciplinary research.
A Primer In Biological Data Analysis And Visualization Using R
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Author : Gregg Hartvigsen
language : en
Publisher: Columbia University Press
Release Date : 2014-02-18
A Primer In Biological Data Analysis And Visualization Using R written by Gregg Hartvigsen and has been published by Columbia University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-18 with Education categories.
R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen's extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of entering data into R, working with data in R, and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normal data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter introducing algorithms and the art of programming using R.
Introduction To Statistical Data Analysis For The Life Sciences
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Author : Claus Thorn Ekstrom
language : en
Publisher: CRC Press
Release Date : 2014-11-06
Introduction To Statistical Data Analysis For The Life Sciences written by Claus Thorn Ekstrom and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-06 with Mathematics categories.
A Hands-On Approach to Teaching Introductory StatisticsExpanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the m
Analyzing Ecological Data
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Author : Alain Zuur
language : en
Publisher: Springer
Release Date : 2007-08-29
Analyzing Ecological Data written by Alain Zuur and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-29 with Science categories.
'Which test should I apply?' During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of 'What are your underlying questions?', 'What do you want to show?'. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better start ing point for an ecologist is to avoid the phrase 'test' and think in terms of 'analy sis'. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, per haps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitative science trying to answer difficult questions about the complex world we live in. Most ecologists are aware of these complexities, but few are fully equipped with the statistical sophistication and understanding to deal with them.