Download or read book Unsupervised Data Mining Applications on High Dimensional Gene Expression Time Series in Toxicogenomics written by Ce Gao and published by . This book was released on 2015 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Toxicogenomics, the study of adverse effects caused by toxicants to human health and environment via high-throughput genomics technologies, present promising alternatives to expensive and lengthy animal-based approaches in toxicity testing and risk assessment. Advances in toxicogenomics techniques now enable monitoring cellular activities continuously, under a large range of experimental and biological conditions and providing comprehensive and high-resolution information at molecular levels. The research interests in toxicogenomics center on key issues involving the quantification of molecular toxic effects, the linkage between molecular endpoints and phenotypic ones, the discernment of dose-response and pharmacokinetics relationships, as well as the integration of bioinformatics into predictive toxicology. In particular, the increasingly complex and voluminous toxicogenomics data pose great analytical challenges. The existing bioinformatics tools are incompatible with the high dimensionality and temporal dynamics of the data, possibly leading to unreliable and misinterpretation of the potential toxicity connotation. The objectives of this dissertation are to develop and demonstrate new or improved methodology that better address the challenges and limitations in high dimensional time series toxicogenomics data analysis for critical bioinformatics application such as toxicity mechanism identification, toxicants classification, and for predictive toxicology knowledge discovery. In this study, we develop new or improve bioinformatics data analysis algorithms so that they are capable of processing high dimensional time series toxicogenomics data, therefore better capture and reflect the dynamics of cellular response to toxicants. We also prove the potential and validity of the incorporation of various molecular disturbance/effect quantifiers into various functional toxicogenomics bioinformatics to provide quantitative insights into the toxicant-induced cellular molecular responses at individual gene, specific pathway and system levels. In addition, we demonstrate the effectives of unsupervised bioinformatics tools for mining new, more in depth, much-detailed and fundamental knowledge and understanding of toxicological information at molecular level. This research could generate new information to fill in the urgent knowledge gaps in toxicogenomics that present barriers to the realization of predictive toxicology and make contributions to several fields including toxicology, bioinformatics and environmental science.
Download or read book Data Mining and Applications in Genomics written by Sio-Iong Ao and published by Springer Science & Business Media. This book was released on 2008-09-25 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford. It provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Data Mining and Applications in Genomics offers state of the art of tremendous advances in data mining algorithms and applications in genomics and also serves as an excellent reference work for researchers and graduate students working on data mining algorithms and applications in genomics.
Download or read book Beyond Expression Profile Clustering written by and published by . This book was released on 2016 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present methods for comparative exploration of high-dimensional biological time-series datasets. In this work we focus on the analysis of gene expression data measured by either microarry or RNAseq. However, the methods we develop are applicable to a range of other high-dimensional datasets, including protein and metabolite datasets, as they become increasingly available. The datasets we work with consist of expression profiles for thousands or tens of thousands of gene. Each of these expression profiles is a time series of expression values for a specific gene. Expression profiles for the genes are sampled under two or more related conditions such as chemical/vehicle exposure or gene suppression/overexpression. Identifying similarities and differences across expression profiles can provide a better understanding of the relationships among the experimental conditions in the dataset. In pursuit of this, we present three novel methods for the analysis of multi-conditional time-series datasets. First, we introduce an approach called Multi-View Clustering. Given a dataset with expression profiles measured under two related conditions, Multi-View Clustering clusters genes on both expression profiles and alignments, where the alignment for a gene represents the correspondences between its expression profiles across conditions. Second, we describe Stable Alignment Clustering, an improved alignment clustering approach which harnesses a common method of assessing cluster stability to counteract instability in alignment clusters. Third,we present ConditionalMotif Finding a method for detecting patterns in time-series datasets where the genes are measured under more than two conditions. By grouping genes and conditions into subsets based on alignment similarity across conditions, this method characterizes the experimental conditions in the dataset by a set of motifs: gene/condition clusters that describe common patterns of change in the dataset.
Download or read book Data Clustering Theory Algorithms and Applications Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Download or read book Markov Processes for Stochastic Modeling written by Oliver Ibe and published by Newnes. This book was released on 2013-05-22 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. Presents both the theory and applications of the different aspects of Markov processes Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
Download or read book Data Mining in Clinical Medicine written by Carlos Fernández Llatas and published by Humana Press. This book was released on 2014-11-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume complies a set of Data Mining techniques and new applications in real biomedical scenarios. Chapters focus on innovative data mining techniques, biomedical datasets and streams analysis, and real applications. Written in the highly successful Methods in Molecular Biology series format, chapters are thought to show to Medical Doctors and Engineers the new trends and techniques that are being applied to Clinical Medicine with the arrival of new Information and Communication technologies Authoritative and practical, Data Mining in Clinical Medicine seeks to aid scientists with new approaches and trends in the field.
Download or read book Data Mining for Biomedical Applications written by Jinyan Li and published by Springer Science & Business Media. This book was released on 2006-03-23 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with one keynote talk were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections
Download or read book Data Mining written by Mehmed Kantardzic and published by John Wiley & Sons. This book was released on 2019-11-12 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.
Download or read book RNA Seq Analysis Methods Applications and Challenges written by Filippo Geraci and published by Frontiers Media SA. This book was released on 2020-06-08 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Genome Data Analysis written by Ju Han Kim and published by Springer. This book was released on 2019-04-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.
Download or read book Bioinformatics for Beginners written by Supratim Choudhuri and published by Elsevier. This book was released on 2014-05-09 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. Avoids non-essential coverage, yet fully describes the field for beginners Explains the molecular basis of evolution to place bioinformatic analysis in biological context Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools Contains over 100 figures that aid in concept discovery and illustration
Download or read book Applications of Toxicogenomic Technologies to Predictive Toxicology and Risk Assessment written by National Research Council and published by National Academies Press. This book was released on 2007-11-19 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new field of toxicogenomics presents a potentially powerful set of tools to better understand the health effects of exposures to toxicants in the environment. At the request of the National Institute of Environmental Health Sciences, the National Research Council assembled a committee to identify the benefits of toxicogenomics, the challenges to achieving them, and potential approaches to overcoming such challenges. The report concludes that realizing the potential of toxicogenomics to improve public health decisions will require a concerted effort to generate data, make use of existing data, and study data in new waysâ€"an effort requiring funding, interagency coordination, and data management strategies.
Download or read book Fundamentals of Data Mining in Genomics and Proteomics written by Werner Dubitzky and published by Springer Science & Business Media. This book was released on 2007-04-13 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Subspace Latent Structure and Feature Selection written by Craig Saunders and published by Springer Science & Business Media. This book was released on 2006-05-16 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many of the papers in this proceedings volume were presented at the PASCAL Workshop entitled Subspace, Latent Structure and Feature Selection Techniques: Statistical and Optimization Perspectives which took place in Bohinj, Slovenia during February, 23–25 2005.
Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.
Download or read book Computational Biomedicine written by Peter Coveney and published by Oxford University Press, USA. This book was released on 2014-06 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Biomedicine unifies the different strands of a broad-ranging subject to demonstrate the power of a tool that has the potential to revolutionise our understanding of the human body, and the therapeutic strategies available to maintain and protect it.
Download or read book Toxicity Testing in the 21st Century written by National Research Council and published by National Academies Press. This book was released on 2007-10-05 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in molecular biology and toxicology are paving the way for major improvements in the evaluation of the hazards posed by the large number of chemicals found at low levels in the environment. The National Research Council was asked by the U.S. Environmental Protection Agency to review the state of the science and create a far-reaching vision for the future of toxicity testing. The book finds that developing, improving, and validating new laboratory tools based on recent scientific advances could significantly improve our ability to understand the hazards and risks posed by chemicals. This new knowledge would lead to much more informed environmental regulations and dramatically reduce the need for animal testing because the new tests would be based on human cells and cell components. Substantial scientific efforts and resources will be required to leverage these new technologies to realize the vision, but the result will be a more efficient, informative and less costly system for assessing the hazards posed by industrial chemicals and pesticides.
