Statistical Methods For Annotation Analysis

DOWNLOAD

Download Statistical Methods For Annotation Analysis PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Statistical Methods For Annotation Analysis book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Statistical Methods For Annotation Analysis

DOWNLOAD
Author : Silviu Paun
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2022-01-13

Statistical Methods For Annotation Analysis written by Silviu Paun and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-13 with Computers categories.

Labelling data is one of the most fundamental activities in science, and has underpinned practice, particularly in medicine, for decades, as well as research in corpus linguistics since at least the development of the Brown corpus. With the shift towards Machine Learning in Artificial Intelligence (AI), the creation of datasets to be used for training and evaluating AI systems, also known in AI as corpora, has become a central activity in the field as well. Early AI datasets were created on an ad-hoc basis to tackle specific problems. As larger and more reusable datasets were created, requiring greater investment, the need for a more systematic approach to dataset creation arose to ensure increased quality. A range of statistical methods were adopted, often but not exclusively from the medical sciences, to ensure that the labels used were not subjective, or to choose among different labels provided by the coders. A wide variety of such methods is now in regular use. This book is meant to provide a survey of the most widely used among these statistical methods supporting annotation practice. As far as the authors know, this is the first book attempting to cover the two families of methods in wider use. The first family of methods is concerned with the development of labelling schemes and, in particular, ensuring that such schemes are such that sufficient agreement can be observed among the coders. The second family includes methods developed to analyze the output of coders once the scheme has been agreed upon, particularly although not exclusively to identify the most likely label for an item among those provided by the coders. The focus of this book is primarily on Natural Language Processing, the area of AI devoted to the development of models of language interpretation and production, but many if not most of the methods discussed here are also applicable to other areas of AI, or indeed, to other areas of Data Science.

Statistical Methods For Annotation Analysis

DOWNLOAD
Author : Silviu Paun
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Statistical Methods For Annotation Analysis written by Silviu Paun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

Labelling data is one of the most fundamental activities in science, and has underpinned practice, particularly in medicine, for decades, as well as research in corpus linguistics since at least the development of the Brown corpus. With the shift towards Machine Learning in Artificial Intelligence (AI), the creation of datasets to be used for training and evaluating AI systems, also known in AI as corpora, has become a central activity in the field as well. Early AI datasets were created on an ad-hoc basis to tackle specific problems. As larger and more reusable datasets were created, requiring greater investment, the need for a more systematic approach to dataset creation arose to ensure increased quality. A range of statistical methods were adopted, often but not exclusively from the medical sciences, to ensure that the labels used were not subjective, or to choose among different labels provided by the coders. A wide variety of such methods is now in regular use. This book is meantto provide a survey of the most widely used among these statistical methods supporting annotation practice. As far as the authors know, this is the first book attempting to cover the two families of methods in wider use. The first family of methods is concerned with the development of labelling schemes and, in particular, ensuring that such schemes are such that sufficient agreement can be observed among the coders. The second family includes methods developed to analyze the output of coders once the scheme has been agreed upon, particularly although not exclusively to identify the most likely label for an item among those provided by the coders. The focus of this book is primarily on Natural Language Processing, the area of AI devoted to the development of models of language interpretation and production, but many if not most of the methods discussed here are also applicable to other areas of AI, or indeed, to other areas of Data Science.

Advanced Statistical Methods For The Analysis Of Large Data Sets

DOWNLOAD
Author : Agostino Di Ciaccio
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-05

Advanced Statistical Methods For The Analysis Of Large Data Sets written by Agostino Di Ciaccio and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-05 with Mathematics categories.

The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”

Statistical Methods Computing And Resources For Genome Wide Association Studies

DOWNLOAD
Author : Riyan Cheng
language : en
Publisher: Frontiers Media SA
Release Date : 2021-08-24

Statistical Methods Computing And Resources For Genome Wide Association Studies written by Riyan Cheng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-24 with Science categories.

Statistical Methods For Meta Analysis

DOWNLOAD
Author : Larry V. Hedges
language : en
Publisher: Academic Press
Release Date : 2014-06-28

Statistical Methods For Meta Analysis written by Larry V. Hedges and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Mathematics categories.

The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.

Advances In Statistical Methods For The Genetic Dissection Of Complex Traits In Plants

DOWNLOAD
Author : Yuan-Ming Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2024-01-26

Advances In Statistical Methods For The Genetic Dissection Of Complex Traits In Plants written by Yuan-Ming Zhang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-26 with Science categories.

Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. However, there are still limits in current GWAS statistics. For example, (1) almost all the existing methods do not estimate additive and dominance effects in quantitative trait nucleotide (QTN) detection; (2) the methods for detecting QTN-by-environment interaction (QEI) are not straightforward and do not estimate additive and dominance effects as well as additive-by-environment and dominance-by-environment interaction effects, leading to unreliable results; and (3) no or too simple polygenic background controls have been employed in QTN-by-QTN interaction (QQI) detection. As a result, few studies of QEI and QQI for complex traits have been reported based on multiple-environment experiments. Recently, new statistical tools, including 3VmrMLM, have been developed to address these needs in GWAS. In 3VmrMLM, all the trait-associated effects, including QTN, QEI and QQI related effects, are compressed into a single effect-related vector, while all the polygenic backgrounds are compressed into a single polygenic effect matrix. These compressed parameters can be accurately and efficiently estimated through a unified mixed model analysis. To further validate these new GWAS methods, particularly 3VmrMLM, they should be rigorously tested in real data of various plants and a wide range of other species.

Data Processing Handbook For Complex Biological Data Sources

DOWNLOAD
Author : Gauri Misra
language : en
Publisher: Academic Press
Release Date : 2019-03-23

Data Processing Handbook For Complex Biological Data Sources written by Gauri Misra and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-23 with Science categories.

Data Processing Handbook for Complex Biological Data provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened. - Explains how to interpret enormous amounts of data generated using several experimental approaches in simple terms, thus relating biology and physics at the atomic level - Presents sample data files and explains the usage of equations and web servers cited in research articles to extract useful information from their own biological data - Discusses, in detail, raw data files, data processing strategies, and the web based sources relevant for data processing

Bioinformatics And Functional Genomics

DOWNLOAD
Author : Jonathan Pevsner
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-17

Bioinformatics And Functional Genomics written by Jonathan Pevsner and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-17 with Science categories.

The bestselling introduction to bioinformatics and genomics – now in its third edition Widely received in its previous editions, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline. Now in a thoroughly updated and expanded third edition, it continues to be the go-to source for students and professionals involved in biomedical research. This book provides up-to-the-minute coverage of the fields of bioinformatics and genomics. Features new to this edition include: Extensive revisions and a slight reorder of chapters for a more effective organization A brand new chapter on next-generation sequencing An expanded companion website, also updated as and when new information becomes available Greater emphasis on a computational approach, with clear guidance of how software tools work and introductions to the use of command-line tools such as software for next-generation sequence analysis, the R programming language, and NCBI search utilities The book is complemented by lavish illustrations and more than 500 figures and tables - many newly-created for the third edition to enhance clarity and understanding. Each chapter includes learning objectives, a problem set, pitfalls section, boxes explaining key techniques and mathematics/statistics principles, a summary, recommended reading, and a list of freely available software. Readers may visit a related Web page for supplemental information such as PowerPoints and audiovisual files of lectures, and videocasts of how to perform many basic operations: www.wiley.com/go/pevsnerbioinformatics. Bioinformatics and Functional Genomics, Third Edition serves as an excellent single-source textbook for advanced undergraduate and beginning graduate-level courses in the biological sciences and computer sciences. It is also an indispensable resource for biologists in a broad variety of disciplines who use the tools of bioinformatics and genomics to study particular research problems; bioinformaticists and computer scientists who develop computer algorithms and databases; and medical researchers and clinicians who want to understand the genomic basis of viral, bacterial, parasitic, or other diseases.

Big Data Analysis For Bioinformatics And Biomedical Discoveries

DOWNLOAD
Author : Shui Qing Ye
language : en
Publisher: CRC Press
Release Date : 2016-01-13

Big Data Analysis For Bioinformatics And Biomedical Discoveries written by Shui Qing Ye and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-13 with Computers categories.

Demystifies Biomedical and Biological Big Data AnalysesBig Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implem

Cardiac Gene Expression

DOWNLOAD
Author : Jun Zhang
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-03

Cardiac Gene Expression written by Jun Zhang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-03 with Science categories.

Cardiac Gene Expression: Methods and Protocols presents both cutting-edge and established methods for studying cardiac gene expression. The protocols provide a template for solid research, and cover the process through screening, analysis, characterization, and functional confirmation of novel genes or known genes with a new function. Section I, Cardiac Gene Expression Profiling: The Global Perspective, discusses several different approaches to examining, identifying, and analyzing changes in transcriptome gene expression. Section II, Cardiac Gene Regulation: Gene-Specific mRNA Measurement in the Myocardium, outlines more sensitive and gene-targeted expression methods. Section III, Cardiac Gene Regulation: Promoter Characterization in the Myocardium, provides protocols for the study of underlying gene regulation mechanisms by focusing on the interaction of transcription factors with their cognate cis binding elements. Section IV, In Silico Assessment of Regulatory cis-Elements and Gene Regulation, and Section V, Cardiac Single Network Polymorphisms, emphasize new analytical approaches for deciphering the functional elements buried in the 3 billion nucleotides of the human genome and other model genomes. The concluding section, Gene Overexpression and Targeting in the Myocardium, highlights methods that facilitate overexpression or cardiac-specific targeted gene deletion.