Machine Learning For Large Scale Genomics

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Artificial Intelligence

Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1789840171
Total Pages : 142 pages
Book Rating : 4.7/5 (898 download)

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Book Synopsis Artificial Intelligence by :

Download or read book Artificial Intelligence written by and published by BoD – Books on Demand. This book was released on 2019-07-31 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is taking on an increasingly important role in our society today. In the early days, machines fulfilled only manual activities. Nowadays, these machines extend their capabilities to cognitive tasks as well. And now AI is poised to make a huge contribution to medical and biological applications. From medical equipment to diagnosing and predicting disease to image and video processing, among others, AI has proven to be an area with great potential. The ability of AI to make informed decisions, learn and perceive the environment, and predict certain behavior, among its many other skills, makes this application of paramount importance in today's world. This book discusses and examines AI applications in medicine and biology as well as challenges and opportunities in this fascinating area.

Genomics-Assisted Crop Improvement

Author : R.K. Varshney
Publisher : Springer Science & Business Media
ISBN 13 : 1402062958
Total Pages : 405 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Genomics-Assisted Crop Improvement by : R.K. Varshney

Download or read book Genomics-Assisted Crop Improvement written by R.K. Varshney and published by Springer Science & Business Media. This book was released on 2007-12-12 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This superb volume provides a critical assessment of genomics tools and approaches for crop breeding. Volume 1 presents the status and availability of genomic resources and platforms, and also devises strategies and approaches for effectively exploiting genomics research. Volume 2 goes into detail on a number of case studies of several important crop and plant species that summarize both the achievements and limitations of genomics research for crop improvement.

Computational Genomics with R

Author : Altuna Akalin
Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 463 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Learning Deep Architectures for AI

Author : Yoshua Bengio
Publisher : Now Publishers Inc
ISBN 13 : 1601982941
Total Pages : 145 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Learning Deep Architectures for AI by : Yoshua Bengio

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.

The Maize Genome

Author : Jeffrey Bennetzen
Publisher : Springer
ISBN 13 : 3319974270
Total Pages : 390 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis The Maize Genome by : Jeffrey Bennetzen

Download or read book The Maize Genome written by Jeffrey Bennetzen and published by Springer. This book was released on 2018-11-24 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses advances in our understanding of the structure and function of the maize genome since publication of the original B73 reference genome in 2009, and the progress in translating this knowledge into basic biology and trait improvement. Maize is an extremely important crop, providing a large proportion of the world’s human caloric intake and animal feed, and serving as a model species for basic and applied research. The exceptionally high level of genetic diversity within maize presents opportunities and challenges in all aspects of maize genetics, from sequencing and genotyping to linking genotypes to phenotypes. Topics covered in this timely book range from (i) genome sequencing and genotyping techniques, (ii) genome features such as centromeres and epigenetic regulation, (iii) tools and resources available for trait genomics, to (iv) applications of allele mining and genomics-assisted breeding. This book is a valuable resource for researchers and students interested in maize genetics and genomics.

Machine Learning in Bioinformatics

Author : Yanqing Zhang
Publisher : John Wiley & Sons
ISBN 13 : 0470397411
Total Pages : 476 pages
Book Rating : 4.4/5 (73 download)

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Book Synopsis Machine Learning in Bioinformatics by : Yanqing Zhang

Download or read book Machine Learning in Bioinformatics written by Yanqing Zhang and published by John Wiley & Sons. This book was released on 2009-02-23 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to machine learning methods and their applications to problems in bioinformatics Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels.

Advanced Lectures on Machine Learning

Author : Olivier Bousquet
Publisher : Springer
ISBN 13 : 3540286500
Total Pages : 249 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Advanced Lectures on Machine Learning by : Olivier Bousquet

Download or read book Advanced Lectures on Machine Learning written by Olivier Bousquet and published by Springer. This book was released on 2011-03-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references. Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning.

AACR 2019 Proceedings: Abstracts 1-2748

Author : American Association for Cancer Research
Publisher : Coe Truman International, LLC
ISBN 13 : 0463198565
Total Pages : 2881 pages
Book Rating : 4.4/5 (631 download)

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Book Synopsis AACR 2019 Proceedings: Abstracts 1-2748 by : American Association for Cancer Research

Download or read book AACR 2019 Proceedings: Abstracts 1-2748 written by American Association for Cancer Research and published by Coe Truman International, LLC. This book was released on 2019-03-08 with total page 2881 pages. Available in PDF, EPUB and Kindle. Book excerpt: American Association for Cancer Research 2019 Proceedings: Abstracts 1-2748 - Part A

Big Data Analytics in Genomics

Author : Ka-Chun Wong
Publisher : Springer
ISBN 13 : 3319412795
Total Pages : 426 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Big Data Analytics in Genomics by : Ka-Chun Wong

Download or read book Big Data Analytics in Genomics written by Ka-Chun Wong and published by Springer. This book was released on 2016-10-24 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.

Methods and Applications of Artificial Intelligence

Author : George A. Vouros
Publisher : Springer Science & Business Media
ISBN 13 : 3540219374
Total Pages : 561 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Methods and Applications of Artificial Intelligence by : George A. Vouros

Download or read book Methods and Applications of Artificial Intelligence written by George A. Vouros and published by Springer Science & Business Media. This book was released on 2004-04-22 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: Arti?cial intelligence has attracted a renewed interest from distinguished sci- tists and has again raised new, more realistic this time, expectations for future advances regarding the development of theories, models and techniques and the use of them in applications pervading many areas of our daily life. The borders of human-level intelligence are still very far away and possibly unknown. Nev- theless, recent scienti?c work inspires us to work even harder in our exploration of the unknown lands of intelligence. This volume contains papers selected for presentation at the 3rd Hellenic Conference on Arti?cial Intelligence (SETN 2004), the o?cial meeting of the Hellenic Society for Arti?cial Intelligence (EETN). The ?rst meeting was held in the University of Piraeus, 1996 and the second in the Aristotle University of Thessaloniki (AUTH), 2002. SETN conferences play an important role in the dissemination of the in- vative and high-quality scienti?c results in arti?cial intelligence which are being produced mainly by Greek scientists in institutes all over the world. However, the most important e?ect of SETN conferences is that they provide the context in which people meet and get to know each other, as well as a very good opp- tunity for students to get closer to the results of innovative arti?cial intelligence research.

Precision Public Health

Author : Tarun Weeramanthri
Publisher : Frontiers Media SA
ISBN 13 : 2889455017
Total Pages : 149 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Precision Public Health by : Tarun Weeramanthri

Download or read book Precision Public Health written by Tarun Weeramanthri and published by Frontiers Media SA. This book was released on 2018-06-25 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision Public Health is a new and rapidly evolving field, that examines the application of new technologies to public health policy and practice. It draws on a broad range of disciplines including genomics, spatial data, data linkage, epidemiology, health informatics, big data, predictive analytics and communications. The hope is that these new technologies will strengthen preventive health, improve access to health care, and reach disadvantaged populations in all areas of the world. But what are the downsides and what are the risks, and how can we ensure the benefits flow to those population groups most in need, rather than simply to those individuals who can afford to pay? This is the first collection of theoretical frameworks, analyses of empirical data, and case studies to be assembled on this topic, published to stimulate debate and promote collaborative work.

Next Steps for Functional Genomics

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
ISBN 13 : 0309676738
Total Pages : 201 pages
Book Rating : 4.3/5 (96 download)

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Book Synopsis Next Steps for Functional Genomics by : National Academies of Sciences, Engineering, and Medicine

Download or read book Next Steps for Functional Genomics written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-12-18 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the holy grails in biology is the ability to predict functional characteristics from an organism's genetic sequence. Despite decades of research since the first sequencing of an organism in 1995, scientists still do not understand exactly how the information in genes is converted into an organism's phenotype, its physical characteristics. Functional genomics attempts to make use of the vast wealth of data from "-omics" screens and projects to describe gene and protein functions and interactions. A February 2020 workshop was held to determine research needs to advance the field of functional genomics over the next 10-20 years. Speakers and participants discussed goals, strategies, and technical needs to allow functional genomics to contribute to the advancement of basic knowledge and its applications that would benefit society. This publication summarizes the presentations and discussions from the workshop.

Understanding Machine Learning

Author : Shai Shalev-Shwartz
Publisher : Cambridge University Press
ISBN 13 : 1107057132
Total Pages : 415 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Understanding Machine Learning by : Shai Shalev-Shwartz

Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVI

Author : Abdelkader Hameurlain
Publisher : Springer Nature
ISBN 13 : 3662623862
Total Pages : 197 pages
Book Rating : 4.6/5 (626 download)

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Book Synopsis Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVI by : Abdelkader Hameurlain

Download or read book Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVI written by Abdelkader Hameurlain and published by Springer Nature. This book was released on 2020-11-20 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 46th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised selected regular papers. Topics covered include an elastic framework for genomic data management, medical data cloud federations, temporal pattern mining, scalable schema discovery, load shedding, and selectivity estimation using linked Bayesian networks.

Fundamentals of Data Mining in Genomics and Proteomics

Author : Werner Dubitzky
Publisher : Springer Science & Business Media
ISBN 13 : 0387475095
Total Pages : 300 pages
Book Rating : 4.3/5 (874 download)

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Book Synopsis Fundamentals of Data Mining in Genomics and Proteomics by : Werner Dubitzky

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.

Special Topics in Information Technology

Author : Luigi Piroddi
Publisher : Springer Nature
ISBN 13 : 3030859185
Total Pages : 151 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Special Topics in Information Technology by : Luigi Piroddi

Download or read book Special Topics in Information Technology written by Luigi Piroddi and published by Springer Nature. This book was released on 2022-01-01 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.

Machine Learning and Systems Biology in Genomics and Health

Author : Shailza Singh
Publisher : Springer Nature
ISBN 13 : 9811659931
Total Pages : 239 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Machine Learning and Systems Biology in Genomics and Health by : Shailza Singh

Download or read book Machine Learning and Systems Biology in Genomics and Health written by Shailza Singh and published by Springer Nature. This book was released on 2022-02-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.