Machine Learning Methods For High Dimensional Data And Multimodal Single Cell Data

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Computational Methods for Single-Cell Data Analysis

Author : Guo-Cheng Yuan
Publisher : Humana Press
ISBN 13 : 9781493990566
Total Pages : 271 pages
Book Rating : 4.9/5 (95 download)

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Book Synopsis Computational Methods for Single-Cell Data Analysis by : Guo-Cheng Yuan

Download or read book Computational Methods for Single-Cell Data Analysis written by Guo-Cheng Yuan and published by Humana Press. This book was released on 2019-02-14 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.

Machine Learning Methods for Multi-Omics Data Integration

Author : Abedalrhman Alkhateeb
Publisher : Springer Nature
ISBN 13 : 303136502X
Total Pages : 171 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Machine Learning Methods for Multi-Omics Data Integration by : Abedalrhman Alkhateeb

Download or read book Machine Learning Methods for Multi-Omics Data Integration written by Abedalrhman Alkhateeb and published by Springer Nature. This book was released on 2023-12-15 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays. Large-scale data sets for multiple omics platforms, including genomics, transcriptomics, proteomics, and metabolomics, have become more accessible and cost-effective over time. Integrating multi-omics data has become increasingly important in many research fields, such as bioinformatics, genomics, and systems biology. This integration allows researchers to understand complex interactions between biological molecules and pathways. It enables us to comprehensively understand complex biological systems, leading to new insights into disease mechanisms, drug discovery, and personalized medicine. Still, integrating various heterogeneous data types into a single learning model also comes with challenges. In this regard, learning algorithms have been vital in analyzing and integrating these large-scale heterogeneous data sets into one learning model. This book overviews the latest multi-omics technologies, machine learning techniques for data integration, and multi-omics databases for validation. It covers different types of learning for supervised and unsupervised learning techniques, including standard classifiers, deep learning, tensor factorization, ensemble learning, and clustering, among others. The book categorizes different levels of integrations, ranging from early, middle, or late-stage among multi-view models. The underlying models target different objectives, such as knowledge discovery, pattern recognition, disease-related biomarkers, and validation tools for multi-omics data. Finally, the book emphasizes practical applications and case studies, making it an essential resource for researchers and practitioners looking to apply machine learning to their multi-omics data sets. The book covers data preprocessing, feature selection, and model evaluation, providing readers with a practical guide to implementing machine learning techniques on various multi-omics data sets.

Relative Distribution Methods in the Social Sciences

Author : Mark S. Handcock
Publisher : Springer Science & Business Media
ISBN 13 : 0387226583
Total Pages : 272 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Relative Distribution Methods in the Social Sciences by : Mark S. Handcock

Download or read book Relative Distribution Methods in the Social Sciences written by Mark S. Handcock and published by Springer Science & Business Media. This book was released on 2006-05-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods.

Handbook of Machine Learning Applications for Genomics

Author : Sanjiban Sekhar Roy
Publisher : Springer Nature
ISBN 13 : 9811691584
Total Pages : 222 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Handbook of Machine Learning Applications for Genomics by : Sanjiban Sekhar Roy

Download or read book Handbook of Machine Learning Applications for Genomics written by Sanjiban Sekhar Roy and published by Springer Nature. This book was released on 2022-06-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.

Advances in methods and tools for multi-omics data analysis

Author : Ornella Cominetti
Publisher : Frontiers Media SA
ISBN 13 : 2832523420
Total Pages : 184 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Advances in methods and tools for multi-omics data analysis by : Ornella Cominetti

Download or read book Advances in methods and tools for multi-omics data analysis written by Ornella Cominetti and published by Frontiers Media SA. This book was released on 2023-05-12 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Second International Conference on Image Processing and Capsule Networks

Author : Joy Iong-Zong Chen
Publisher : Springer Nature
ISBN 13 : 3030847608
Total Pages : 840 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Second International Conference on Image Processing and Capsule Networks by : Joy Iong-Zong Chen

Download or read book Second International Conference on Image Processing and Capsule Networks written by Joy Iong-Zong Chen and published by Springer Nature. This book was released on 2021-09-09 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications. The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.

Machine Learning and Mathematical Models for Single-Cell Data Analysis

Author : Le Ou-Yang
Publisher : Frontiers Media SA
ISBN 13 : 2832501842
Total Pages : 118 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Machine Learning and Mathematical Models for Single-Cell Data Analysis by : Le Ou-Yang

Download or read book Machine Learning and Mathematical Models for Single-Cell Data Analysis written by Le Ou-Yang and published by Frontiers Media SA. This book was released on 2022-11-29 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt:

10 Years of frontiers in genetics: Past discoveries, current challenges and future perspectives

Author : William C. Cho
Publisher : Frontiers Media SA
ISBN 13 : 283252477X
Total Pages : 427 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis 10 Years of frontiers in genetics: Past discoveries, current challenges and future perspectives by : William C. Cho

Download or read book 10 Years of frontiers in genetics: Past discoveries, current challenges and future perspectives written by William C. Cho and published by Frontiers Media SA. This book was released on 2023-06-02 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Detection Methods in Precision Medicine

Author : Mengsu (Michael) Yang
Publisher : Royal Society of Chemistry
ISBN 13 : 1788019962
Total Pages : 389 pages
Book Rating : 4.7/5 (88 download)

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Book Synopsis Detection Methods in Precision Medicine by : Mengsu (Michael) Yang

Download or read book Detection Methods in Precision Medicine written by Mengsu (Michael) Yang and published by Royal Society of Chemistry. This book was released on 2020-12-10 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision medicine is a topical subject that attracts tremendous attention from scientific and medical communities, being set to transform health care in the future. This book will be among the first to cover the detection methods for precision medicine. The first section provides an overview of the biomarkers used for precision medicine, such as proteins, nucleic acids, and metabolites. The coverage then turns to sequencing techniques and their applications, and other bioanalytical techniques, including mass spectrometry for proteome and phosphoproteome analysis, immunological methods and droplet technologies. The final sections include biosensors applied to precision medicine and clinical applications. This book provides a reference for researchers and students interested and working in the development of bioanalytical techniques for clinical applications. It provides a useful introduction for physicians and medical laboratory technologists to the recent advances in detection methods for precision medicine.

Artificial Intelligence

Author :
Publisher : Elsevier
ISBN 13 : 0443137641
Total Pages : 260 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Artificial Intelligence by :

Download or read book Artificial Intelligence written by and published by Elsevier. This book was released on 2023-09-11 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence, Volume 49 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics. Chapters in this new release include AI Teacher-Student based Adaptive Structural Deep Learning Model and Its Estimating Uncertainty of Image Data, Machine-derived Intelligence: Computations Beyond the Null Hypothesis, Object oriented basis of artificial intelligence methodologies I in Judicial Systems in India, Artificial Intelligence in Systems Biology, Machine-Learning in Geometry and Physics, Innovation and Machine Learning: Crowdsourcing Open-Source Natural Language Processing (NLP) Algorithms to Advance Public Health Surveillance, and more. Other chapters cover Learning and identity testing of Markov chains, Data privacy for machine learning and statistics, and The interface between AI and Mathematics. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Handbook of Statistics series - Includes the latest information on Artificial Intelligence

From Unimodal to Multimodal Machine Learning

Author : Blaž Škrlj
Publisher : Springer Nature
ISBN 13 : 3031570162
Total Pages : 78 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis From Unimodal to Multimodal Machine Learning by : Blaž Škrlj

Download or read book From Unimodal to Multimodal Machine Learning written by Blaž Škrlj and published by Springer Nature. This book was released on with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Single-cell analysis on the pathophysiology of autoimmune diseases

Author : Shiang-Jong Tzeng
Publisher : Frontiers Media SA
ISBN 13 : 2832551637
Total Pages : 213 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Single-cell analysis on the pathophysiology of autoimmune diseases by : Shiang-Jong Tzeng

Download or read book Single-cell analysis on the pathophysiology of autoimmune diseases written by Shiang-Jong Tzeng and published by Frontiers Media SA. This book was released on 2024-07-11 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite increasing research to facilitate the understanding of the pathophysiology of autoimmune disorders, the exact cause of the incident of autoimmunity is unknown. Current concepts on the occurrence of autoimmune diseases are thought to involve autoantigens, genetic predisposition, disease triggers, and the breakdown of immune tolerance. In addition to the breakdown of immunological tolerance, one key characteristic of autoimmune disease is that within a single disease there is considerable variability in the clinical manifestation and severity in patients. Single-cell omics have emerged as an effective means of unraveling the complexity and heterogeneity of chronic disease development and therapeutic responses. Recently, advances in cutting-edge spatial profiling of diverse cell types have increased our understanding of how distinct cells interact and orchestrate at specific locations across a tissue landscape in both physiological and pathological contexts at the single-cell level.

Handbook of Computational Neurodegeneration

Author : Panagiotis Vlamos
Publisher : Springer Nature
ISBN 13 : 3319759221
Total Pages : 1031 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Handbook of Computational Neurodegeneration by : Panagiotis Vlamos

Download or read book Handbook of Computational Neurodegeneration written by Panagiotis Vlamos and published by Springer Nature. This book was released on 2023-07-25 with total page 1031 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Computational Neurodegeneration provides a comprehensive overview of the field and thus bridges the gap between standard textbooks of research on neurodegeneration and dispersed publications for specialists that have a narrowed focus on computational methods to study this complicated process. The handbook reviews the central issues and methodological approaches related to the field for which the reader pursues a thorough overview. It also conveys more advanced knowledge, thus serving both as an introductory text and as a starting point for an in-depth study of a specific area, as well as a quick reference source for the expert by reflecting the state of the art and future prospects. The book includes topics that are usually missing in standard textbooks and that are only marginally represented in the specific literature. The broad scope of this handbook is reflected by five major parts that facilitate an integration of computational concepts, methods and applications in the study of neurodegeneration. Each part is intended to stand on its own, giving an overview of the topic and the most important problems and approaches, which are supported by examples, practical applications, and proposed methodologies. The basic concepts and knowledge, standard procedures and methods are presented, as well as recent advances and new perspectives.

Biocomputing 2021 - Proceedings Of The Pacific Symposium

Author : Russ B Altman
Publisher : World Scientific
ISBN 13 : 9811232717
Total Pages : 380 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Biocomputing 2021 - Proceedings Of The Pacific Symposium by : Russ B Altman

Download or read book Biocomputing 2021 - Proceedings Of The Pacific Symposium written by Russ B Altman and published by World Scientific. This book was released on 2020-11-24 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pacific Symposium on Biocomputing (PSB) 2021 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2021 will be held on a virtual platform at psb.stanford.edu/ on January 5-7, 2021. Tutorials and workshops will be offered prior to the start of the conference.PSB 2021 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Bioinformatics Research and Applications

Author : Wei Peng
Publisher : Springer Nature
ISBN 13 : 9819751284
Total Pages : 533 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Bioinformatics Research and Applications by : Wei Peng

Download or read book Bioinformatics Research and Applications written by Wei Peng and published by Springer Nature. This book was released on 2024 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19-21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

ICDSMLA 2019

Author : Amit Kumar
Publisher : Springer Nature
ISBN 13 : 9811514208
Total Pages : 2010 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis ICDSMLA 2019 by : Amit Kumar

Download or read book ICDSMLA 2019 written by Amit Kumar and published by Springer Nature. This book was released on 2020-05-19 with total page 2010 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-impact articles from the 1st International Conference on Data Science, Machine Learning & Applications 2019. It highlights the latest developments in the areas of Artificial Intelligence, Machine Learning, Soft Computing, Human–Computer Interaction and various data science & machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.

Learning to Classify Text Using Support Vector Machines

Author : Thorsten Joachims
Publisher : Springer Science & Business Media
ISBN 13 : 079237679X
Total Pages : 228 pages
Book Rating : 4.7/5 (923 download)

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Book Synopsis Learning to Classify Text Using Support Vector Machines by : Thorsten Joachims

Download or read book Learning to Classify Text Using Support Vector Machines written by Thorsten Joachims and published by Springer Science & Business Media. This book was released on 2002-04-30 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on ideas from Support Vector Machines (SVMs), Learning To Classify Text Using Support Vector Machines presents a new approach to generating text classifiers from examples. The approach combines high performance and efficiency with theoretical understanding and improved robustness. In particular, it is highly effective without greedy heuristic components. The SVM approach is computationally efficient in training and classification, and it comes with a learning theory that can guide real-world applications. Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a statistical learning model of text classification. In addition, it includes an overview of the field of text classification, making it self-contained even for newcomers to the field. This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.