Proteome Informatics
Proteome Informatics

Author: Conrad Bessant

Publisher: Royal Society of Chemistry

Published: 2016-11-15

Total Pages: 429

ISBN-13: 1782626735

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The field of proteomics has developed rapidly over the past decade nurturing the need for a detailed introduction to the various informatics topics that underpin the main liquid chromatography tandem mass spectrometry (LC-MS/MS) protocols used for protein identification and quantitation. Proteins are a key component of any biological system, and monitoring proteins using LC-MS/MS proteomics is becoming commonplace in a wide range of biological research areas. However, many researchers treat proteomics software tools as a black box, drawing conclusions from the output of such tools without considering the nuances and limitations of the algorithms on which such software is based. This book seeks to address this situation by bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, so that users of proteomics data can be confident that they are using appropriate tools in suitable ways.

Genetics Meets Metabolomics
Genetics Meets Metabolomics

Author: Karsten Suhre

Publisher: Springer Science & Business Media

Published: 2012-06-15

Total Pages: 328

ISBN-13: 1461416892

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This book is written by leading researchers in the fields about the intersection of genetics and metabolomics which can lead to more comprehensive studies of inborn variation of metabolism.

Omics-Driven Crop Improvement for Stress Tolerance, volume II
Omics-Driven Crop Improvement for Stress Tolerance, volume II

Author: Weicong Qi

Publisher: Frontiers Media SA

Published: 2024-09-04

Total Pages: 139

ISBN-13: 2832554059

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Climate change and global warming are arising threats to ecology and agriculture, and the biotic and abiotic stresses on crop cultivation are becoming more severe. Simultaneously, hunger and poverty remain widespread around the world and are rather thriving with the global population increases, over-fertilization, and land degradation. Rising challenges therefore make the adaptation of agriculture to the environment even more pivotal. Plant tolerance against various stress, including abiotic and biotic stresses mostly, is a classic topic and also a hot spot, of which the goal is to provide possibilities to improve the crops’ sustainability in coping with varied environments. Sustainable crop improvement can help feed the growing population in such an era of shrinking arable land and dwindling water resources. Worldwide, the inexorable exposure of plants to the environment makes crops always come to cross biotic and abiotic stresses, which constantly affect the food supply. Scientists have devoted efforts to improve crop resistance against devastating stressors such as drought, salt, nutrition deprivation, pests and pathogens, etc., and save yields from destruction. With the explosive development of omics technologies, e.g., genomics, transcriptomics, proteomics, metabolomics, interactomics, and phenomics, crop improvement is embarking on a fire-new bioinformatics era. The integration of multi-omics will provide new perspectives to understand the intricate nature of stress response in crops

Learning to Classify Text Using Support Vector Machines
Learning to Classify Text Using Support Vector Machines

Author: Thorsten Joachims

Publisher: Springer Science & Business Media

Published: 2002-04-30

Total Pages: 228

ISBN-13: 079237679X

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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.

Biological Insights of Multi-Omics Technologies in Human Diseases
Biological Insights of Multi-Omics Technologies in Human Diseases

Author: Aarif Ali

Publisher: Elsevier

Published: 2024-05-23

Total Pages: 420

ISBN-13: 0443239703

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"Biological Insights of Multi-Omics Technologies in Human Diseases ́ provides detailed information about the basics of multi-omic technologies including ethics, historical perspective, science, drug discovery, and development and metabolism. With a strong focus on the practical application of omics approaches in cancer, cardiovascular, neurology, respiratory, viral, gastroenterology, autoimmune diseases, PCOS and tuberculosis, this book also includes special topics related to COVID-19 and Machine learning approaches. In 13 chapters this book provides comprehensive coverage of the challenges and opportunities facing the therapeutic implications of multi-omics from academic, regulatory, pharmaceutical, socio-ethical, and economic perspectives. The chapters are designed in a well-defined chronology such that readers will intuitively understand the central idea. This book is an ideal resource for health professionals, scientists and researchers, nutritionists, health practitioners, students, and all those who wish to broaden their knowledge in the allied field. • Explains the in-depth role of multi-omics on drug discovery/metabolism, diseases, and highlights progress in both the research and clinical areas of computation, as well as relevant implementation experience and challenges. • Describes the practice of multi-omic technologies in the treatment of several diseases.• Includes practical application and machine learning approaches of multi-omics.

Plant Metabolomics
Plant Metabolomics

Author: Kazuki Saito

Publisher: Springer Science & Business Media

Published: 2006-06-29

Total Pages: 351

ISBN-13: 3540297820

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Metabolomics – which deals with all metabolites of an organism – is a rapidly-emerging sector of post-genome research fields. It plays significant roles in a variety of fields from medicine to agriculture and holds a fundamental position in functional genomics studies and their application in plant biotechnology. This volume comprehensively covers plant metabolomics for the first time. The chapters offer cutting-edge information on analytical technology, bioinformatics and applications. They were all written by leading researchers who have been directly involved in plant metabolomics research throughout the world. Up-to-date information and future developments are described, thereby producing a volume which is a landmark of plant metabolomics research and a beneficial guideline to graduate students and researchers in academia, industry, and technology transfer organizations in all plant science fields.

Evolution of Translational Omics
Evolution of Translational Omics

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2012-09-13

Total Pages: 354

ISBN-13: 0309224187

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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Proteomics Data Analysis
Proteomics Data Analysis

Author: Daniela Cecconi

Publisher:

Published: 2021

Total Pages: 326

ISBN-13: 9781071616413

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This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.

Molecular Genetics and Emerging Therapies for Epithelial Ovarian Cancer: Basic Research and Clinical Perspectives
Molecular Genetics and Emerging Therapies for Epithelial Ovarian Cancer: Basic Research and Clinical Perspectives

Author: Stergios Boussios

Publisher: Frontiers Media SA

Published: 2023-11-06

Total Pages: 348

ISBN-13: 2832538436

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Epithelial ovarian cancer (EOC) is the most lethal gynecological disorder due to a lack of effective early detection strategies. Worldwide, approximately 230,000 women are diagnosed annually, whereas 150,000 die. It represents the seventh most commonly diagnosed cancer among women in the world with 5-year survival rate of 46%. More than one-fifth of EOC have been related to hereditary conditions. Considerable efforts have been made to implement screening of the general population to diagnose EOC early; nevertheless, this has been ineffective and there is no approved strategy. Nowadays, new approaches for early diagnosis and prevention based on molecular genomics are in development. Whole genome sequencing has established the potency of the somatic genome, characterised with diverse DNA repair deficiencies that can be used to stratify EOCs into distinct biological groups with predictive signatures of resistance or relapse. The incorporation of next-generation sequencing (NGS) into clinical practice remains challenging for two reasons. Firstly, the EOC risk is not clear for some of the included genes and secondly, the variant of uncertain significance rates increase as more genes are analyzed. Finally, beyond germline pathogenic variants, somatic mutations may also affect therapeutic choices, and as such upfront tumor sequencing may be equally important to NGS, particularly as we continue to challenge treatment paradigms in the first‐line management of EOC.