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Author: Santosh Kumar Upadhyay Publisher: Academic Press ISBN: 0128214635 Category : Science Languages : en Pages : 392
Book Description
The growth of human population has increased the demand for improved yield and quality of crops and horticultural plants. However, plant productivity continues to be threatened by stresses such as heat, cold, drought, heavy metals, UV radiations, bacterial and fungal pathogens, and insect pests. Long noncoding RNAs are associated with various developmental pathways, regulatory systems, abiotic and biotic stress responses and signaling, and can provide an alternative strategy for stress management in plants. Long Noncoding RNAs in Plants: Roles in development and stress provides the most recent advances in LncRNAs, including identification, characterization, and their potential applications and uses. Introductory chapters include the basic features and brief history of development of lncRNAs studies in plants. The book then provides the knowledge about the lncRNAs in various important agricultural and horticultural crops such as cereals, legumes, fruits, vegetables, and fiber crop cotton, and their roles and applications in abiotic and biotic stress management. - Includes the latest advances and research in long noncoding RNAs in plants - Provides alternative strategies for abiotic and biotic stress management in horticultural plants and agricultural crops - Focuses on the application and uses of long noncoding RNAs
Author: Santosh Kumar Upadhyay Publisher: Academic Press ISBN: 0128214635 Category : Science Languages : en Pages : 392
Book Description
The growth of human population has increased the demand for improved yield and quality of crops and horticultural plants. However, plant productivity continues to be threatened by stresses such as heat, cold, drought, heavy metals, UV radiations, bacterial and fungal pathogens, and insect pests. Long noncoding RNAs are associated with various developmental pathways, regulatory systems, abiotic and biotic stress responses and signaling, and can provide an alternative strategy for stress management in plants. Long Noncoding RNAs in Plants: Roles in development and stress provides the most recent advances in LncRNAs, including identification, characterization, and their potential applications and uses. Introductory chapters include the basic features and brief history of development of lncRNAs studies in plants. The book then provides the knowledge about the lncRNAs in various important agricultural and horticultural crops such as cereals, legumes, fruits, vegetables, and fiber crop cotton, and their roles and applications in abiotic and biotic stress management. - Includes the latest advances and research in long noncoding RNAs in plants - Provides alternative strategies for abiotic and biotic stress management in horticultural plants and agricultural crops - Focuses on the application and uses of long noncoding RNAs
Author: Mathieu Rederstorff Publisher: Humana ISBN: 9781493949038 Category : Medical Languages : en Pages : 0
Book Description
This volume contains state-of-the-art methods tackling all aspects of small non-coding RNAs biology. Small Non-Coding RNAs: Methods and Protocols guides readers through customized dedicated protocols and technologies that will be of valuable help to all those willing to contribute deciphering the numerous functions of small non-coding RNAs. Written in the highly successful Methods of 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 key tips on troubles troubleshooting and avoiding known pitfalls. Instructive and practical, Small Non-Coding RNAs: Methods and Protocols reaches out to biochemists, cellular and molecular biologists already working in the field of RNA biology and to those just starting to study small non-coding RNAs.
Author: Pierre Baldi Publisher: MIT Press ISBN: 9780262025065 Category : Computers Languages : en Pages : 492
Book Description
A guide to machine learning approaches and their application to the analysis of biological data. An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory, which is the situation in molecular biology. The goal in machine learning is to extract useful information from a body of data by building good probabilistic models—and to automate the process as much as possible. In this book Pierre Baldi and Søren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology. This new second edition contains expanded coverage of probabilistic graphical models and of the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.
Author: Ying Xu Publisher: World Scientific ISBN: 1860949827 Category : Medical Languages : en Pages : 494
Book Description
Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses.
Author: Altuna Akalin Publisher: CRC Press ISBN: 1498781861 Category : Mathematics Languages : en Pages : 463
Book Description
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.
Author: Jan Gorodkin Publisher: Humana ISBN: 9781627037082 Category : Science Languages : en Pages : 0
Book Description
The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes. However, a long series of striking discoveries, from RNA's ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere. However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In RNA Sequence, Structure, Function: Computational and Bioinformatic Methods, expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in more detailed aspects of the algorithms. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results. Thorough and intuitive, RNA Sequence, Structure, Function: Computational and Bioinformatic Methods aids scientists in continuing to study key methods and principles of RNA bioinformatics.
Author: Richard Durbin Publisher: Cambridge University Press ISBN: 113945739X Category : Science Languages : en Pages : 372
Book Description
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Author: Julia A. Chekanova Publisher: Humana Press ISBN: 9781493990443 Category : Science Languages : en Pages : 480
Book Description
This volume focuses on various approaches to studying long non-coding RNAs (lncRNAs), including techniques for finding lncRNAs, localization, and observing their functions. The chapters in this book cover how to catalog lncRNAs in various plant species; determining subcellular localization; protein interactions; structures; and RNA modifications. 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. Cutting-edge and innovative, Plant Long Non-Coding RNAs: Methods and Protocols is a valuable resource that aids researchers in understanding the functions of lncRNAs in different plant species, and helps them explore currently uncharted facets of plant biology.
Author: Jeffrey J P Tsai Publisher: World Scientific ISBN: 981320799X Category : Science Languages : en Pages : 233
Book Description
This compendium contains 10 chapters written by world renowned researchers with expertise in semantic computing, genome sequence analysis, biomolecular interaction, time-series microarray analysis, and machine learning algorithms.The salient feature of this book is that it highlights eight types of computational techniques to tackle different biomedical applications. These techniques include unsupervised learning algorithms, principal component analysis, fuzzy integral, graph-based ensemble clustering method, semantic analysis, interolog approach, molecular simulations and enzyme kinetics.The unique volume will be a useful reference material and an inspirational read for advanced undergraduate and graduate students, computer scientists, computational biologists, bioinformatics and biomedical professionals.
Author: Santosh Kumar Upadhyay
Author: Santosh Kumar Upadhyay
Author: Mathieu Rederstorff
Author: Pierre Baldi
Author: Ying Xu
Author: Altuna Akalin
Author: Jan Gorodkin
Author: Richard Durbin
Author: Julia A. Chekanova
Author: Jeffrey J P Tsai
Author: Bernhard Schölkopf