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Author: Khalid Rehman Hakeem
Publisher: Springer
ISBN: 3319671561
Category : Science
Languages : en
Pages : 465
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Book Description
This book: (i) introduces fundamental and applied bioinformatics research in the field of plant life sciences; (ii) enlightens the potential users towards the recent advances in the development and application of novel computational methods available for the analysis and integration of plant -omics data; (iii) highlights relevant databases, softwares, tools and web resources developed till date to make ease of access for researchers working to decipher plant responses towards stresses; and (iv) presents a critical cross-talks on the available high-throughput data in plant research. Therefore, in addition to being a reference for the professional researchers, it is also of great interest to students and their professors. Considering immense significance of plants for all lives on Earth, the major focus of research in plant biology has been to: (a) select plants that best fit the purposes of human, (b) develop crop plants superior in quality, quantity and farming practices when compared to natural (wild) plants, and (c) explore strategies to help plants to adapt biotic and abiotic/environmental stress factors. Accordingly the development of novel techniques and their applications have increased significantly in recent years. In particular, large amount of biological data have emerged from multi-omics approaches aimed at addressing numerous aspects of the plant systems under biotic or abiotic stresses. However, even though the field is evolving at a rapid pace, information on the cross-talks and/or critical digestion of research outcomes in the context of plant bioinformatics is scarce. “Plant Bioinformatics: Decoding the Phyta” is aimed to bridge this gap.
Author: Khalid Rehman Hakeem
Publisher: Springer
ISBN: 3319671561
Category : Science
Languages : en
Pages : 465
Get Book Here
Book Description
This book: (i) introduces fundamental and applied bioinformatics research in the field of plant life sciences; (ii) enlightens the potential users towards the recent advances in the development and application of novel computational methods available for the analysis and integration of plant -omics data; (iii) highlights relevant databases, softwares, tools and web resources developed till date to make ease of access for researchers working to decipher plant responses towards stresses; and (iv) presents a critical cross-talks on the available high-throughput data in plant research. Therefore, in addition to being a reference for the professional researchers, it is also of great interest to students and their professors. Considering immense significance of plants for all lives on Earth, the major focus of research in plant biology has been to: (a) select plants that best fit the purposes of human, (b) develop crop plants superior in quality, quantity and farming practices when compared to natural (wild) plants, and (c) explore strategies to help plants to adapt biotic and abiotic/environmental stress factors. Accordingly the development of novel techniques and their applications have increased significantly in recent years. In particular, large amount of biological data have emerged from multi-omics approaches aimed at addressing numerous aspects of the plant systems under biotic or abiotic stresses. However, even though the field is evolving at a rapid pace, information on the cross-talks and/or critical digestion of research outcomes in the context of plant bioinformatics is scarce. “Plant Bioinformatics: Decoding the Phyta” is aimed to bridge this gap.
Author: Jen-Tsung Chen
Publisher: John Wiley & Sons
ISBN: 1394209932
Category : Science
Languages : en
Pages : 612
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Book Description
Explore and advance bioinformatics and systems biology tools for crop breeding programs in this practical resource for researchers Plant biology and crop breeding have produced an immense amount of data in recent years, from genomics to interactome and beyond. Bioinformatics tools, which aim at analyzing the vast quantities of data produced by biological research and processes, have developed at a rapid pace to meet the challenges of this vast data trove. The resulting field of bioinformatics and systems biology is producing increasingly rich and transformative research. Bioinformatics for Plant Research and Crop Breeding offers an overview of this field, its recent advances, and its wider applications. Drawing on a range of analytical and data-science tools, its foundation on an in-silico platform acquired multi-omics makes it indispensable for scientists and researchers alike. It promises to become ever more relevant as new techniques for generating and organizing data continue to transform the field. Bioinformatics for Plant Research and Crop Breeding readers will also find: A focus on emerging trends in plant science, sustainable agriculture, and global food security Detailed discussion of topics including plant diversity, plant stresses, nanotechnology in agriculture, and many others Applications incorporating artificial intelligence, machine learning, deep learning and more Bioinformatics for Plant Research and Crop Breeding is ideal for researchers and scientists interested in the potential of OMICs, and bioinformatic tools to aid and develop crop improvement programs.
Author: Pradeep Sharma
Publisher: Academic Press
ISBN: 0323885993
Category : Technology & Engineering
Languages : en
Pages : 707
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Book Description
Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots. Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence. This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics. - Discusses integral aspects of molecular biology and pivotal tool sfor molecular breeding - Enables breeders to design cost-effective and efficient breeding strategies - Provides examples ofinnovative genome-wide marker (SSR, SNP) discovery - Explores both the theoretical and practical aspects of computational biology with focus on innovation processes - Covers recent trends of bioinformatics and different tools and techniques
Author: Christopher A. Cullis
Publisher: John Wiley & Sons
ISBN: 0471488585
Category : Science
Languages : en
Pages : 230
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Book Description
Plant research has stood at the forefront of the genomics revolution. One of the first genome projects, the sequencing of the commonly used model organism Arabidopsis, has already yielded important results for the study of a broad array of crops such as corn and soybeans. With crop and food bioengineering only in its infancy, the need to understand the fundamental genetic mechanisms of plants will only become more pressing. A comprehensive guide to this fascinating area of genomics, Plant Genomics and Proteomics presents an integrated, broadly accessible treatment of the complex relationship between the genome, transcriptome, and proteome of plants. This clearly written text introduces the reader to the range of molecular techniques applicable to investigating the unique facets of plant growth, development, and response to the environment. Coverage includes: Functional and structural genomics addressed within the context of current techniques and challenges to come How to utilize DNA and protein sequence data Practical considerations for choosing and employing the most commonly available computer applications A review of applications for biotechnology, including genetic modification and defense against pathogens Bioinformatics tools and Web resources Numerous examples from the latest research throughout Assuming no specialized knowledge of plant biology on the part of its reader, Plant Genomics and Proteomics provides an invaluable resource for students and researchers in biotechnology, plant biology, genomics, and bioinformatics.
Author: S. M. Paul Khurana
Publisher: Springer Nature
ISBN: 9811384991
Category : Science
Languages : en
Pages : 671
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Book Description
Refinement in sequencing technologies and potential of genomic research resulted in meteoric growth of biological information such as sequences of DNA, RNA and protein requiring databases for efficient storage, management and retrieval of the biological information. Also, computational algorithms for analysis of these colossal data became a vital aspect of biological sciences. The work aims to show the process of turning bioscience innovation into companies and products, covering the basic science, the translation of science into technology. Due to rapid developments, there seems to be no basic difference between the pharmaceutical industry and the biotechnological industry. However, approved products in the pipeline and renewed public confidence make it one of the most promising areas of economic growth in the near future. India offers a huge market for the products as well as cheap manufacturing base for export. The book is a sincere work of compilation of new and recent advances in the topic of concern through various innovative researches and scientific opinion therefrom. The book is dedicated to the readers who will definitely find it interesting and knowledgeable in carrying out their respective researches in different aspects of applied microbiology and biotechnology.
Author: Vijai Bhadauria
Publisher: CAISTER ACADEMIC Press
ISBN: 9781910190654
Category : Science
Languages : en
Pages : 0
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Book Description
A timely and useful review of current developments in next-generation sequencing aimed at plant geneticists and crop scientists. Scientists review developments in next-generation sequencing and bioinformatics and discuss their application in understanding and improving agronomic traits such as yield, drought tolerance and disease resistance.
Author: Mohammad Yaseen Sofi
Publisher: Academic Press
ISBN: 0323911293
Category : Medical
Languages : en
Pages : 268
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Book Description
Bioinformatics for Everyone provides a brief overview on currently used technologies in the field of bioinformatics—interpreted as the application of information science to biology— including various online and offline bioinformatics tools and softwares. The book presents valuable knowledge in a simplified way to help students and researchers easily apply bioinformatics tools and approaches to their research and lab routines. Several protocols and case studies that can be reproduced by readers to suit their needs are also included. - Explains the most relevant bioinformatics tools available in a didactic manner so that readers can easily apply them to their research - Includes several protocols that can be used in different types of research work or in lab routines - Discusses upcoming technologies and their impact on biological/biomedical sciences
Author: Rabinarayan Satpathy
Publisher: John Wiley & Sons
ISBN: 111978560X
Category : Computers
Languages : en
Pages : 439
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Book Description
Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning 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. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.
Author: Noor Ahmad Shaik
Publisher: Springer
ISBN: 3030026345
Category : Science
Languages : en
Pages : 410
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Book Description
Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it mostly focuses on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquire these basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes. Unlike other bioinformatics books which are mostly theoretical, this book provides practical examples for the readers on state-of-the-art open source tools to solve biological problems. Flow charts of experiments, graphical illustrations, and mock data are included for quick reference. Volume I is therefore an ideal companion for students and early stage professionals wishing to master this blooming field.
Author: Tandy Warnow
Publisher: Springer
ISBN: 3030108376
Category : Computers
Languages : en
Pages : 426
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Book Description
This volume presents a compelling collection of state-of-the-art work in algorithmic computational biology, honoring the legacy of Professor Bernard M.E. Moret in this field. Reflecting the wide-ranging influences of Prof. Moret’s research, the coverage encompasses such areas as phylogenetic tree and network estimation, genome rearrangements, cancer phylogeny, species trees, divide-and-conquer strategies, and integer linear programming. Each self-contained chapter provides an introduction to a cutting-edge problem of particular computational and mathematical interest. Topics and features: addresses the challenges in developing accurate and efficient software for the NP-hard maximum likelihood phylogeny estimation problem; describes the inference of species trees, covering strategies to scale phylogeny estimation methods to large datasets, and the construction of taxonomic supertrees; discusses the inference of ultrametric distances from additive distance matrices, and the inference of ancestral genomes under genome rearrangement events; reviews different techniques for inferring evolutionary histories in cancer, from the use of chromosomal rearrangements to tumor phylogenetics approaches; examines problems in phylogenetic networks, including questions relating to discrete mathematics, and issues of statistical estimation; highlights how evolution can provide a framework within which to understand comparative and functional genomics; provides an introduction to Integer Linear Programming and its use in computational biology, including its use for solving the Traveling Salesman Problem. Offering an invaluable source of insights for computer scientists, applied mathematicians, and statisticians, this illuminating volume will also prove useful for graduate courses on computational biology and bioinformatics.
