Essentials Of Bioinformatics Volume Iii

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 will mostly focus 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. The third volume is titled In Silico Life Sciences: Agriculture. It focuses on plant genetic, genomic, transcriptomic, proteomic and metabolomics data. Using examples of new crop diseases-emergence, crop productivity and biotic/abiotic stress tolerance, this book illustrates how bioinformatics can be an integral components of modern day plant science research.

Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

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 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. Our second title of this volume set In Silico Life Sciences: Medicine provides hands-on experience in analyzing high throughput molecular data for the diagnosis, prognosis, and treatment of monogenic or polygenic human diseases. The key concepts in this volume include risk factor assessment, genetic tests and result interpretation, personalized medicine, and drug discovery. This volume is expected to train readers in both single and multi-dimensional biological analysis using open data sets, and provides a unique learning experience through clinical scenarios and case studies.

Bioinformatics is an upcoming discipline of Life Sciences. It is an integration of computer science, and mathematical and statistical methods to manage and analyze the biological data. The fundamental issues that directly impact an understanding of life at structural, functional and molecular level, and regulation of gene expression can be studied by using bioinformatics tools. The Fundamentals of Bioinformatics is a comprehensive book for undergraduates, postgraduates and research scholars, who urge to learn about theoretical as well as practical aspects of this upcoming field. This pioneering book provides up-to-date information on bioinformatics and emphasizes recent topics like drug design technology, pharmacogenomics, proteomics and genomics. The present textbook will be an asset to Life sciences and technology institutions, since it has been designed based on the prescribed syllabus of various Indian Universities and aboard, and cover all the important topics on Bioinformatics.

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.

This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolboxTM. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence comparison, scoring, and determining evolutionary distance. The main focus of the third part is on modeling biological sequences and patterns as Markov chains. It presents key principles for analyzing and searching for sequences of significant motifs and biomarkers. The last part of the book, dedicated to systems biology, covers phylogenetic analysis and evolutionary tree computations, as well as gene expression analysis with microarrays. In brief, the book offers the ideal hands-on reference guide to the field of bioinformatics and computational biology.

This is an open access book. We are pleased to announce our 3rd International Conference on Bioinformatics and Data Science (ICBDS – 2022) and 9th International Conference on Public Mental Health and Neurosciences (ICPMN – 2022) which was a unique conference where we connectted Biological Function through Computational Genomics to the world of integrated medicine and therapeutics. Functional genomics is a field of molecular biology that attempts to describe gene (and protein) functions and interactions. This science aims to understand the complex relationship between genotype and phenotype on a global (genome-wide) scale of different biological processes. Most researchers now study genes or regions on a “genome-wide” scale (i.e. all or multiple genes/regions at the same time), with the hope of narrowing them down to a list of candidate genes or regions to analyze in more detail. There are several specific functional genomics approaches depending on what we are focused on DNA level (genomics and epigenomics), RNA level (transcriptomics), protein level (proteomics), metabolite level (metabolomics) and phenotype level (phenomics). The recent trends in gene and genome editing technologies, promising genomic information can be modulated in the areas of medicine, agriculture and environment. Big data is a promising in many research areas, but still it is computationally challenging and non-availability of experts to handle big-data with reduced speed and cost. With the increasing use of advanced technology and the exploding amount of big-data in, it is imperative to introduce effective and efficient methods to handle big data using computing technologies. The big data analytics technique is required to solve the problems in bioinformatics such as the storage of vast information generated by analyzing the big-data. Big data analytics can examine large data sets, analyze and correlate genomic and proteomic information. Big data research finds a huge application in Neuroscience and Brain research. Our unique conference connects genomics to the world of genomics to integrated medicine including yogic sciences.

This book illustrates the importance and significance of bioinformatics in the field of agriculture. It first introduces the basic concepts of bioinformatics, such as homologous sequence and gene function analyses, determination of protein structures, and discusses machine learning applications for an in-depth understanding of the desired genes and proteins based on commonly used bioinformatics software and tools, e.g. BLAST, molecular modelling, molecular-docking and simulations, protein-protein and domain-domain interactions. The book also describes recent advances in the high-throughput analysis of whole genome and transcriptome using next-generation sequencing platforms, and functional proteome studies. It also examines the role of computational biology in understanding and improving the nutrient quality and yield of crops. Lastly, the book explores a comprehensive list of applications of bioinformatics to improve plant yield, biomass, and health, and the challenges involved.