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75 results in Genomics, bioinformatics and systems biology

Page 1 of 4

Fine-Tuning Life
  • A Guide to MicroRNAs, Your Genome's Master Regulators
  • David C. Henshall
  • Published online:
    14 June 2024
    Print publication:
    27 June 2024
  • Take a journey into the fascinating world of microRNA, the genome's master controllers. Discovered in 1993, our genome's master controllers are critical to the evolution of complex life, including humans. This captivating book tells their story, from their discovery and unique role in regulating protein levels to their practical applications in brain health and other branches of medicine. Written by a neuroscientist, it provides an in-depth look at what we know about microRNAs and how we came to know it. Explore the impact of these molecular conductors on your life and gain a new appreciation for the precision they bring to the molecular noise in our cells. Perfect for students of neuroscience, life sciences such as biochemistry and genetics and the curious public alike, this is the captivating tale of the conductors of life's molecular orchestra.

Multivariate Biomarker Discovery
  • Data Science Methods for Efficient Analysis of High-Dimensional Biomedical Data
  • Darius M. Dziuda
  • Published online:
    30 May 2024
    Print publication:
    06 June 2024
  • Multivariate biomarker discovery is increasingly important in the realm of biomedical research, and is poised to become a crucial facet of personalized medicine. This will prompt the demand for a myriad of novel biomarkers representing distinct 'omic' biosignatures, allowing selection and tailoring treatments to the various individual characteristics of a particular patient. This concise and self-contained book covers all aspects of predictive modeling for biomarker discovery based on high-dimensional data, as well as modern data science methods for identification of parsimonious and robust multivariate biomarkers for medical diagnosis, prognosis, and personalized medicine. It provides a detailed description of state-of-the-art methods for parallel multivariate feature selection and supervised learning algorithms for regression and classification, as well as methods for proper validation of multivariate biomarkers and predictive models implementing them. This is an invaluable resource for scientists and students interested in bioinformatics, data science, and related areas.

Principles of Computational Modelling in Neuroscience
  • 2nd edition
  • David Sterratt, Bruce Graham, Andrew Gillies, Gaute Einevoll, David Willshaw
  • Published online:
    07 October 2023
    Print publication:
    05 October 2023
  • Taking a step-by-step approach to modelling neurons and neural circuitry, this textbook teaches students how to use computational techniques to understand the nervous system at all levels, using case studies throughout to illustrate fundamental principles. Starting with a simple model of a neuron, the authors gradually introduce neuronal morphology, synapses, ion channels and intracellular signalling. This fully updated new edition contains additional examples and case studies on specific modelling techniques, suggestions on different ways to use this book, and new chapters covering plasticity, modelling extracellular influences on brain circuits, modelling experimental measurement processes, and choosing appropriate model structures and their parameters. The online resources offer exercises and simulation code that recreate many of the book's figures, allowing students to practice as they learn. Requiring an elementary background in neuroscience and high-school mathematics, this is an ideal resource for a course on computational neuroscience.

Genome-Scale Algorithm Design
  • Bioinformatics in the Era of High-Throughput Sequencing
  • 2nd edition
  • Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu
  • Published online:
    28 September 2023
    Print publication:
    12 October 2023
  • Presenting the fundamental algorithms and data structures that power bioinformatics workflows, this book covers a range of topics from the foundations of sequence analysis (alignments and hidden Markov models) to classical index structures (k-mer indexes, suffix arrays, and suffix trees), Burrows–Wheeler indexes, graph algorithms, network flows, and a number of advanced omics applications. The chapters feature numerous examples, algorithm visualizations, and exercises, providing graduate students, researchers, and practitioners with a powerful algorithmic toolkit for the applications of high-throughput sequencing. An accompanying website (www.genome-scale.info) offers supporting teaching material. The second edition strengthens the toolkit by covering minimizers and other advanced data structures and their use in emerging pangenomics approaches.

Integrative Bioinformatics for Biomedical Big Data
  • A No-Boundary Thinking Approach
  • Edited by Xiuzhen Huang, Jason H. Moore, Yu Zhang
  • Published online:
    14 September 2023
    Print publication:
    28 September 2023
  • The volume and complexity of biological and biomedical research continues to grow exponentially with cutting-edge technologies such as high-throughput sequencing. Unfortunately, bioinformatics analysis is often considered only after data have been generated, which significantly limits the ability to make sense of complex big data. This unique book introduces the idea of No-Boundary Thinking (NBT) in biological and biomedical research, which aims to access, integrate, and synthesize data, information, and knowledge from bioinformatics to define important problems and articulate impactful research questions. This interdisciplinary volume brings together a team of bioinformatics specialists who draw on their own experiences with NBT to illustrate the importance of collaborative science. It will help stimulate discussion and application of NBT, and will appeal to all biomedical researchers looking to maximize their use of bioinformatics for making scientific discoveries.

Algorithmic Information Dynamics
  • A Computational Approach to Causality with Applications to Living Systems
  • Hector Zenil, Narsis A. Kiani, Jesper Tegnér
  • Published online:
    11 May 2023
    Print publication:
    25 May 2023
  • Biological systems are extensively studied as interactions forming complex networks. Reconstructing causal knowledge from, and principles of, these networks from noisy and incomplete data is a challenge in the field of systems biology. Based on an online course hosted by the Santa Fe Institute Complexity Explorer, this book introduces the field of Algorithmic Information Dynamics, a model-driven approach to the study and manipulation of dynamical systems . It draws tools from network and systems biology as well as information theory, complexity science and dynamical systems to study natural and artificial phenomena in software space. It consists of a theoretical and methodological framework to guide an exploration and generate computable candidate models able to explain complex phenomena in particular adaptable adaptive systems, making the book valuable for graduate students and researchers in a wide number of fields in science from physics to cell biology to cognitive sciences.

Our Genes
  • A Philosophical Perspective on Human Evolutionary Genomics
  • Rasmus Grønfeldt Winther
  • Published online:
    14 December 2022
    Print publication:
    22 December 2022
  • Situated at the intersection of natural science and philosophy, Our Genes explores historical practices, investigates current trends, and imagines future work in genetic research to answer persistent, political questions about human diversity. Readers are guided through fascinating thought experiments, complex measures and metrics, fundamental evolutionary patterns, and in-depth treatment of exciting case studies. The work culminates in a philosophical rationale, based on scientific evidence, for a moderate position about the explanatory power of genes that is often left unarticulated. Simply put, human evolutionary genomics - our genes - can tell us much about who we are as individuals and as collectives. However, while they convey scientific certainty in the popular imagination, genes cannot answer some of our most important questions. Alternating between an up-close and a zoomed-out focus on genes and genomes, individuals and collectives, species and populations, Our Genes argues that the answers we seek point to rich, necessary work ahead.

Understanding Forensic DNA
  • Suzanne Bell, John M. Butler
  • Published online:
    02 September 2022
    Print publication:
    22 September 2022
  • Forensic DNA analysis plays a central role in the judicial system. A DNA sample can change the course of an investigation with immense consequences. Because DNA typing is recognized as the epitome of forensic science, increasing public awareness in this area is vital. Through several cases, examples and illustrations, this book explains the basic principles of forensic DNA typing, and how it integrates with law enforcement investigations and legal decisions. Written for a general readership, Understanding Forensic DNA explains both the power and the limitations of DNA analysis. This book dispels common misunderstandings regarding DNA analysis and shows how astounding match probabilities such as one-in-a-trillion are calculated, what they really mean, and why DNA alone never solves a case.

Computational Thinking for Life Scientists
  • Benny Chor, Amir Rubinstein
  • Published online:
    19 August 2022
    Print publication:
    08 September 2022
  • Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.

Understanding DNA Ancestry
  • Sheldon Krimsky
  • Published online:
    05 March 2022
    Print publication:
    04 November 2021
  • DNA ancestry companies generate revenues in the region of $1bn a year, and the company 23andMe is said to have sold 10 million DNA ancestry kits to date. Although evidently popular, the science behind how DNA ancestry tests work is mystifying and difficult for the general public to interpret and understand. In this accessible and engaging book, Sheldon Krimsky, a leading researcher, investigates the methods that different companies use for DNA ancestry testing. He also discusses what the tests are used for, from their application in criminal investigations to discovering missing relatives. With a lack of transparency from companies in sharing their data, absent validation of methods by independent scientists, and currently no agreed-upon standards of accuracy, this book also examines the ethical issues behind genetic genealogy testing, including concerns surrounding data privacy and security. It demystifies the art and science of DNA ancestry testing for the general reader.

Networks of Networks in Biology
  • Concepts, Tools and Applications
  • Edited by Narsis A. Kiani, David Gomez-Cabrero, Ginestra Bianconi
  • Published online:
    24 February 2021
    Print publication:
    01 April 2021
  • Biological systems are extremely complex and have emergent properties that cannot be explained or even predicted by studying their individual parts in isolation. The reductionist approach, although successful in the early days of molecular biology, underestimates this complexity. As the amount of available data grows, so it will become increasingly important to be able to analyse and integrate these large data sets. This book introduces novel approaches and solutions to the Big Data problem in biomedicine, and presents new techniques in the field of graph theory for handling and processing multi-type large data sets. By discussing cutting-edge problems and techniques, researchers from a wide range of fields will be able to gain insights for exploiting big heterogonous data in the life sciences through the concept of 'network of networks'.

Quantitative Genetics
  • Armando Caballero
  • Published online:
    06 October 2020
    Print publication:
    23 April 2020
  • Quantitative genetics is the study of continuously varying traits which make up the majority of biological attributes of evolutionary and commercial interest. This book provides a much-needed up-to-date, in-depth yet accessible text for the field. In lucid language, the author guides readers through the main concepts of population and quantitative genetics and their applications. It is written to be approachable to even those without a strong mathematical background, including applied examples, a glossary of key terms, and problems and solutions to support students in grasping important theoretical developments and their relevance to real-world biology. An engaging, must-have textbook for advanced undergraduate and postgraduate students. Given its applied focus, it also equips researchers in genetics, genomics, evolutionary biology, animal and plant breeding, and conservation genetics with the understanding and tools for genetic improvement, comprehension of the genetic basis of human diseases, and conservation of biological resources.

Cladistics
  • A Guide to Biological Classification
  • 3rd edition
  • David M. Williams, Malte C. Ebach
  • Published online:
    20 July 2020
    Print publication:
    06 August 2020
  • This new edition of a foundational text presents a contemporary review of cladistics, as applied to biological classification. It provides a comprehensive account of the past fifty years of discussion on the relationship between classification, phylogeny and evolution. It covers cladistics in the era of molecular data, detailing new advances and ideas that have emerged over the last twenty-five years. Written in an accessible style by internationally renowned authors in the field, readers are straightforwardly guided through fundamental principles and terminology. Simple worked examples and easy-to-understand diagrams also help readers navigate complex problems that have perplexed scientists for centuries. This practical guide is an essential addition for advanced undergraduates, postgraduates and researchers in taxonomy, systematics, comparative biology, evolutionary biology and molecular biology.

Topological Data Analysis for Genomics and Evolution
  • Topology in Biology
  • Raul Rabadan, Andrew J. Blumberg
  • Published online:
    18 November 2019
    Print publication:
    19 December 2019
  • Biology has entered the age of Big Data. A technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce comparisons of shape to a comparison of algebraic invariants, such as numbers, which are typically easier to work with. Topological data analysis is a rapidly developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology as well as mathematicians interested in applied topology.

Integer Linear Programming in Computational and Systems Biology
  • An Entry-Level Text and Course
  • Dan Gusfield
  • Published online:
    31 May 2019
    Print publication:
    13 June 2019
  • Integer linear programming (ILP) is a versatile modeling and optimization technique that is increasingly used in non-traditional ways in biology, with the potential to transform biological computation. However, few biologists know about it. This how-to and why-do text introduces ILP through the lens of computational and systems biology. It uses in-depth examples from genomics, phylogenetics, RNA, protein folding, network analysis, cancer, ecology, co-evolution, DNA sequencing, sequence analysis, pedigree and sibling inference, haplotyping, and more, to establish the power of ILP. This book aims to teach the logic of modeling and solving problems with ILP, and to teach the practical 'work flow' involved in using ILP in biology. Written for a wide audience, with no biological or computational prerequisites, this book is appropriate for entry-level and advanced courses aimed at biological and computational students, and as a source for specialists. Numerous exercises and accompanying software (in Python and Perl) demonstrate the concepts.

Analyzing Network Data in Biology and Medicine
  • An Interdisciplinary Textbook for Biological, Medical and Computational Scientists
  • Edited by Nataša Pržulj
  • Published online:
    18 March 2019
    Print publication:
    28 March 2019
  • The increased and widespread availability of large network data resources in recent years has resulted in a growing need for effective methods for their analysis. The challenge is to detect patterns that provide a better understanding of the data. However, this is not a straightforward task because of the size of the data sets and the computer power required for the analysis. The solution is to devise methods for approximately answering the questions posed, and these methods will vary depending on the data sets under scrutiny. This cutting-edge text introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, before discussing the thought processes and creativity involved in the analysis of large-scale biological and medical data sets, using a wide range of real-life examples. Bringing together leading experts, this text provides an ideal introduction to and insight into the interdisciplinary field of network data analysis in biomedicine.

Genome Editing and Engineering
  • From TALENs, ZFNs and CRISPRs to Molecular Surgery
  • Edited by Krishnarao Appasani
  • Foreword by George M. Church
  • Published online:
    30 July 2018
    Print publication:
    23 August 2018
  • Recent advances in genome editing tools using endonucleases such as TALENs, ZFNs, and CRISPRs, combined with genomic engineering technologies, have opened up a wide range of opportunities from applications in the basic sciences and disease biology research, to the potential for clinical applications and the development of new diagnostic tools. This complete guide to endonuclease-based genomic engineering gives readers a thorough understanding of this rapidly expanding field. Chapters cover the discovery, basic science, and application of these techniques, focusing particularly on their potential relevance to the treatment of cancer, and cardiovascular and immunological disease. The final section discusses the legal and ethical issues which accompany the technology. Providing authoritative coverage of the potential that genome editing and engineering have, this is an ideal reference for researchers and graduate students and those working in the biotechnology and pharmaceutical industries, as well as in a clinical setting.

Computing for Biologists
  • Python Programming and Principles
  • Ran Libeskind-Hadas, Eliot Bush
  • Published online:
    28 May 2018
    Print publication:
    22 September 2014
  • Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.

Modern Prometheus
  • Editing the Human Genome with Crispr-Cas9
  • Jim Kozubek
  • Published online:
    19 April 2018
    Print publication:
    26 April 2018
  • Would you change your genes if you could? As we confront the 'industrial revolution of the genome', the recent discoveries of Crispr-Cas9 technologies are offering, for the first time, cheap and effective methods for editing the human genome. This opens up startling new opportunities as well as significant ethical uncertainty. Tracing events across a fifty-year period, from the first gene splicing techniques to the present day, this is the story of gene editing - the science, the impact and the potential. Kozubek weaves together the fascinating stories of many of the scientists involved in the development of gene editing technology. Along the way, he demystifies how the technology really works and provides vivid and thought-provoking reflections on the continuing ethical debate. This updated paperback edition contains all the very latest on the patent battle over Crisp and the applications of Crispr technology in agriculture and medicine.

Introduction to Hidden Semi-Markov Models
  • John van der Hoek, Robert J. Elliott
  • Published online:
    01 February 2018
    Print publication:
    08 February 2018
  • Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction to the subject by first developing the theory of Markov processes in an elementary discrete time, finite state framework suitable for senior undergraduates and graduates. The authors then introduce semi-Markov chains and hidden semi-Markov chains, before developing related estimation and filtering results. Genomics applications are modelled by discrete observations of these hidden semi-Markov chains. This book contains new results and previously unpublished material not available elsewhere. The approach is rigorous and focused on applications.

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