This is intended to be a simple and accessible book on machine learning methods and their application in computational genomics and nanopore transduction detection. This book has arisen from eight years of teaching one-semester courses on various machine-learning, cheminformatics, and bioinformatics topics. The book begins with a description of ad hoc signal acquisition methods and how to orient on signal processing problems with the standard tools from information theory and signal analysis. A general stochastic sequential analysis (SSA) signal processing architecture is then described that implements Hidden Markov Model (HMM) methods. Methods are then shown for classification and clustering using generalized Support Vector Machines, for use with the SSA Protocol, or independent of that approach. Optimization metaheuristics are used for tuning over algorithmic parameters throughout. Hardware implementations and short code examples of the various methods are also described.

Informatics and Machine Learning Discover a thorough exploration of how to use computational, algorithmic, statistical, and informatics methods to analyze digital data Informatics and Machine Learning: From Martingales to Metaheuristics delivers an interdisciplinary presentation on how analyze any data captured in digital form. The book describes how readers can conduct analyses of text, general sequential data, experimental observations over time, stock market and econometric histories, or symbolic data, like genomes. It contains large amounts of sample code to demonstrate the concepts contained within and assist with various levels of project work. The book offers a complete presentation of the mathematical underpinnings of a wide variety of forms of data analysis and provides extensive examples of programming implementations. It is based on two decades worth of the distinguished author’s teaching and industry experience. A thorough introduction to probabilistic reasoning and bioinformatics, including Python shell scripting to obtain data counts, frequencies, probabilities, and anomalous statistics, or use with Bayes’ rule An exploration of information entropy and statistical measures, including Shannon entropy, relative entropy, maximum entropy (maxent), and mutual information A practical discussion of ad hoc, ab initio, and bootstrap signal acquisition methods, with examples from genome analytics and signal analytics Perfect for undergraduate and graduate students in machine learning and data analytics programs, Informatics and Machine Learning: From Martingales to Metaheuristics will also earn a place in the libraries of mathematicians, engineers, computer scientists, and life scientists with an interest in those subjects.

Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. - Avoids non-essential coverage, yet fully describes the field for beginners - Explains the molecular basis of evolution to place bioinformatic analysis in biological context - Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools - Contains over 100 figures that aid in concept discovery and illustration

This is an introductory text and laboratory manual to be used primarily in undergraduate courses. It is also useful for graduate students and research scientists who require an introduction to the theory and methods of nanopore sequencing. The book has clear explanations of the principles of this emerging technology, together with instructional material written by experts that describes how to use a MinION nanopore instrument for sequencing in research or the classroom.At Harvard University the book serves as a textbook and lab manual for a university laboratory course designed to intensify the intellectual experience of incoming undergraduates while exploring biology as a field of concentration. Nanopore sequencing is an ideal topic as a path to encourage students about the range of courses they will take in Biology by pre-emptively addressing the complaint about having to take a course in Physics or Maths while majoring in Biology. The book addresses this complaint by concretely demonstrating the range of topics — from electricity to biochemistry, protein structure, molecular engineering, and informatics — that a student will have to master in subsequent courses if he or she is to become a scientist who truly understands what his or her biology instrument is measuring when investigating biological phenomena.

This volume guides researchers on how to characterize, image rare, and hitherto unknown taxa and their interactions, to identify new functions and biomolecules and to understand how environmental changes condition the activity and the response of the organisms living with us and in our environment. Chapters cover different organism types (i.e., archaea, bacteria, fungi, protest, microfauna and microeukaryotes) and propose detailed protocols to produce high quality DNA, to analyse active microbial communities directly involved in complex interactions or processes through stable isotope probing, to identify and characterize of new functional genes, to image in situ interactions and to apply bioinformatics analysis tools to complex metagenomic or RNAseq sequence data. Written in the 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 protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Microbial Environmental Genomics (MEG): Methods and Protocols, Second Edition aims to serve as a primary research reference for researchers in microbiology working to in the expanding field of molecular ecology and environmental genomics.

In this book I describe how to use computational, algorithmic, statistical, and informatics methods to analyze any data that is captured in digital form, whether it be text, sequential data in general (such as experimental observations over time, or stock market and econometric histories), or symbolic data such as genome and transcriptome data.

Omics Technologies and Bio-Engineering: Towards Improving Quality of Life, Volume 1 is a unique reference that brings together multiple perspectives on omics research, providing in-depth analysis and insights from an international team of authors. The book delivers pivotal information that will inform and improve medical and biological research by helping readers gain more direct access to analytic data, an increased understanding on data evaluation, and a comprehensive picture on how to use omics data in molecular biology, biotechnology and human health care. - Covers various aspects of biotechnology and bio-engineering using omics technologies - Focuses on the latest developments in the field, including biofuel technologies - Provides key insights into omics approaches in personalized and precision medicine - Provides a complete picture on how one can utilize omics data in molecular biology, biotechnology and human health care