Methods In Medical Informatics

Author: Jules J. Berman
Publisher: CRC Press
ISBN: 9781439841846
Size: 12.99 MB
Format: PDF, ePub, Mobi
View: 793
Download
Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implemented with open source programming languages, you can fully utilize the medical information contained in clinical and research datasets. The common computational tasks of medical informatics are accessible to anyone willing to learn the basics. Methods in Medical Informatics: Fundamentals of Healthcare Programming in Perl, Python, and Ruby demonstrates that biomedical professionals with fundamental programming knowledge can master any kind of data collection. Providing you with access to data, nomenclatures, and programming scripts and languages that are all free and publicly available, this book — Describes the structure of data sources used, with instructions for downloading Includes a clearly written explanation of each algorithm Offers equivalent scripts in Perl, Python, and Ruby, for each algorithm Shows how to write short, quickly learned scripts, using a minimal selection of commands Teaches basic informatics methods for retrieving, organizing, merging, and analyzing data sources Provides case studies that detail the kinds of questions that biomedical scientists can ask and answer with public data and an open source programming language Requiring no more than a working knowledge of Perl, Python, or Ruby, Methods in Medical Informatics will have you writing powerful programs in just a few minutes. Within its chapters, you will find descriptions of the basic methods and implementations needed to complete many of the projects you will encounter in your biomedical career.

Healthcare Data Analytics

Author: Chandan K. Reddy
Publisher: CRC Press
ISBN: 148223212X
Size: 70.94 MB
Format: PDF, ePub, Mobi
View: 3689
Download
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available to solve healthcare problems. The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients. Written by prominent researchers and experts working in the healthcare domain, the book sheds light on many of the computational challenges in the field of medical informatics. Each chapter in the book is structured as a "survey-style" article discussing the prominent research issues and the advances made on that research topic. The book is divided into three major categories: Healthcare Data Sources and Basic Analytics - details the various healthcare data sources and analytical techniques used in the processing and analysis of such data Advanced Data Analytics for Healthcare - covers advanced analytical methods, including clinical prediction models, temporal pattern mining methods, and visual analytics Applications and Practical Systems for Healthcare - covers the applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision support Computer scientists are usually not trained in domain-specific medical concepts, whereas medical practitioners and researchers have limited exposure to the data analytics area. The contents of this book will help to bring together these diverse communities by carefully and comprehensively discussing the most relevant contributions from each domain.

Python For Bioinformatics Second Edition

Author: Sebastian Bassi
Publisher: CRC Press
ISBN: 1351976958
Size: 47.71 MB
Format: PDF, ePub, Docs
View: 4878
Download
In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.

Repurposing Legacy Data

Author: Jules J. Berman
Publisher: Elsevier
ISBN: 0128029153
Size: 45.39 MB
Format: PDF, Kindle
View: 5002
Download
Repurposing Legacy Data: Innovative Case Studies takes a look at how data scientists have re-purposed legacy data, whether their own, or legacy data that has been donated to the public domain. Most of the data stored worldwide is legacy data—data created some time in the past, for a particular purpose, and left in obsolete formats. As with keepsakes in an attic, we retain this information thinking it may have value in the future, though we have no current use for it. The case studies in this book, from such diverse fields as cosmology, quantum physics, high-energy physics, microbiology, psychiatry, medicine, and hospital administration, all serve to demonstrate how innovative people draw value from legacy data. By following the case examples, readers will learn how legacy data is restored, merged, and analyzed for purposes that were never imagined by the original data creators. Discusses how combining existing data with other data sets of the same kind can produce an aggregate data set that serves to answer questions that could not be answered with any of the original data Presents a method for re-analyzing original data sets using alternate or improved methods that can provide outcomes more precise and reliable than those produced in the original analysis Explains how to integrate heterogeneous data sets for the purpose of answering questions or developing concepts that span several different scientific fields

Chromatin

Author: Ralf Blossey
Publisher: CRC Press
ISBN: 1351646818
Size: 39.10 MB
Format: PDF, ePub
View: 2626
Download
An invaluable resource for computational biologists and researchers from other fields seeking an introduction to the topic, Chromatin: Structure, Dynamics, Regulation offers comprehensive coverage of this dynamic interdisciplinary field, from the basics to the latest research. Computational methods from statistical physics and bioinformatics are detailed whenever possible without lengthy recourse to specialized techniques.

Managing Your Biological Data With Python

Author: Allegra Via
Publisher: CRC Press
ISBN: 1439880948
Size: 29.91 MB
Format: PDF, ePub, Docs
View: 4579
Download
Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen. The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming "recipes," ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures. Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.

Game Theoretical Models In Biology

Author: Mark Broom
Publisher: CRC Press
ISBN: 1439853215
Size: 63.59 MB
Format: PDF, Mobi
View: 3494
Download
Covering the major topics of evolutionary game theory, Game-Theoretical Models in Biology presents both abstract and practical mathematical models of real biological situations. It discusses the static aspects of game theory in a mathematically rigorous way that is appealing to mathematicians. In addition, the authors explore many applications of game theory to biology, making the text useful to biologists as well. The book describes a wide range of topics in evolutionary games, including matrix games, replicator dynamics, the hawk-dove game, and the prisoner’s dilemma. It covers the evolutionarily stable strategy, a key concept in biological games, and offers in-depth details of the mathematical models. Most chapters illustrate how to use MATLAB® to solve various games. Important biological phenomena, such as the sex ratio of so many species being close to a half, the evolution of cooperative behavior, and the existence of adornments (for example, the peacock’s tail), have been explained using ideas underpinned by game theoretical modeling. Suitable for readers studying and working at the interface of mathematics and the life sciences, this book shows how evolutionary game theory is used in the modeling of these diverse biological phenomena.

Beautiful Data

Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
ISBN: 144937929X
Size: 11.82 MB
Format: PDF, ePub
View: 3365
Download
In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video. With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include: Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran

Statistical Methods For Qtl Mapping

Author: Zehua Chen
Publisher: CRC Press
ISBN: 143986831X
Size: 56.49 MB
Format: PDF, ePub, Docs
View: 4160
Download
While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. Statistical Methods for QTL Mapping brings together many recent statistical techniques that address the data complexity of QTL mapping. After introducing basic genetics topics and statistical principles, the author discusses the principles of quantitative genetics, general statistical issues of QTL mapping, commonly used one-dimensional QTL mapping approaches, and multiple interval mapping methods. He then explains how to use a feature selection approach to tackle a QTL mapping problem with dense markers. The book also provides comprehensive coverage of Bayesian models and MCMC algorithms and describes methods for multi-trait QTL mapping and eQTL mapping, including meta-trait methods and multivariate sequential procedures. This book emphasizes the modern statistical methodology for QTL mapping as well as the statistical issues that arise during this process. It gives the necessary biological background for statisticians without training in genetics and, likewise, covers statistical thinking and principles for geneticists. Written primarily for geneticists and statisticians specializing in QTL mapping, the book can also be used as a supplement in graduate courses or for self-study by PhD students working on QTL mapping projects.

Ruby

Author: Jules J. Berman
Publisher: Jones & Bartlett Learning
ISBN: 0763757578
Size: 62.68 MB
Format: PDF, ePub
View: 5168
Download
An ideal companion to many introductory computer science courses, as well as an excellent primer, Ruby: The Programming Language offers an accessible introduction to this easy to learn, open-source language. This overview describes the fundamentals of the object-oriented Ruby language and discusses how students can quickly construct complete web applications with ease. Ruby: The Programming Language will excite students on the capabilities of computer programming and inspire them to delve deeper into the computer science discipline.