- Gene Ontology Consortium"The Gene Ontology project provides a controlled vocabulary of terms for describing gene product characteristics and gene product annotation data from GO Consortium members, as well as tools to access and process these data. ""The Gene Ontology (GO) project is a major bioinformatics initiative to develop a computational representation of our evolving knowledge of how genes encode biological functions at the molecular, cellular and tissue system levels. Biological systems are so complex that we need to rely on computers to represent this knowledge. The project has developed formal ontologies that represent over 40,000 biological concepts, and are constantly being revised to reflect new discoveries. To date, these concepts have been used to "annotate" gene functions based on experiments reported in over 100,000 peer-reviewed scientific papers."

- Mathematics for the Life Sciences by Louis GrossLocation: QH323.5 .B63 2014Published: 2014This textbook...covers deterministic methods and those that incorporate uncertainty, problems in discrete and continuous time, probability, graphing and data analysis, matrix modeling, difference equations, differential equations, and much more. The book uses MATLAB throughout, explaining how to use it, write code, and connect models to data in examples chosen from across the life sciences. Provides undergraduate life science students with a succinct overview of major mathematical concepts that are essential for modern biology Covers all the major quantitative concepts that national reports have identified as the ideal components of an entry-level course for life science students Provides good background for the MCAT, which now includes data-based and statistical reasoning Explicitly links data and math modeling Includes end-of-chapter homework problems, end-of-unit student projects, and select answers to homework problems Uses MATLAB throughout, and MATLAB m-files with an R supplement are available online Prepares students to read with comprehension the growing quantitative literature across the life sciences Forthcoming online answer key, solution guide, and illustration package (available to professors).
- One Hundred Physics Visualizations Using MATLAB by Dan GreenPublished: 2014-01-01"This book provides visualizations of many topics in general physics. The aim is to have an interactive MATLAB script wherein the user can vary parameters in a specific problem and then immediately see the outcome by way of dynamic "movies" of the response of the system in question. MATLAB tools are used throughout and the software scripts accompany the text in symbolic mathematics, classical mechanics, electromagnetism, waves and optics, gases and fluid flow, quantum mechanics, special and general relativity, and astrophysics and cosmology. The emphasis is on building up an intuition by running many different parametric choices chosen actively by the user and watching the subsequent behavior of the system."
- Environmental Modeling : Using MatLab by Ekkehard HolzbecherPublished: 2012-02-02The book has two aims: to introduce basic concepts of environmental modelling and to facilitate the application of the concepts using modern numerical tools such as MATLAB. It is targeted at all natural scientists dealing with the environment: process and chemical engineers, physicists, chemists, biologists, biochemists, hydrogeologists, geochemists and ecologists.
- Statics with Matlab by Dan B. Marghitu; Mihai Dupac; Nels H. MadsenPublished: 2013Engineering mechanics involves the development of mathematical models of the physical world. Statics addresses the forces acting on and in mechanical objects and systems. Statics with MATLAB(R) develops an understanding of the mechanical behavior of complex engineering structures and components using MATLAB(R) to execute numerical calculations and to facilitate analytical calculations. MATLAB(R) is presented and introduced as a highly convenient tool to solve problems for theory and applications in statics.
- Scientific Computing - an Introduction Using Maple and MATLAB by Walter Gander; Martin J. Gander; Felix KwokPublished: 2014Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple - Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material "hands-on".
- An Introduction to MATLAB® Programming and Numerical Methods for Engineers by Timmy Siauw; Alexandre BayenPublished: 2014Assuming no prior background in linear algebra or real analysis, An Introduction to MATLAB® Programming and Numerical Methods for Engineers enables you to develop good computational problem solving techniques through the use of numerical methods and the MATLAB® programming environment. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level allowing you to quickly apply results in practical settings.
- Environmental Data Analysis with MatLab by William Menke; Joshua MenkeLocation: GE45.M37 M46 2016Published: 2016Numerical derivatives and integrals are derived and illustrated. Includes log-log plots with further examples of their use. Discusses new datasets on precipitation and stream flow. Topical enhancement applies the chi-squared test to the results of the generalized least squares method. New coverage of cluster analysis and approximation techniques that are widely applied in data analysis, including Taylor Series and low-order polynomial approximations; non-linear least-squares with Newton's method; and pre-calculation and updating techniques applicable to real time data acquisition. [From the publisher]
- MATLAB Recipes for Earth Sciences (Fifth Edition) by Martin H. TrauthPublished: 2020The book introduces some of the most important methods of data analysis employed in earth sciences and illustrates their use through examples using the MATLAB® software package, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.

- A Primer on Scientific Programming with Python by Hans Petter LangtangenPublished: 2016The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.
- An Introduction to Statistics with Python by Thomas HaslwanterPublished: 2016With applications in the life sciences.
- Learning SciPy for Numerical and Scientific Computing by Francisco J. Blanco-SilvaPublished: 2013SciPy guarantees fast, accurate, and easy-to-code solutions to your numerical and scientific computing applications. "Learning SciPy for Numerical and Scientific Computing" unveils secrets to some of the most critical mathematical and scientific computing problems and will play an instrumental role in supporting your research. The book will teach you how to quickly and efficiently use different modules and routines from the SciPy library to cover the vast scope of numerical mathematics with its simplistic practical approach that's easy to follow.
- Python for ArcGIS by Laura TateosianPublished: 2016This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. [From the publisher]
- Programming ArcGIS 10. 1 with Python Cookbook by Eric PimplerPublished: 2013This book will show you how to use the Python programming language to create geoprocessing scripts, tools, and shortcuts for the ArcGIS Desktop environment.This book will make you a more effective and efficient GIS professional by showing you how to use the Python programming language with ArcGIS Desktop to automate geoprocessing tasks, manage map documents and layers, find and fix broken data links, edit data in feature classes and tables, and much more.
- Python Geospatial Development by Erik WestraPublished: 2013Python Geospatial Development teaches you everything you need to know about writing geospatial applications using Python. No prior knowledge of geospatial concepts, tools or techniques is required. The book guides you through the process of installing and using various toolkits, obtaining geospatial data for use in your programs, and building complete and sophisticated geospatial applications in Python. Python Geospatial Development teaches you everything you need to know about writing geospatial applications using Python. No prior knowledge of geospatial concepts, tools or techniques is required.

- GIS Based Chemical Fate Modeling by Alberto PistocchiPublished: 2014Over the past decade, researchers have discovered that geographic information systems (GIS) are not only excellent tools for managing and displaying maps, but also useful in the analysis of chemical fate and transport in the environment. Among its many benefits, GIS facilitates the identification of critical factors that drive chemical fate and transport. Moreover, GIS makes it easier to communicate and explain key model assumptions. GIS Based Chemical Fate Modeling makes a unique contribution to the environmental sciences by explaining how GIS analytical functions enhance the development and interpretation of chemical fate and transport models.
- Python for ArcGIS by Laura TateosianPublished: 2016This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. [From the publisher]

- Building Bioinformatics Solutions by Conrad Bessant; Darren Oakley; Ian ShadforthPublished: 2014Bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. This unique book provides an invaluable introduction to three of the main tools used in the development of bioinformatics software - Perl, R and MySQL - and explains how these can be used together to tackle the complex data-driven challenges that typify modern biology.

- Using R for biostatistics by Thomas W. MacFarland and Jan M. YatesPublished: 2021Beginning with a focus on data from a parametric perspective, the authors address topics such as Student t-Tests for independent samples and matched pairs; oneway and twoway analyses of variance; and correlation and linear regression. The authors also demonstrate the importance of a nonparametric perspective for quality assurance through chapters on the Mann-Whitney U Test, Wilcoxon Matched-Pairs Signed-Ranks test, Kruskal-Wallis H-Test for Oneway Analysis of Variance, and the Friedman Twoway Analysis of Variance. To address the element of data presentation, the book also provides an extensive review of the many graphical functions available with R. [Publisher]
- A Primer in Biological Data Analysis and Visualization Using R by Gregg HartvigsenISBN: 0231554400Published: 2021...Guides readers through the processes of correctly entering and analyzing data and using R to visualize data using histograms, boxplots, barplots, scatterplots, and other common graph types. He covers testing data for normality, defining and identifying outliers, and working with non-normally distributed data. Students are introduced to common one- and two-sample tests as well as one- and two-way analysis of variance (ANOVA), correlation, and linear and nonlinear regression analyses. This volume also includes a section on advanced procedures and a chapter outlining algorithms and the art of programming using R. [Publisher]
- Biostatistics with R by Babak ShahbabaPublished: 2011

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Subjects: Digital and Computational Studies