From Computational Logic to Computational Biology PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download From Computational Logic to Computational Biology PDF full book. Access full book title From Computational Logic to Computational Biology by Domenico Cantone. Download full books in PDF and EPUB format.
Author: Domenico Cantone
Publisher: Springer Nature
ISBN: 3031552482
Category :
Languages : en
Pages : 280
Get Book Here
Book Description
Author: Domenico Cantone
Publisher: Springer Nature
ISBN: 3031552482
Category :
Languages : en
Pages : 280
Get Book Here
Book Description
Author: Dan Gusfield
Publisher: Cambridge University Press
ISBN: 1108421768
Category : Computers
Languages : en
Pages : 431
Get Book Here
Book Description
This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.
Author: Dong Xu
Publisher: World Scientific
ISBN: 1908978716
Category : Science
Languages : en
Pages : 246
Get Book Here
Book Description
Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques./a
Author: Karthik Raman
Publisher: CRC Press
ISBN: 0429944527
Category : Computers
Languages : en
Pages : 359
Get Book Here
Book Description
This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. Key Features: A hands-on approach to modelling Covers a broad spectrum of modelling, from static networks to dynamic models and constraint-based models Thoughtful exercises to test and enable understanding of concepts State-of-the-art chapters on exciting new developments, like community modelling and biological circuit design Emphasis on coding and software tools for systems biology Companion website featuring lecture videos, figure slides, codes, supplementary exercises, further reading, and appendices: https://ramanlab.github.io/SysBioBook/ An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians and others.
Author: Shawn T. O'Neil
Publisher:
ISBN: 9780870719264
Category : Science
Languages : en
Pages : 0
Get Book Here
Book Description
A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the "natural environment" of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful "pipe" operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.
Author: Tim J. Stevens
Publisher: Cambridge University Press
ISBN: 1316194140
Category : Science
Languages : en
Pages : 721
Get Book Here
Book Description
Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.
Author: Hamid R Arabnia
Publisher: Morgan Kaufmann
ISBN: 0128026464
Category : Computers
Languages : en
Pages : 670
Get Book Here
Book Description
Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques. • Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets. • Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis. • Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research. • Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications. - Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems. - Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications. - Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software.
Author: Martin Davis
Publisher: Springer Science & Business Media
ISBN: 1447142829
Category : Computers
Languages : en
Pages : 213
Get Book Here
Book Description
In his rich and varied career as a mathematician, computer scientist, and educator, Jacob T. Schwartz wrote seminal works in analysis, mathematical economics, programming languages, algorithmics, and computational geometry. In this volume of essays, his friends, students, and collaborators at the Courant Institute of Mathematical Sciences present recent results in some of the fields that Schwartz explored: quantum theory, the theory and practice of programming, program correctness and decision procedures, dextrous manipulation in Robotics, motion planning, and genomics. In addition to presenting recent results in these fields, these essays illuminate the astonishingly productive trajectory of a brilliant and original scientist and thinker.
Author: Joao Carlos Setubal
Publisher: Springer Science & Business Media
ISBN: 3540280081
Category : Computers
Languages : en
Pages : 270
Get Book Here
Book Description
This book constitutes the refereed proceedings of the Brazilian Symposium on Bioinformatics, BSB 2005, held in Sao Leopoldo, Brazil in July 2005. The 15 revised full papers and 10 revised extended abstracts presented together with 3 invited papers were carefully reviewed and selected from 55 submissions. The papers address a broad range of current topics in computational biology and bioinformatics.
Author: Gabriella Panuccio
Publisher: Springer Nature
ISBN: 3030545687
Category : Technology & Engineering
Languages : en
Pages : 231
Get Book Here
Book Description
This book highlights the latest research on practical applications of computational biology and bioinformatics, and addresses emerging experimental and sequencing techniques that are posing new challenges for bioinformatics and computational biology. Successfully applying these techniques calls for new algorithms and approaches from fields such as statistics, data mining, machine learning, optimization, computer science, and artificial intelligence. In response to these challenges, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences.These proceedings include 21 papers covering many different subfields of bioinformatics and computational biology. Focusing on interdisciplinary applications that combine e.g. bioinformatics, chemoinformatics, and system biology, they are intended to promote the collaboration of scientists from different research groups and with different backgrounds (computer scientists, mathematicians, biologists) to reach breakthrough solutions and overcome the challenges outlined above.
