An Introduction to Computational Biochemistry PDF Download

Author: C. Stan Tsai
Publisher: John Wiley & Sons
ISBN: 0471461091
Category : Science
Languages : en
Pages : 381

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Book Description
This comprehensive text offers a solid introduction to the biochemical principles and skills required for any researcher applying computational tools to practical problems in biochemistry. Each chapter includes an introduction to the topic, a review of the biological concepts involved, a discussion of the programming and applications used, key references, and problem sets and answers. Providing detailed coverage of biochemical structures, enzyme reactions, metabolic simulation, genomic and proteomic analyses, and molecular modeling, this is the perfect resource for students and researchers in biochemistry, bioinformatics, bioengineering and computational science.

Author: Oren M. Becker
Publisher: CRC Press
ISBN: 9780203903827
Category : Medical
Languages : en
Pages : 534

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Book Description
Covering theoretical methods and computational techniques in biomolecular research, this book focuses on approaches for the treatment of macromolecules, including proteins, nucleic acids, and bilayer membranes. It uses concepts in free energy calculations, conformational analysis, reaction rates, and transition pathways to calculate and interpret b

Author: Bernhard Haubold
Publisher: Springer Science & Business Media
ISBN: 3764373873
Category : Science
Languages : en
Pages : 329

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Book Description
Written with the advanced undergraduate in mind, this book introduces into the field of Bioinformatics. The authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book. The focus is on methods of comparative genomics and subjects covered include: alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs). The volume contains exercises, questions & answers to selected problems.

Author: Karthik Raman
Publisher: CRC Press
ISBN: 0429944527
Category : Computers
Languages : en
Pages : 359

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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: Uri Alon
Publisher: CRC Press
ISBN: 1584886420
Category : Mathematics
Languages : en
Pages : 324

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Book Description
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.

Author: Bruce R. Donald
Publisher: MIT Press
ISBN: 0262548798
Category : Science
Languages : en
Pages : 497

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Book Description
An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.

Author: L. Pachter
Publisher: Cambridge University Press
ISBN: 9780521857000
Category : Mathematics
Languages : en
Pages : 440

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Book Description
This book, first published in 2005, offers an introduction to the application of algebraic statistics to computational biology.

Author: Nikolay V Dokholyan
Publisher: Springer Science & Business Media
ISBN: 1461421454
Category : Science
Languages : en
Pages : 360

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Book Description
Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.

Author: Joshua Schrier
Publisher: University Science Books
ISBN: 9781938787904
Category : Science
Languages : en
Pages : 0

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Book Description
This book will revolutionize the way physical chemistry is taught by bridging the gap between the traditional "solve a bunch of equations for a very simple model" approach and the computational methods that are used to solve research problems. While some recent textbooks include exercises using pre-packaged Hartree-Fock/DFT calculations, this is largely limited to giving students a proverbial black box. The DIY (do-it-yourself) approach taken in this book helps student gain understanding by building their own simulations from scratch. The reader of this book should come away with the ability to apply and adapt these techniques in computational chemistry to his or her own research problems, and have an enhanced ability to critically evaluate other computational results. This book is mainly intended to be used in conjunction with an existing physical chemistry text, but it is also well suited as a stand-alone text for upper level undergraduate or intro graduate computational chemistry courses.

Author: Richard Durbin
Publisher: Cambridge University Press
ISBN: 113945739X
Category : Science
Languages : en
Pages : 372

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Book Description
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.