Handbook of Chemoinformatics Algorithms (Chapman & Hall/CRC Mathematical and Computational Biology)

It then focuses on molecular descriptors, virtual screening methods, and quantitative structure—activity relationship QSAR models, before introducing algorithms to enumerate and sample chemical structures. The book also covers computer-aided molecular design, reaction network generation, and open source software and database technologies.

The remaining chapters describe techniques developed in the context of bioinformatics and computational biology and their potential applications to chemical problems. This handbook presents a selection of algorithms relevant in practice, making the book useful to those working in the field. It offers an up-to-date account of many algorithmic aspects of chemoinformatics.

Machine Learning-Based Bioinformatics Algorithms: Application to Chemicals, Shawn Martin. Faeder, and William S. Learn More about VitalSource Bookshelf. CPD consists of any educational activity which helps to maintain and develop knowledge, problem-solving, and technical skills with the aim to provide better health care through higher standards.

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Description Table of Contents Author s Bio. Summary Unlike in the related area of bioinformatics, few books currently exist that document the techniques, tools, and algorithms of chemoinformatics. Display 1 - 20 from 23 results. An Introduction to Systems Biology: Written for students and researchers in systems biology, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological networks, highlighting simple, recurring circuit elements that make up the network.

Rigorously classroom-tested, it contains new additions as well as corrections and revisions for better flow. This edition includes four new chapters: It also doubles the number of exercises and adds an appendix. Local courier delivery with tracking number or collect from 90 lockers islandwide. Add to My List. The area of biologically inspired computing, or biological computation , involves the development of new, biologically based techniques for solving difficult computational problems. A unified overview of computer science ideas inspired by biology, strong Biological Computation strong presents the most fundamental and significant concepts in this area.

In the book, students discover that bacteria communicate, that DNA can be used for performing computations, how evolution solves optimization problems, that the way ants organize their nests can be applied to solve clustering problems, and what the human immune system can teach us about protecting computer netwo.. Emphasizing computational and algorithmic issues surrounding bio-ontologies, this self-contained text helps readers understand ontological algorithms and their applications.

The first part of the book defines ontology and bio-ontologies. It also explains the importance of mathematical logic for understanding concepts of inference in bio-ontologies, discusses the probability and statistics topics necessary for understanding ontology algorithms, and describes ontology languages, including OBO the preeminent language for bio-ontologies , RDF, RDFS, and OWL.

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Methods in Medical Informatics: 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. Fundamentals of Healthcare Programming in Perl, Python, and Ruby strong demonstrates that biomedical professionals with fundamental programm..

Computational Systems Biology of Cancer.

The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models--integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer br Drawn from the authors' decade-long work in the cancer computational systems biology laborat..

Dynamics of Biological Systems. From the spontaneous rapid firing of cortical neurons to the spatial diffusion of disease epidemics, biological systems exhibit rich dynamic behaviour over a vast range of time and space scales. Unifying many of these diverse phenomena, strong Dynamics of Biological Systems strong provides the computational and mathematical platform from which to understand the underlying processes of the phenomena.

Through an extensive tour of various biological systems, the text introduces computational methods for simulating spatial diffusion processes in excitable media, such as the human heart, as well as mathematical tools for dealing with systems of nonlinear ordina.. The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, strong Genome Annotation strong explores automated genome analysis and annotation from its origins to the challenges of next-generation sequencing data analysis.

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The book initially takes you through the last 16 years since the sequencing of the first complete microbial genome. It explains how current analysis strategies were developed, including sequencing strategies, statistical models, and early annotation systems.

Mathematical Modeling and Model Analysis. Drawing on the latest research in the field, strong Systems Biology: Mathematical Modeling and Model Analysis strong presents many methods for modeling and analyzing biological systems, in particular cellular systems. It shows how to use predictive mathematical models to acquire and analyze knowledge about cellular systems.

It also explores how the models are systematically applied in biotechnology. The first part of the book introduces biological basics, such as metabolism, signaling, gene expression, and control as well as mathematical modeling fundamentals, including deterministic models and thermodynamics.

The text also discusses linear regression meth..

Managing Your Biological Data with Python. Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, strong Managing Your Biological Data with Python strong 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.