Download mining the biomedical literature computational molecular biology in pdf or read mining the biomedical literature computational molecular biology in pdf online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get mining the biomedical literature computational molecular biology in pdf book now. This site is like a library, Use search box in the widget to get ebook that you want.



Mining The Biomedical Literature

Author: Hagit Shatkay
Publisher: MIT Press
ISBN: 0262017695
Size: 32.57 MB
Format: PDF, Mobi
View: 3071
Download and Read
The authors offer an accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing textmining systems.

Current Topics In Computational Molecular Biology

Author: Tao Jiang
Publisher: MIT Press
ISBN: 9780262100922
Size: 60.15 MB
Format: PDF, ePub
View: 3433
Download and Read
A survey of current topics in computational molecular biology. Computational molecular biology, or bioinformatics, draws on the disciplines of biology, mathematics, statistics, physics, chemistry, computer science, and engineering. It provides the computational support for functional genomics, which links the behavior of cells, organisms, and populations to the information encoded in the genomes, as well as for structural genomics. At the heart of all large-scale and high-throughput biotechnologies, it has a growing impact on health and medicine. This survey of computational molecular biology covers traditional topics such as protein structure modeling and sequence alignment, and more recent ones such as expression data analysis and comparative genomics. It combines algorithmic, statistical, database, and AI-based methods for studying biological problems. The book also contains an introductory chapter, as well as one on general statistical modeling and computational techniques in molecular biology. Each chapter presents a self-contained review of a specific subject. Not for sale in China, including Hong Kong.

Computational Molecular Biology

Author: Pavel Pevzner
Publisher: MIT Press
ISBN: 9780262161978
Size: 68.57 MB
Format: PDF, Mobi
View: 1187
Download and Read
Computational gene hunting. Restriction mapping. Map assembly. Sequencing. DNA arrays. Sequence comparision. Multiple alignment. Finding signals in DNA. Gene prediction. Genome rearrangements. Computational proteomics. Problems .All you need to know about molecular biology. Bibliography. Index.

Kernel Methods In Computational Biology

Author: Sorin Istrail
Publisher: MIT Press
ISBN: 9780262195096
Size: 18.40 MB
Format: PDF, Kindle
View: 530
Download and Read
A Primer on Molecular Biology. A Primer on Kernel Methods. Support Vector Machine Applications in Computational Biology. Inexact Matching String Kernels for Protein Classification. Fast Kernels for String and Tree Matching. Local Alignment Kernels for Biological Sequences. Kernels for Graphs. Diffusion Kernels. A Kernel for Protein Secondary Structure Prediction. Heterogeneous Data Comparsion and Gene Selection with Kernel Canonical Correlation Analysis. Kernel-Based Integration of Genomic Data Using Semdefinite Programming. Protein Classification via Kernel Matrix Completion. Accurate Splice Site Detection for Caenorhabditid elegans. Gene Espression Analysis: Joint Feature Selection and Classifier Design. Gene Selection for Microarray Data.

Using The Biological Literature

Author: Diane Schmidt
Publisher: CRC Press
ISBN: 146655858X
Size: 46.94 MB
Format: PDF, Docs
View: 366
Download and Read
The biological sciences cover a broad array of literature types, from younger fields like molecular biology with its reliance on recent journal articles, genomic databases, and protocol manuals to classic fields such as taxonomy with its scattered literature found in monographs and journals from the past three centuries. Using the Biological Literature: A Practical Guide, Fourth Edition is an annotated guide to selected resources in the biological sciences, presenting a wide-ranging list of important sources. This completely revised edition contains numerous new resources and descriptions of all entries including textbooks. The guide emphasizes current materials in the English language and includes retrospective references for historical perspective and to provide access to the taxonomic literature. It covers both print and electronic resources including monographs, journals, databases, indexes and abstracting tools, websites, and associations—providing users with listings of authoritative informational resources of both classical and recently published works. With chapters devoted to each of the main fields in the basic biological sciences, this book offers a guide to the best and most up-to-date resources in biology. It is appropriate for anyone interested in searching the biological literature, from undergraduate students to faculty, researchers, and librarians. The guide includes a supplementary website dedicated to keeping URLs of electronic and web-based resources up to date, a popular feature continued from the third edition.

Biological Data Mining

Author: Jake Y. Chen
Publisher: CRC Press
ISBN: 9781420086850
Size: 44.94 MB
Format: PDF, ePub
View: 7490
Download and Read
Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics. The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

Encyclopedia Of Data Warehousing And Mining

Author: Wang, John
Publisher: IGI Global
ISBN: 1591405599
Size: 62.74 MB
Format: PDF, Mobi
View: 4792
Download and Read
Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.

Algorithms In Structural Molecular Biology

Author: Bruce R. Donald
Publisher: MIT Press
ISBN: 0262297841
Size: 63.51 MB
Format: PDF, Kindle
View: 6965
Download and Read
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.

Biological Modeling And Simulation

Author: Russell Schwartz
Publisher: MIT Press
ISBN: 0262303396
Size: 17.32 MB
Format: PDF, ePub
View: 6920
Download and Read
There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

Immunological Bioinformatics

Author: Ole Lund
Publisher: MIT Press
ISBN: 9780262122801
Size: 54.62 MB
Format: PDF, ePub, Mobi
View: 6720
Download and Read
Using bioinformatics methods to generate a systems-level view of the immune system; description of the main biological concepts and the new data-driven algorithms. Despite the fact that advanced bioinformatics methodologies have not been used as extensively in immunology as in other subdisciplines within biology, research in immunological bioinformatics has already developed models of components of the immune system that can be combined and that may help develop therapies, vaccines, and diagnostic tools for such diseases as AIDS, malaria, and cancer. In a broader perspective, specialized bioinformatics methods in immunology make possible for the first time a systems-level understanding of the immune system. The traditional approaches to immunology are reductionist, avoiding complexity but providing detailed knowledge of a single event, cell, or molecular entity. Today, a variety of experimental bioinformatics techniques connected to the sequencing of the human genome provides a sound scientific basis for a comprehensive description of the complex immunological processes. This book offers a description of bioinformatics techniques as they are applied to immunology, including a succinct account of the main biological concepts for students and researchers with backgrounds in mathematics, statistics, and computer science as well as explanations of the new data-driven algorithms in the context of biological data that will be useful for immunologists, biologists, and biochemists working on vaccine design. In each chapter the authors show interesting biological insights gained from the bioinformatics approach. The book concludes by explaining how all the methods presented in the book can be integrated to identify immunogenic regions in microorganisms and host genomes.