الصفحة 1
الصفحة 1
DNA Computing ; 7th International Workshop on DNA-Based Computers, DNA7, Tampa, FL, USA, June 10-13, 2001, Revised Papers
Constitutes the post-proceedings of the 7th International Workshop on DNA-Based Computers, held in Florida in 2001. The 26 papers cover experimental tools, theoretical tools, probabilistic computational models, computer simulation and sequence design, algorithms, experimental solutions and more.
Data Integration in the Life Sciences ; Vol. 4075 ; 3rd International Workshop, DILS 2006, Hinxton, UK, July 20-22, 2006, Proceedings
Data management and data integration are fundamental problems in the life sciences. Advances in molecular biology and molecular medicine are almost u- versallyunderpinned by enormouse?orts in data management,data integration, automatic data quality assurance, and computational data analysis. Many hot topics in the life sciences, such as systems biology, personalized medicine, and pharmacogenomics, critically depend on integrating data sets and applications producedby di?erent experimentalmethods, in di?erent researchgroups,andat di?erent levels of granularity.
Combinatorial pattern matching ; Vol.4009) ; 17th Annual Symposium, CPM 2006, Barcelona, Spain, July 5-7, 2006, Proceedings
The book presents 33 revised full papers together with 3 invited talks, organized in topical sections on data structures, indexing data structures, probabilistic and algebraic techniques, applications in molecular biology, string matching, data compression, and dynamic programming
Combinatorial pattern matching ; Vol. 3537 ; 16th Annual Symposium, CPM 2005, Jeju Island, Korea, June 19-22, 2005, Proceedings
This volume presents the proceedings of The 16th Annual Symposium on Combinatorial Pattern Matching was heldon Jeju Island, Korea on June 19–22, 2005. the Program Committee accepted 37 of the submissionsto be presented at the conference. This collection of papers offers original research contributionsin combinatorial pattern matching and its applications.In addition to the selected papers
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including: Importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms / Curation and delivery of biological metadata for use in statistical modeling and interpretation. / Statistical analysis of high-throughput data, including machine learning and visualization,modeling and visualization of graphs and networks. This book is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Bioinformatics : Problem Solving Paradigms
This book highlights basic paradigms of problem analysis and algorithm design in the context of core bioinformatics problems. Mathematically demanding themes are put across to the reader by properly chosen representations with the aid of lots of illustrations.
Algorithmic Aspects of Bioinformatics
Advances in bioinformatics and systems biology require improved computational methods for analyzing data, while progress in molecular biology is in turn influencing the development of computer science methods. This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. This book describes topics in detail and presents formal models in a mathematically precise, yet intuitive manner, with many figures and chapter summaries, detailed derivations, and examples. It is well suited as an introduction into the field of bioinformatics, and will benefit students and lecturers in bioinformatics and algorithmics, while also offering practitioners an update on current research topics.
Advances in bioinformatics and computational biology ; 2nd Brazilian symposium on bioinformatics, BSB 2007, Angra dos Reis, Brazil, August 29-31, 2007, Proceedings
This book address a broad range of current topics in computationl biology and bioinformatics featuring original research in computer science, mathematics and statistics as well as in molecular biology, biochemistry, genetics, medicine, microbiology and other life sciences.
A Computer Scientists Guide to Cell Biology
Provides a succinct treatment of the general concepts of cell biology, furnishing the computer scientist with the tools necessary to read and understand current literature in the field.After a brief introduction to cell biology, the text focuses on the principles behind the most-widely used experimental procedures and mechanisms, relating them to well-understood concepts in computer science. The presentation of the material has been prepared for the reader’s quick grasp of the topic: comments on nomenclature and background notes can be ascertained at a glance, and essential vocabulary is boldfaced throughout the text for easy identification.
