Search Results - ((bioinformatics OR bioinformatic) OR informatics).~

Bioinformatics : converting data to knowledge : a workshop summary / by Pool, Robert, 1955-

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The role of bioinformatics in agriculture

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Bioinformatics : a primer / by Narayanan, P.

Table of Contents: “…Cover; Preface; Acknowledgement; Contents; Chapter 1 Bioinformatics: Introduction; Chapter 2 Atoms and Molecules; Chapter 3 Features of Nucleic Acids; Chapter 4 Features of Proteins; Chapter 5 Physicochemical Characterization of Biomolecules; Chapter 6 Primary Structure (Sequence) Determination of Biomolecules; Chapter 7 Spatial Structure Determination of Biomolecules; Chapter 8 Protein-Ligand Interactions; Chapter 9 The Protein-folding Problem; Chapter 10. …”
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Bioinformatics : Managing Scientific Data. by Lacroix, Zo

Table of Contents: “…Issues to Address While Designing a Biological Information System; Chapter 5. SRS: An Integration Platform for Databanks and Analysis Tools in Bioinformatics; Chapter 6. …”
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Bioinformatics : a Swiss perspective /

Table of Contents: “…Palagi, Frédérique Lisacek -- Protein-Protein Interaction Networks: Assembly and Analysis / Christian von Mering -- Protein Structure Modeling and Docking at the Swiss Institute of Bioinformatics / Torsten Schwede and Manuel C. Peitsch -- Molecular Modeling of Proteins: From Simulations to Drug Design Applications / Vincente Zoete [and others] -- An Introduction to Phylogenetics and Its Molecular Aspects / Gabriel J. …”
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Bioinformatics : High Performance Parallel Computer Architectures. by Schmidt, Bertil

Table of Contents: “…Front cover; Contents; Editor; Contributors; Chapter 1: Algorithms for Bioinformatics; Chapter 2: Introduction to GPGPUs andMassively Threaded Programming; Chapter 3: FPGA: Architecture and Programming; Chapter 4: Parallel Algorithms forAlignments on the Cell BE; Chapter 5: Orchestrating the PhylogeneticLikelihood Function on EmergingParallel Architectures; Chapter 6: Parallel Bioinformatics Algorithmsfor CUDA-Enabled GPUs; Chapter 7: CUDA Error Correction Method forHigh-Throughput Short-Read Sequencing Data; Chapter 8: FPGA Acceleration of SeededSimilarity Searching.…”
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Bioinformatics : theory and practice by Chikhale, N. J.

Table of Contents: “…Cover -- Contents -- Chapter 1 : Introduction To Bioinformatics -- Chapter 2 :The Central Dogma Of Biology -- Chapter 3 :Amino Acid Information -- Chapter 4 :Functional Genomics -- Chapter 5 : Biological Databases And Databanks-I -- Chapter 6 :Biological Databases And Databanks -- II -- Chapter 7 :Name And Function Of Database -- Chapter 8 :Retrieval Of Data And Its Description -- Chapter 9 :Gene Expression Analysis -- Chapter 10 :Microarray And Gene Expression -- Chapter 11 :Pairwise Sequence Alignments -- Chapter 12 :Fasta And Blast -- Chapter 13 :Multiple Sequence Alignments -- Chapter 14 :Methods Of Gene Prediction -- Chapter 15 :RNA Secondary Structure Prediction -- References -- Abbreviations and Acronyms -- Glossary -- Index.…”
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The Bioinformatics : Machine Learning Approach. by Brunak, Søren

Table of Contents: “…Series Foreword; Preface; 1 Introduction; 2 Machine-Learning Foundations: The Probabilistic Framework; 3 Probabilistic Modeling and Inference: Examples; 4 Machine Learning Algorithms; 5 Neural Networks: The Theory; 6 Neural Networks: Applications; 7 Hidden Markov Models: The Theory; 8 Hidden Markov Models: Applications; 9 Probabilistic Graphical Models in Bioinformatics; 10 Probabilistic Models of Evolution: Phylogenetic Trees; 11 Stochastic Grammars and Linguistics; 12 Microarrays and Gene Expression; 13 Internet Resources and Public Databases; A Statistics.…”
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Bioinformatics : the impact of accurate quantification on proteomic and genetic analysis and research

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Bioinformatics : Sequence and Genome Analysis. by Mount, David W.

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Connecting Medical Informatics and Bio-Informatics : Proceedings of MIE2005.

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Machine learning in bioinformatics

Table of Contents: “…Feature selection for ensemble learning and its application /…”
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Informatics and Machine Learning : From Martingales to Metaheuristics. by Winters-Hilt, Stephen

Table of Contents: “…Python (or Perl) and Linux 2 1.2 Informatics and Data Analytics 3 1.3 FSA-Based Signal Acquisition and Bioinformatics 4 1.4 Feature Extraction and Language Analytics 7 1.5 Feature Extraction and Gene Structure Identification 8 1.5.1 HMMs for Analysis of Information Encoding Molecules 11 1.5.2 HMMs for Cheminformatics and Generic Signal Analysis 11 1.6 Theoretical Foundations for Learning 13 1.7 Classification and Clustering 13 1.8 Search 14 1.9 Stochastic Sequential Analysis (SSA) Protocol (Deep Learning Without NNs) 15 1.9.1 Stochastic Carrier Wave (SCW) Analysis - Nanoscope Signal Analysis 18 1.9.2 Nanoscope Cheminformatics - A Case Study for Device "Smartening" 19 1.10 Deep Learning using Neural Nets 20 1.11 Mathematical Specifics and Computational Implementations 21 2 Probabilistic Reasoning and Bioinformatics 23 2.1 Python Shell Scripting…”
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Quantum Bio-Informatics V : Proceedings of the Quantum Bio-Informatics 2011. by Accardi, Luigi

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Quantum bio-informatics II : from quantum information to bio-informatics : Tokyo University of Science, Japan, 12-16 March 2008 /

Table of Contents: “…Asano, M. Ohya and Y. Tanaka -- Towards quantum cybernetics : optimal feedback control in quantum bio informatics / V.P. …”
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Mathematics of bioinformatics : theory, methods, and applications by He, Matthew

Table of Contents: “…Frontmatter -- Bioinformatics and Mathematics -- Genetic Codes, Matrices, and Symmetrical Techniques -- Biological Sequences, Sequence Alignment, and Statistics -- Structures of DNA and Knot Theory -- Protein Structures, Geometry, and Topology -- Biological Networks and Graph Theory -- Biological Systems, Fractals, and Systems Biology -- Matrix Genetics, Hadamard Matrices, and Algebraic Biology -- Bioinformatics, Denotational Mathematics, and Cognitive Informatics -- Evolutionary Trends and Central Dogma of Informatics -- Appendix A: Bioinformatics Notation and Databases -- Appendix B: Bioinformatics and Genetics Time Line -- Appendix C: Bioinformatics Glossary -- Index -- Bioinformatics: Computational Techniques and Engineering.…”
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Essays in bioinformatics

Table of Contents: “…Title page; Foreword; Editors' Note; Contents; Biology and Informatics; Concepts of Similarity in Bioinformatics; Comparison of Sequences, Protein 3D Structures and Genomes; GenBank: The NCBI Nucleotide Sequence Database; Swiss-Prot: Juggling Between Evolution and Stability; EMBOSS -- A Sequence Analysis Package; Prediction and Visualization of DNA Structural Properties from Sequence; Protein Structure and Its Classification; Macromolecular Structure Databases; Protein Secondary Structure Prediction: Comparison of Ten Common Prediction Algorithms Using a Neural Network.…”
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Bioinformatics algorithms : techniques and applications

Table of Contents: “…BIOINFORMATICS ALGORITHMS; CONTENTS; Preface; Contributors; 1 Educating Biologists in the 21st Century: Bioinformatics Scientists versus Bioinformatics Technicians; PART I TECHNIQUES; 2 Dynamic Programming Algorithms for Biological Sequence and Structure Comparison; 3 Graph Theoretical Approaches to Delineate Dynamics of Biological Processes; 4 Advances in Hidden Markov Models for Sequence Annotation; 5 Sorting- and FFT-Based Techniques in the Discovery of Biopatterns; 6 A Survey of Seeding for Sequence Alignment; 7 The Comparison of Phylogenetic Networks: Algorithms and Complexity.…”
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Systems bioinformatics : an engineering case-based approach

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Statistical Bioinformatics : For Biomedical and Life Science Researchers. by Lee, Jae K.

Table of Contents: “…Statistical bioinformatics; contents; preface; contributors; 1 road to statistical bioinformatics; 2 probability concepts and distributions for analyzing large biological data; 3 quality control of high-throughput biological data; 4 statistical testing and significance for large biological data analysis; 5 clustering: unsupervised learning in large biological data; 6 classification: supervised learning with high-dimensional biological data; 7 multidimensional analysis and visualization on large biomedical data; 8 statistical models, inference, and algorithms for large biological data analysis.…”
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