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1.

図書
図書
1. Computational biology : a statistical mechanics perspective. 2nd ed
Ralf Blossey
出版情報: Boca Raton : CRC Press, c2019  xiii, 285 p. ; 25 cm
シリーズ名: Chapman and Hall/CRC mathematical & computational biology series / series editors Alison M. Etheridge ... [et al.]
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2.

図書
図書
2. Computational intelligence in biomedical imaging (: hbk)
Kenji Suzuki editor
出版情報: New York : Springer, c2014  xv, 406 p. ; 25 cm
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3.

図書
図書
3. Biodata mining and visualization : novel approaches (: hbk.)
Ilkka Havukkala
出版情報: Singapore : World Scientific, c2010  xv, 307 p. ; 24 cm
シリーズ名: Science, engineering, and biology informatics ; v. 5
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目次情報: 続きを見る
Preface
Acknowledgement
About the Author
Introduction to Modern Molecular Biology / 1：
Cells store large amounts of information in DNA / 1.1：
Cells process complex information / 1.2：
Cellular life is chemically complex and somewhat stochastic / 1.3：
Challenges in analyzing complex biodata / 1.4：
References
Biodata Explosion / 2：
Primary sequence and structure data / 2.1：
DNA sequence databases / 2.1.1：
Protein sequence databases / 2.1.2：
Molecular structure databases / 2.1.3：
Secondary annotation data / 2.2：
Motif annotations / 2.2.1：
Gene function annotations / 2.2.2：
Genomic annotations / 2.2.3：
Inter-species phylogeny and gene family annotations / 2.2.4：
Experimental and personalized data / 2.3：
DNA expression profiles / 2.3.1：
Proteomics data and degradomics / 2.3.2：
Protein expression profiles, 2D gel and protein interaction data / 2.3.3：
Metabolomics and metabolic pathway databases / 2.3.4：
Personalized data / 2.3.5：
Semantic and processed text data / 2.4：
Ontologies / 2.4.1：
Text-mined annotation data / 2.4.2：
Integrated and federated databases / 2.5：
Local Pattern Discovery and Comparing Genes and Proteins / 3：
DNA/RNA motif discovery / 3.1：
Single motif models: MEME, AlignAce etc. / 3.1.1：
Multiple motif models: LOGOS and MotifRegressor / 3.1.2：
Informative k-mers approach / 3.1.3：
Protein motif discovery / 3.2：
InterProScan and other traditional methods / 3.2.1：
Protein k-mer and other string based methods / 3.2.2：
Genetic algorithms, particle swarms and ant colonies / 3.3：
Genetic algorithms / 3.3.1：
Particle swarm optimization / 3.3.2：
Ant colony optimization / 3.3.3：
Sequence visualization / 3.4：
Global Pattern Discovery and Comparing Genomes / 4：
Alignment-based methods / 4.1：
Pairwise genome-wide search algorithms: LAGAN, AVID etc. / 4.1.1：
Multiple alignment methods: MLAGAN, MAVID, MULTIZ etc. / 4.1.2：
Dotplots / 4.1.3：
Visualization of genome comparisons / 4.1.4：
Global motif maps / 4.1.5：
Alignmentless methods / 4.2：
K-mer based methods / 4.2.1：
Average common substring and compressibility based methods / 4.2.2：
2D portraits of genomes / 4.2.3：
Genome scale non-sequence data analysis / 4.3：
DNA physical structure based methods / 4.3.1：
Secondary structure based comparisons / 4.3.2：
Molecule Structure Based Searching and Comparison / 5：
Molecule structures as graphs or strings / 5.1：
3D to 1D transformations / 5.1.1：
Graph matching methods / 5.1.2：
Graph visualization / 5.1.3：
Graph grammars / 5.1.4：
RNA structure comparison and prediction / 5.2：
Image comparison based methods / 5.3：
Gabor filter based methods / 5.3.1：
Image symmetry set based methods / 5.3.2：
Other graph topology based methods / 5.3.3：
Function Annotation and Ontology Based Searching and Classification / 6：
Annotation ontologies / 6.1：
Gene Ontology based mining / 6.2：
Sequence similarity based function prediction / 6.3：
Cellular location prediction / 6.4：
New integrative methods: Utilizing networks / 6.5：
Text mining bioliterature for automated annotation / 6.6：
Natural language processing (NLP) / 6.6.1：
Semantic profiling / 6.6.2：
Matrix factorization methods / 6.6.3：
New Methods for Genomics Data: SVM and Others / 7：
SVM kernels / 7.1：
SVM trees / 7.2：
Methods for microarray data / 7.3：
Gene selection algorithms / 7.3.1：
Gene selection by consistency methods / 7.3.2：
Genome as a time series and discrete wavelet transform / 7.4：
Parameterless clustering for gene expression / 7.5：
Transductive confidence machines, conformal predictors and ROC isometrics / 7.6：
Text compression methods for biodata analysis / 7.7：
Integration of Multimodal Data: Toward Systems Biology / 8：
Comparative genome annotation systems / 8.1：
Phylogenetics methods / 8.2：
Network inference from interaction and coexpression data / 8.3：
Bayesian inference, association rule mining and Petri nets / 8.4：
Future Challenges / 9：
Network analysis methods / 9.1：
Unsupervised and supervised clustering / 9.2：
Neural networks and evolutionary methods / 9.3：
Semantic web and ontologization of biology / 9.4：
Biological data fusion / 9.5：
Rise of the GPU machines / 9.6：
Index
Preface
Acknowledgement
About the Author
4.

図書
図書
4. Computational biology : a statistical mechanics perspective
Ralf Blossey
出版情報: Boca Raton : Chapman & Hall/CRC, 2006  251 p., 8 p. of plates ; 25 cm
シリーズ名: Chapman and Hall/CRC mathematical & computational biology series / series editors Alison M. Etheridge ... [et al.]
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Statistical Mechanics / I：
Equilibrium Statistical Mechanics / 1：
Z: The partition function / 1.1：
Relation to thermodynamics / 1.2：
Computing Z / 1.3：
Nonequilibrium Statistical Mechanics / 2：
Stochastic processes / 2.1：
The master equation / 2.2：
Fluctuation theorems / 2.3：
The Fokker-Planck and Langevin equations / 2.4：
Sequence alignment: a nonequilibrium phase transition / 2.5：
Biomolecules / II：
Molecules, Code and Representation
DNA and RNA: the building blocks
Representing RNA structure
Proteins
DNA
Thermal stability of DNA: the melting transition
The melting profiles of genomic DNA and cDNA
Hybridizing DNA
RNA / 3：
Computing RNA secondary structure: combinatorics / 3.1：
The RNA partition function / 3.2：
RNA phase behaviour and folding kinetics / 3.3：
Proteins: folding / 4：
Proteins: docking / 4.2：
Electrostatics / 4.3：
Chromatin / 4.4：
Bacterial chemotaxis: cooperativity once more / 4.5：
Networks / III：
Network Dynamics I: Deterministic
Deterministic dynamics: [lambda]-repressor expression
The Turing insight
The Min system
Network Dynamics II: Fluctuations
Noise in signalling
Stochastic cascades
Stochastic focusing
Fluctuating gene network dynamics
Extrinsic vs. intrinsic noise
Networks: Structure
Networks as graphs
Probability generating functions and network characteristics
Statistical mechanics of networks
Network growth / 3.4：
Index
Statistical Mechanics / I：
Equilibrium Statistical Mechanics / 1：
Z: The partition function / 1.1：
5.

図書
図書
5. Computational methods for SNPs and Haplotype inference : DIMACS/RECOMB satellite workshop, Piscataway, NJ, USA, November 21-22, 2002 : revised papers
Sorin Istrail, Michael Waterman, Andrew Clark, (eds.)
出版情報: Berlin ; Tokyo : Springer, c2004  ix, 152 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 2983 . Lecture notes in bioinformatics
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6.

図書
図書
6. Handbook on biological networks
edited by Stefano Boccaletti, Vito Latora, Yamir Moreno
出版情報: Singapore : World Scientific, c2010  ix, 441 p. ; 26 cm
シリーズ名: World Scientific lecture notes in complex systems ; v. 10
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Preface
Introduction / 1：
Networks at the Cellular Level
The Structural Network Properties of Biological Systems / Matteo Brilli ; Pietro Lió2：
Dynamics of Multicellular Synthetic Gene Networks / Ekkehard Ullner ; Aneta Koseska ; Alexey Zaikin ; Evgenii Volkov ; Jürgen Kurths ; Jordi García-Ojalvo3：
Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level / Juilee Thakar ; Réka Albert4：
Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks / Albert Díaz-Guilera ; Elena R. Álvarez-Buylla5：
Geometry and Topology of Folding Landscapes / Lorenzo Bongini ; Lapo Casetti6：
Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses / Timothy R. Lezon ; Indira H. Shrivastava ; Zheng Yang ; Ivet Bahar7：
Metabolic Networks / Maria Concetta Palumbo ; Lorenzo Farina ; Alfredo Colosimo ; Alessandro Giuliani8：
Brain Networks
The Human Brain Network / Olaf Sporns9：
Brain Network Analysis from High-Resolution EEG Signals / Fabrizio De Vico Fallani ; Fabio Babiloni10：
An Optimization Approach to the Structure of the Neuronal Layout of C. elegans / Alex Arenas ; Alberto Fernández ; Sergio Gómez11：
Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory / Nadav Raichman ; Liel Rubinsky ; Mark Shein ; Itay Baruchi ; Vladislav Volman ; Eshel Ben-Jacob12：
Synchrony and Precise Timing in Complex Neural Networks / Raoul-Martin Memmesheimer ; Marc Timme13：
Networks at the Individual and Population Levels
Ideas for Moving Beyond Structure to Dynamics of Ecological Networks / Daniel B. Stouffer ; Miguel A. Fortuna ; Jordi Bascompte14：
Evolutionary Models for Simple Biosystems / Franco Bagnoli15：
Evolution of Cooperation in Adaptive Social Networks / Sven Van Segbroeck ; Francisco C. Santos ; Arne Traulsen ; Tom Lenaerts ; Jorge M. Pacheco16：
From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies / Arturo Buscarino ; Luigi Fortuna ; Mattia Frasca ; Alessandro Rizzo17：
Interplay of Network State and Topology in Epidemic Dynamics / Thilo Gross18：
Index
Preface
Introduction / 1：
Networks at the Cellular Level
7.

図書
図書
7. Computational ecology : artificial neural networks and their applications (: hbk)
Wenjun Zhang
出版情報: Singapore : World Scientific, c2010  xiii, 296 p. ; 24 cm
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Preface
Introduction / Chapter 1：
Computational Ecology / 1：
Artificial Neural Networks and Ecological Applications / 2：
Artificial Neural Networks: Principles, Theories and Algorithms / Part I：
Feedforward Neural Networks / Chapter 2：
Linear Separability and Perceptron
Some Analogies of Multilayer Feedforward Networks
Functionability of Multilayer Feedforward Networks / 3：
Linear Neural Networks / Chapter 3：
LMS Rule
Radial Basis Function Neural Networks / Chapter 4：
Theory of RBF Neural Network
Regularized RBF Neural Network
RBF Neural Network Learning
Probabilistic Neural Network / 4：
Generalized Regression Neural Network / 5：
Functional Link Neural Network / 6：
Wavelet Neural Network / 7：
BP Neural Network / Chapter 5：
BP Algorithm
BP Theorem
BP Training
Limitations and Improvements of BP Algorithm
Self-Organizing Neural Networks / Chapter 6：
Self-Organizing Feature Map Neural Network
Self-Organizing Competitive Learning Neural Network
Hamming Neural Network
WTA Neural Network
LVQ Neural Network
Adaptive Resonance Theory
Feedback Neural Networks / Chapter 7：
Elman Neural Network
Hopfield Neural Networks
Simulated Annealing
Boltzmann Machine
Design and Customization of Artificial Neural Networks / Chapter 8：
Mixture of Experts
Hierarchical Mixture of Experts
Neural Network Controller
Customization of Neural Networks
Learning Theory, Architecture Choice and Interpretability of Neural Networks / Chapter 9：
Learning Theory
Architecture Choice
Interpretability of Neural Networks
Mathematical Foundations of Artificial Neural Networks / Chapter 10：
Bayesian Methods
Randomization, Bootstrap and Monte Carlo Techniques
Stochastic Process and Stochastic Differential Equation
Interpolation
Function Approximation
Optimization Methods
Manifold and Differential Geometry
Functional Analysis / 8：
Algebraic Topology / 9：
Motion Stability / 10：
Entropy of a System / 11：
Distance or Similarity Measures / 12：
Matlab Neural Network Toolkit / Chapter 11：
Functions of Perceptron
Functions of Linear Neural Networks
Functions of BP Neural Network
Functions of Self-Organizing Neural Networks
Functions of Radial Basis Neural Networks
Functions of Probabilistic Neural Network
Function of Generalized Regression Neural Network
Functions of Hopfield Neural Network
Function of Elman Neural Network
Applications of Artificial Neural Networks in Ecology / Part II：
Dynamic Modeling of Survival Process / Chapter 12：
Model Description
Data Description
Results
Discussion
Simulation of Plant Growth Process / Chapter 13：
Data Source
Simulation of Food Intake Dynamics / Chapter 14：
Species Richness Estimation and Sampling Data Documentation / Chapter 15：
Estimation of Plant Species Richness on Grassland
Documentation of Sampling Data of Invertebrates
Modeling Arthropod Abundance from Plant Composition of Grassland Community / Chapter 16：
Pattern Recognition and Classification of Ecosystems and Functional Groups / Chapter 17：
Modeling Spatial Distribution of Arthropods / Chapter 18：
Risk Assessment of Species Invasion and Establishment / Chapter 19：
Invasion Risk Assessment Based on Species Assemblages
Determination of Abiotic Factors Influencing Species Invasion
Prediction of Surface Ozone / Chapter 20：
BP Prediction of Daily Total Ozone
MLP Prediction of Hourly Ozone Levels
Modeling Dispersion and Distribution of Oxide and Nitrate Pollutants / Chapter 21：
Modeling Nitrogen Dioxide Dispersion
Simulation of Nitrate Distribution in Ground Water
Modeling Terrestrial Biomass / Chapter 22：
Estimation of Aboveground Grassland Biomass
Estimation of Trout Biomass
References
Index
Preface
Introduction / Chapter 1：
Computational Ecology / 1：
8.

電子ブック
ＥＢ
8. The processes of life : an introduction to molecular biology ((ebook) :)
Lawrence E. Hunter
出版情報: Cambridge, Mass. ; London : MIT, c2009  1 online resource (xiv, 299 p.)
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Preface
In the Beginning ... / 1：
Approaching the Study of Life / 1.1：
Billions and Billions of Creatures ... / 1.2：
... All Alike / 1.3：
Where To from Here / 1.4：
Evolution / 2：
Inheritance / 2.1：
Variation / 2.2：
Selection / 2.3：
A Brief History of Life on Earth / 2.4：
Evolution and Life / 2.5：
Suggested Readings / 2.6：
A Little Bit of Chemistry / 3：
Matter / 3.1：
Atoms / 3.1.1：
Molecules and Bonds / 3.1.2：
Reactions / 3.2：
Organic Chemistry / 3.3：
Energy and Thermodynamics / 3.4：
Chemistry and Life / 3.5：
The Structure and Function of Bacteria / 3.6：
Membranes and Boundaries / 4.1：
Cytoplasm and Metabolism / 4.2：
Chromosomes and Genomes / 4.3：
Bacterial Life / 4.4：
Biological Macromolecules / 4.5：
Protein / 5.1：
Protein Structure / 5.1.1：
Protein Evolution / 5.1.2：
Protein Function / 5.1.3：
Nucleic Acids / 5.2：
DNA / 5.2.1：
RNA / 5.2.2：
DNA Evolution / 5.2.3：
Macromolecules and Life / 5.3：
Eukaryotes / 5.4：
Eukaryotic Gene Structure and Transcription / 6.1：
Components of the Eukaryotic Cell / 6.2：
The Nucleus / 6.2.1：
The Endoplasmic Reticulum and Golgi Apparatus / 6.2.2：
The Mitochondrion / 6.2.3：
The Chloroplast / 6.2.4：
Other Plastids / 6.2.5：
The Proteasome, the Lysosome, and the Peroxisome / 6.2.6：
Lifestyles of the Single-Celled Eukaryote / 6.3：
Multicellular Organisms and Development / 6.4：
The Origin of Multicellular Organisms / 7.1：
Development / 7.2：
Molecular Maps / 7.2.1：
Cell-to-Cell Signaling / 7.2.2：
Cell Motion / 7.2.3：
Differentiation / 7.2.4：
Organogenesis / 7.2.5：
Growth / 7.3：
Multicellular Life and Humanity / 7.4：
Anatomy, Physiology, and Systems Biology / 7.5：
Homeostasis / 8.1：
Tissues / 8.2：
Organ Systems / 8.3：
The Cardiovascular System / 8.3.1：
The Immune System / 8.3.2：
The Nervous System / 8.3.3：
Systems Biology / 8.4：
Disease and Its Treatment / 8.5：
General Principles of Pathology and Therapeutics / 9.1：
Cellular Stress and Responses to It / 9.1.1：
Cell Injury / 9.1.2：
Cell Death / 9.1.3：
General Principles of Therapeutics / 9.1.4：
Healing / 9.2：
Genetics and Disease / 9.3：
Infectious Disease and Antibiotics / 9.4：
Cardiovascular Disease / 9.5：
Cancer / 9.6：
Drug Discovery / 9.7：
Molecular Medicine / 9.8：
Molecular Biotechnology / 9.9：
Molecular Instrumentation / 10.1：
Measurements of Mass and Charge / 10.1.1：
Macromolecular Structure Determination / 10.1.2：
Assays of Molecular Activity / 10.1.3：
Distribution of Molecules Through Space and Time / 10.1.4：
Nucleic Acid Instrumentation / 10.1.5：
Model Organisms: Germs, Worms, Weeds, Bugs, and Rodents / 10.2：
Escherichia coli / 10.2.1：
Saccharomyces cerevisiae / 10.2.2：
Arabidopsis thaliana / 10.2.3：
Caenorhabditis elegans / 10.2.4：
Drosophila melanogaster / 10.2.5：
Danio rerio / 10.2.6：
Mus musculus / 10.2.7：
Genetic Engineering / 10.3：
Molecular Biotechnology and Human Life / 10.4：
Molecular Bioethics / 10.5：
Molecular Biology and Medicine / 11.1：
Molecular Biology and Agriculture / 11.2：
Molecular Biology and Society / 11.3：
Regulation and Control of Molecular Biotechnology / 11.4：
Learning about Life / 11.5：
Glossary / 11.6：
Index
Preface
In the Beginning ... / 1：
Approaching the Study of Life / 1.1：
9.

電子ブック
ＥＢ
9. Modern applications of Flory's "Statistical mechanics of chain molecules" (: electronic bk)
Alan E. Tonelli, editor, Gary Patterson, editor ; sponsored by ACS Division of Polymer Chemistry, Inc.
出版情報: [Washington, DC] : American Chemical Society, c2022  1 online resource (240 p.)
シリーズ名: ACS symposium series ; 1356
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10.

電子ブック
ＥＢ
10. Cellular biophysics and modeling : a primer on the computational biology of excitable cells (: electronic bk)
Greg Conradi Smith
出版情報:   1 online resource (xii, 382 p.)
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