OSTİM Technical University Library

Sepetiniz boş.

Genome Informatics 2009.

Yazar:Sakakibara, Yasubumi
Katkıda bulunan(lar):Morishita, Shinichi | Lee, Sang Yup
Materyal türü: KonuKonuYayıncı: Singapore : World Scientific Publishing Company, 2009Telif hakkı tarihi: �2009Tanım: 1 online resource (243 pages)İçerik türü:text Ortam türü:computer Taşıyıcı türü: online resourceISBN: 9781848165632Tür/Form:Electronic books.Ek fiziksel biçimler:Print version:: Genome Informatics 2009: Genome Informatics Series Vol. 23 - Proceedings Of The 20th International ConferenceÇevrimiçi kaynaklar: Click to View
İçindekiler:
Intro -- CONTENTS -- Preface -- Acknowledgments -- Committees -- Part A Full Papers -- Predicting Protein-Protein Relationships from Literature Using Latent Topics T. Aso �j K. Eguchi -- 1. Introduction -- 2. LDA and Estimation Algorithms -- 2.1. Generative Process of LDA -- 2.2. Collapsed Gibbs Sampling Inference -- 2.3. Collapsed Variational Bayesian Inference -- 3. Protein-Protein Relationship Prediction based on LDA -- 4. Data and Entity Representation -- 4.1. GENIA Collection -- 4.2. TREC Collection and GENIA Tagger -- 5. Experiments -- 5.1. Log-Likelihood -- 5.2. Entity-Link Prediction -- 5.2.1. Experimental Settings -- 5.2.2. Task-based Evaluation -- 5.2.3 . Protein-Protein Relationship Network -- 6. Conclusions -- Acknowledgments -- References -- Evaluation of DNA Intramolecular Interactions for Nucleosome Positioning in Yeast M. Fernandez, S. Fujii, H. Kono �j A. Sarai -- 1. Introduction -- 2. Method and Results -- 2.1. Intramolecular Interaction Energy Calculation -- 2.2. Oscillation Pattern of Dinucleotides Along the Nucleosome Structure -- 2.3. Intramolecular Energy Profile of Yeast Genome -- 3. Discussions -- References -- Quality Control and Reproducibility in DNA Microarray Experiments A. Fujita, J. R. Sato, F. H. L. da Silva, M. C. Galviio, M. C. Sogayar �j S. Miyano -- 1. Introduction -- 2. Materials and Methods -- 2.1. Dahlberg's Error (D.E.) -- 2.2. Support Vector Regression (SVR) -- 2.3. Modeling DNA Microarray Data -- 2.4. DNA Microarray -- 2.4 .1. Cell Lysis and RNA Extraction -- 2.4.2. Labeling and Purification of Targets -- 2.4.3. Hybridization and Washing of the DNA Arrays -- 3. Results and Discussions -- Acknowledgments -- References -- Comparative Analysis of Topological Patterns in Different Mammalian Networks B. Goemann, A. P. Potapov, M. Ante �j E. Wingender -- 1. Introduction -- 2 Methods.
2.1 Construction of the Networks -- 2.2 Computation of the Painvise Discollnect -- v -- ty Index -- 3 Results and Discussion -- 3.1 Autoregulation as a Feature of the Most 1mportant Nodes -- 3.2 The Mutual Regulation of Two Nodes is a Motif -- 3.3 Three-Node Patterns in the Networks Analyzed -- 3.4 Largelmportant Subnetworks Derived from Pattern Analysis -- 4 Conclusions -- Acknowledgments -- References -- Tools for Investigating Mechanisms of Antigenic Variation: New Extensions to varDB C. N. Hayes, D. Diez, N. Joannin, M. Kanehisa, M. Wahlgren, C. E. Wheelock �j S. Goto -- 1. Introduction -- 2. Tools for Investigating Mechanisms of Antigenic Variation -- 2.1. Sequence Selection and Preparation -- 2.2. Generating a Codon Alignment -- 2.3 . Analyzing Codon Usage -- 2.4. Nucleotide Repeats and DNA Secondary Structure -- 2.5. Mutation Hotspot Motifs -- 2.6. Recombination -- 2.7. Variability and Immune Selection -- 3. Conclusions -- Acknowledgments -- References -- Localized Suffix Array and Its Application to Genome Mapping Problems for Paired-End Short Reads K. Kimura 8 A. Koike -- 1. Introduction -- 2. Localized Suffix Array (LSA) -- 2.1. Basic Idea -- 2.2. Procedural Introduction of Recursive Localization (RL) and LSA -- 2.3. Algorithms for LSA Construction and RL of Index Intervals -- 3. Application to Paired-End (PE) Mapping Problems -- 3.1. Single-End (SE) Mapping Method -- 3.2. Paired-End (PE) Search Methods -- 3.3. Experimental Results -- 4. Additional Results and Discussions -- 5. Conclusions -- References -- Comparative Analysis of Aerobic and Anaerobic Prokaryotes to Identify Correlation between Oxygen Requirement and Gene-Gene Functional Association Patterns y. Lin 8 H. Wu -- 1. Introduction -- 2. Aerobic and Anaerobic Prokaryotes -- 3. Quantification of Gene-Gene Functional Association -- 3.1. Stochastic Model for Gene Arrangement.
3.2. Validation of Gene-Gene Functional Association Measures -- 3.2.1. Validation of the A (gi, gj) Measures based on Biological Process Ontology Annotations -- 3.2.2. Validation of the A (gi, gj ) Measures based on KEGG Pathway Annotations -- 4. Identification of Gene Pairs with Different Functional Association Patterns under the Two Different Oxygen Requirement Conditions -- 4.1. Student's t-Test Results -- 4.2. Biological Implications of the Gene Pairs with Large/Small p- Values -- 5. Prediction of Oxygen Requirement Conditions Based on certain Gene-Gene Functional Association Patterns -- 6. Conclusion -- Acknow ledgments -- References -- Calculation of Protein-Ligand Binding Free Energy Using Smooth Reaction Path Generation (SRPG) Method: A Comparison of the Explicit Water Model, GB/SA Model and Docking Score Function D. Mitomo, Y. Fukunishi, J. Higo 8 H. Nakamura -- 1. Introduction -- 2. Methods and Materials -- 2.1. ..1G Calculation -- 2.2. Ligand Dissociation Path -- 2.3. Smooth Reaction Path -- 2.4. PMF Calculation -- 2.5. Computational Models -- 3. Results -- 4. Discussion -- 5. Conclusion -- Acknowledgments -- References -- Structural Insights into the Enzyme Mechanism of a New Family of D-2-Hydroxyacid Dehydrogenases, a Close Homolog of 2-Ketopantoate Reductase S. Mondal 8 K. Mizuguchi -- 1. Introduction -- 2. Material and Methods -- 2.1. Comparative Modeling and Structural Analysis -- 2.2. Normal Mode Analysis -- 3. Results -- 3.1. Comparative Modeling -- 3.2. Hinge Bending -- 3.3. Cofactor Recognition -- 3.4. Substrate Recognition -- 4. Discussion -- 5. Conclusions -- Acknowledgments -- References -- Comprehensive Analysis of Sequence-Structure Relationships in the Loop Regions of Proteins S. Nakamura 8 K. Shimizu -- 1. Introduction -- 2. Materials and Methods -- 2.1. Preparation of Datasets -- 2.2. Predictions Using SVR.
2.3. Calculation of Prediction Accuracy -- 2.4. Random Prediction -- 2.5. Dataset from GASP8 Targets -- 3. Results and Discussion -- 4. Conclusion -- References -- The Prediction of Local Modular Structures in a Co-Expression Network Based on Gene Expression Datasets Y. Ogata, N. Sakurai, H. Suzuki, K. Aoki, K. Saito 8 D. Shibata -- 1. Introduction -- 2. Method and Results -- 2.1. Definitions -- 2.2. Microarray datasets -- 2.3. An algorithm to extract co-expression modules -- 2.4. Testing -- 2.5. Implementation -- 3. Discussion -- 4. Conclusions -- Acknowledgments -- References -- Gradient-Based Optimization of Hyperparameters for Base-Pairing Profile Local Alignment Kernels K. Sato, Y. Saito 8 Y. Sakakibara -- 1. Introduction -- 2. Methods -- 2.1. Base-Pairing Profile Local Alignment Kernels -- 2.2. Gradient-Based Optimization for SVMs -- 3. Results -- 4. Discussion -- 5. Conclusion -- Acknowledgments -- References -- A Method for Efficient Execution of Bioinformatics Workfiows 1. Seo, Y. Kido, S. Seno, Y. Takenaka 8 H. Matsuda -- 1. Introduction -- 2. Workflow Operations in Hybrid Architecture -- 3. Improved Method -- 4. Experimental Result -- 4.1. Experiment with Test Web Services -- 4.2. Experiment with Bioinformatics Web Services in Distributed Environment -- 5. Discussion -- References -- Development of a New Meta-Score for Protein Structure Prediction from Seven All-Atom Distance Dependent Potentials Using Support Vector Regression M. Shirota, T. Ishida 8 K. Kinoshita -- 1. Introduction -- 2. Materials and Methods -- 2.1. Decoy Sets -- 2.2. Quality of the Structure -- 2.3. Component Statistical Potentials -- 2.4. Normalization of the All-Atom Distance Dependent Potentials -- 2.5. Development of the Meta-Score -- 2.6. Assessment of Potentials -- 2.7. Statistical Significance of the Difference in Performance -- 3. Results and Discussion.
3.1. Performances for the Training Set -- 3.2. Performances for the Test Set -- 3.3. Evaluation of the Meta-Score as an Absolute Quality Score for Protein Structures -- 4. Conclusion -- Acknowledgments -- References -- Refining Markov Clustering for Protein Complex Prediction by Incorporating Core-Attachment Structure S. Srihari, K. Ning fj H. W. Leong -- 1. Introduction -- 2. Methods -- 2.1. Clustering the PPI Graph Using MCL -- 2.2. Determining Core Proteins -- 2.3. Filtering Out Noisy Clusters -- 2.4. Determining Attachment Proteins -- 2.5. Determining Module Proteins -- 2.6. Determining Complexes and Ranking them -- 3. Results and Discussions -- 3.1. Improvement over MeL -- 3.2. Comparisons with CORE and COA CH -- 3.3. Analysis of Complexes Predicted by MCL-CA -- 4. Conclusions and Future Work -- Acknowledgments -- References -- An Assessment of Prediction Algorithms for Nucleosome Positioning Y. Tanaka fj K. Nakai -- 1. Introduction -- 2. Materials and Methods -- 2.1. Genome-Scale Nucleosome Maps -- 2.2. Application of Prediction Algorithms -- 2.3. Receiver Operating Characteristic (ROC) Curve -- 2.4. Over- and Under-Represented Oligomers -- 3 Results and Discussion -- 3.1 Prediction Ability 0/ Each Algorithm/or Overall Nucleosomes -- 3.2 General and Specific Sequence Dependencies in Nucleosome Positioning ~ ,' -- 4 Conclusions -- Additional Data and URL -- Acknowledgments -- References -- Cancer Classification Using Single Genes X. Wang fj O. Gotoh -- 1. Introduction -- 2. Materials and Methods -- 2.1. Datasets -- 2.2. Rough Sets -- 2.3. Data Preprocessing, Gene Selection and Classification -- 3. Results -- 3.1. Classification Results -- 3.2. Comparison of Classification Results -- 3.3. Analysis of Results -- 4. Discussion -- References.
RECOUNT: Expectation Maximization Based Error Correction Tool for Next Generation Sequencing Data E. Wijaya, M. C. Frith, Y. Suzuki &amp.
Bu kütüphanenin etiketleri: Kütüphanedeki eser adı için etiket yok. Etiket eklemek için oturumu açın.
    Ortalama derecelendirme: 0.0 (0 oy)
Bu kayda ilişkin materyal yok

Intro -- CONTENTS -- Preface -- Acknowledgments -- Committees -- Part A Full Papers -- Predicting Protein-Protein Relationships from Literature Using Latent Topics T. Aso �j K. Eguchi -- 1. Introduction -- 2. LDA and Estimation Algorithms -- 2.1. Generative Process of LDA -- 2.2. Collapsed Gibbs Sampling Inference -- 2.3. Collapsed Variational Bayesian Inference -- 3. Protein-Protein Relationship Prediction based on LDA -- 4. Data and Entity Representation -- 4.1. GENIA Collection -- 4.2. TREC Collection and GENIA Tagger -- 5. Experiments -- 5.1. Log-Likelihood -- 5.2. Entity-Link Prediction -- 5.2.1. Experimental Settings -- 5.2.2. Task-based Evaluation -- 5.2.3 . Protein-Protein Relationship Network -- 6. Conclusions -- Acknowledgments -- References -- Evaluation of DNA Intramolecular Interactions for Nucleosome Positioning in Yeast M. Fernandez, S. Fujii, H. Kono �j A. Sarai -- 1. Introduction -- 2. Method and Results -- 2.1. Intramolecular Interaction Energy Calculation -- 2.2. Oscillation Pattern of Dinucleotides Along the Nucleosome Structure -- 2.3. Intramolecular Energy Profile of Yeast Genome -- 3. Discussions -- References -- Quality Control and Reproducibility in DNA Microarray Experiments A. Fujita, J. R. Sato, F. H. L. da Silva, M. C. Galviio, M. C. Sogayar �j S. Miyano -- 1. Introduction -- 2. Materials and Methods -- 2.1. Dahlberg's Error (D.E.) -- 2.2. Support Vector Regression (SVR) -- 2.3. Modeling DNA Microarray Data -- 2.4. DNA Microarray -- 2.4 .1. Cell Lysis and RNA Extraction -- 2.4.2. Labeling and Purification of Targets -- 2.4.3. Hybridization and Washing of the DNA Arrays -- 3. Results and Discussions -- Acknowledgments -- References -- Comparative Analysis of Topological Patterns in Different Mammalian Networks B. Goemann, A. P. Potapov, M. Ante �j E. Wingender -- 1. Introduction -- 2 Methods.

2.1 Construction of the Networks -- 2.2 Computation of the Painvise Discollnect -- v -- ty Index -- 3 Results and Discussion -- 3.1 Autoregulation as a Feature of the Most 1mportant Nodes -- 3.2 The Mutual Regulation of Two Nodes is a Motif -- 3.3 Three-Node Patterns in the Networks Analyzed -- 3.4 Largelmportant Subnetworks Derived from Pattern Analysis -- 4 Conclusions -- Acknowledgments -- References -- Tools for Investigating Mechanisms of Antigenic Variation: New Extensions to varDB C. N. Hayes, D. Diez, N. Joannin, M. Kanehisa, M. Wahlgren, C. E. Wheelock �j S. Goto -- 1. Introduction -- 2. Tools for Investigating Mechanisms of Antigenic Variation -- 2.1. Sequence Selection and Preparation -- 2.2. Generating a Codon Alignment -- 2.3 . Analyzing Codon Usage -- 2.4. Nucleotide Repeats and DNA Secondary Structure -- 2.5. Mutation Hotspot Motifs -- 2.6. Recombination -- 2.7. Variability and Immune Selection -- 3. Conclusions -- Acknowledgments -- References -- Localized Suffix Array and Its Application to Genome Mapping Problems for Paired-End Short Reads K. Kimura 8 A. Koike -- 1. Introduction -- 2. Localized Suffix Array (LSA) -- 2.1. Basic Idea -- 2.2. Procedural Introduction of Recursive Localization (RL) and LSA -- 2.3. Algorithms for LSA Construction and RL of Index Intervals -- 3. Application to Paired-End (PE) Mapping Problems -- 3.1. Single-End (SE) Mapping Method -- 3.2. Paired-End (PE) Search Methods -- 3.3. Experimental Results -- 4. Additional Results and Discussions -- 5. Conclusions -- References -- Comparative Analysis of Aerobic and Anaerobic Prokaryotes to Identify Correlation between Oxygen Requirement and Gene-Gene Functional Association Patterns y. Lin 8 H. Wu -- 1. Introduction -- 2. Aerobic and Anaerobic Prokaryotes -- 3. Quantification of Gene-Gene Functional Association -- 3.1. Stochastic Model for Gene Arrangement.

3.2. Validation of Gene-Gene Functional Association Measures -- 3.2.1. Validation of the A (gi, gj) Measures based on Biological Process Ontology Annotations -- 3.2.2. Validation of the A (gi, gj ) Measures based on KEGG Pathway Annotations -- 4. Identification of Gene Pairs with Different Functional Association Patterns under the Two Different Oxygen Requirement Conditions -- 4.1. Student's t-Test Results -- 4.2. Biological Implications of the Gene Pairs with Large/Small p- Values -- 5. Prediction of Oxygen Requirement Conditions Based on certain Gene-Gene Functional Association Patterns -- 6. Conclusion -- Acknow ledgments -- References -- Calculation of Protein-Ligand Binding Free Energy Using Smooth Reaction Path Generation (SRPG) Method: A Comparison of the Explicit Water Model, GB/SA Model and Docking Score Function D. Mitomo, Y. Fukunishi, J. Higo 8 H. Nakamura -- 1. Introduction -- 2. Methods and Materials -- 2.1. ..1G Calculation -- 2.2. Ligand Dissociation Path -- 2.3. Smooth Reaction Path -- 2.4. PMF Calculation -- 2.5. Computational Models -- 3. Results -- 4. Discussion -- 5. Conclusion -- Acknowledgments -- References -- Structural Insights into the Enzyme Mechanism of a New Family of D-2-Hydroxyacid Dehydrogenases, a Close Homolog of 2-Ketopantoate Reductase S. Mondal 8 K. Mizuguchi -- 1. Introduction -- 2. Material and Methods -- 2.1. Comparative Modeling and Structural Analysis -- 2.2. Normal Mode Analysis -- 3. Results -- 3.1. Comparative Modeling -- 3.2. Hinge Bending -- 3.3. Cofactor Recognition -- 3.4. Substrate Recognition -- 4. Discussion -- 5. Conclusions -- Acknowledgments -- References -- Comprehensive Analysis of Sequence-Structure Relationships in the Loop Regions of Proteins S. Nakamura 8 K. Shimizu -- 1. Introduction -- 2. Materials and Methods -- 2.1. Preparation of Datasets -- 2.2. Predictions Using SVR.

2.3. Calculation of Prediction Accuracy -- 2.4. Random Prediction -- 2.5. Dataset from GASP8 Targets -- 3. Results and Discussion -- 4. Conclusion -- References -- The Prediction of Local Modular Structures in a Co-Expression Network Based on Gene Expression Datasets Y. Ogata, N. Sakurai, H. Suzuki, K. Aoki, K. Saito 8 D. Shibata -- 1. Introduction -- 2. Method and Results -- 2.1. Definitions -- 2.2. Microarray datasets -- 2.3. An algorithm to extract co-expression modules -- 2.4. Testing -- 2.5. Implementation -- 3. Discussion -- 4. Conclusions -- Acknowledgments -- References -- Gradient-Based Optimization of Hyperparameters for Base-Pairing Profile Local Alignment Kernels K. Sato, Y. Saito 8 Y. Sakakibara -- 1. Introduction -- 2. Methods -- 2.1. Base-Pairing Profile Local Alignment Kernels -- 2.2. Gradient-Based Optimization for SVMs -- 3. Results -- 4. Discussion -- 5. Conclusion -- Acknowledgments -- References -- A Method for Efficient Execution of Bioinformatics Workfiows 1. Seo, Y. Kido, S. Seno, Y. Takenaka 8 H. Matsuda -- 1. Introduction -- 2. Workflow Operations in Hybrid Architecture -- 3. Improved Method -- 4. Experimental Result -- 4.1. Experiment with Test Web Services -- 4.2. Experiment with Bioinformatics Web Services in Distributed Environment -- 5. Discussion -- References -- Development of a New Meta-Score for Protein Structure Prediction from Seven All-Atom Distance Dependent Potentials Using Support Vector Regression M. Shirota, T. Ishida 8 K. Kinoshita -- 1. Introduction -- 2. Materials and Methods -- 2.1. Decoy Sets -- 2.2. Quality of the Structure -- 2.3. Component Statistical Potentials -- 2.4. Normalization of the All-Atom Distance Dependent Potentials -- 2.5. Development of the Meta-Score -- 2.6. Assessment of Potentials -- 2.7. Statistical Significance of the Difference in Performance -- 3. Results and Discussion.

3.1. Performances for the Training Set -- 3.2. Performances for the Test Set -- 3.3. Evaluation of the Meta-Score as an Absolute Quality Score for Protein Structures -- 4. Conclusion -- Acknowledgments -- References -- Refining Markov Clustering for Protein Complex Prediction by Incorporating Core-Attachment Structure S. Srihari, K. Ning fj H. W. Leong -- 1. Introduction -- 2. Methods -- 2.1. Clustering the PPI Graph Using MCL -- 2.2. Determining Core Proteins -- 2.3. Filtering Out Noisy Clusters -- 2.4. Determining Attachment Proteins -- 2.5. Determining Module Proteins -- 2.6. Determining Complexes and Ranking them -- 3. Results and Discussions -- 3.1. Improvement over MeL -- 3.2. Comparisons with CORE and COA CH -- 3.3. Analysis of Complexes Predicted by MCL-CA -- 4. Conclusions and Future Work -- Acknowledgments -- References -- An Assessment of Prediction Algorithms for Nucleosome Positioning Y. Tanaka fj K. Nakai -- 1. Introduction -- 2. Materials and Methods -- 2.1. Genome-Scale Nucleosome Maps -- 2.2. Application of Prediction Algorithms -- 2.3. Receiver Operating Characteristic (ROC) Curve -- 2.4. Over- and Under-Represented Oligomers -- 3 Results and Discussion -- 3.1 Prediction Ability 0/ Each Algorithm/or Overall Nucleosomes -- 3.2 General and Specific Sequence Dependencies in Nucleosome Positioning ~ ,' -- 4 Conclusions -- Additional Data and URL -- Acknowledgments -- References -- Cancer Classification Using Single Genes X. Wang fj O. Gotoh -- 1. Introduction -- 2. Materials and Methods -- 2.1. Datasets -- 2.2. Rough Sets -- 2.3. Data Preprocessing, Gene Selection and Classification -- 3. Results -- 3.1. Classification Results -- 3.2. Comparison of Classification Results -- 3.3. Analysis of Results -- 4. Discussion -- References.

RECOUNT: Expectation Maximization Based Error Correction Tool for Next Generation Sequencing Data E. Wijaya, M. C. Frith, Y. Suzuki &amp.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2022. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

There are no comments on this title.

yorum yazmak için.

Ziyaretçi Sayısı

Destekleyen Koha