Biocomputing 2012 - Proceedings Of The Pacific Symposium.

• Author: Klein, Teri E.
• TeilnehmendeR: Jung, Tiffany A.; Hunter, Lawrence.; Dunker, A Keith.; Altman, Russ B.
• Place / Publishing House: Singapore : : World Scientific Publishing Company,, 2011.; ©2012.
• Year of Publication: 2011
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (455 pages)

Table of Contents

• Intro
• Contents
• Preface
• IDENTIFICATION OF ABERRANT PATHWAY AND NETWORK ACTIVITY FROM HIGH-THROUGHPUT DATA
• Session Introduction Rachel Karchin, Michael F. Ochs, Joshua M. Stuart, and Joel S. Bader
• Introduction
• Genetic interaction networks in model organisms
• Human data and local subnetworks
• Converging problems and challenges
• References
• SSLPred : Predicting Synthetic Sickness Lethality Nirmalya Bandyopadhyayy, Sanjay Ranka, and Tamer Kahveci
• 1. Introduction
• 2. Background
• 3. Methods
• 3.1. Problem Formulation and Notation
• 3.2. Between Pathway Conjectures
• 3.3. Regression based solution
• 4. Experiments
• 4.1. Datasets
• 4.2. Comparison with Hescott's Method
• 5. Conclusion
• References
• Predicting the Effects of Copy-Number Variation in Double and Triple Mutant Combinations Gregory W. Carter, Michelle Hays, Song Li, and Timothy Galitski
• 1. Introduction
• 2. Network Model Inference
• 2.1.1. Yeast Gene Expression Profiling
• 2.1.2. Singular Value Decomposition Analysis
• 2.1.3. Genetic Influences Decomposition
• 2.2. Predictions and Validation for a Multicopy Perturbation
• 2.2.1. Prediction for Multi-Copy Strains
• 2.2.2. Experimental Test of Predictions
• 3. Discussion and Conclusions
• 4. Supplementary Material
• 5. Acknowledgments
• References
• Integrative Network Analysis to Identify Aberrant Pathway Networks in Ovarian Cancer Li Chen, Jianhua Xuan, Jinghua Gu, Yue Wang, Li Chen, Zhen Zhang, Tian-Li Wang, and Ie-Ming Shih
• 1. Introduction
• 2. Materials and method
• 2.1. Integrative framework
• 2.2. Data description
• 2.3. DNA copy number consensus region detection
• 2.4. Network identification by bootstrapping MRF (BMRF)
• 2.5. Network constrained support vector machines (NetSVM)
• 2.6. Classification performance merits and survival analysis
• 3. Results and discussion.
• 4. Conclusion
• 5. Acknowledgments
• References
• Role of Synthetic Genetic Interactions in Understanding Functional Interactions Among Pathways Shahin Mohammadi, Giorgos Kollias, and Ananth Grama
• 1. Introduction
• 2. Methods
• 2.1. Notations
• 2.2. Performance of local methods for predicting functional similarity of gene pairs
• 2.3. Constructing the neighborhood overlap graph (NOG)
• 2.4. Identifying interaction ports and inferring cross-pathway dependencies
• 3. Results
• 3.1. Datasets
• 3.1.1. Genetic interaction network
• 3.1.2. Functional annotations
• 3.1.3. Availability
• 3.2. Similarity of genetic neighborhood as a predictor of functional similarity
• 3.3. Constructing KEGG crosstalk map
• 4. Discussion
• 5. Acknowledgments
• References
• Discovery of Mutated Subnetworks Associated with Clinical Data in Cancer Fabio Vandin, Patrick Clay, Eli Upfal, and Benjamin J. Raphael
• 1. Introduction
• 2. Methods
• 2.1. Generalized HotNet
• 2.2. Adaptation to Clinical Data
• 2.2.1. Gene Scores
• 2.2.2. Selection of parameters t and
• 2.2.3. The Null Hypothesis Distribution
• 3. Results
• 3.1. Simulated data
• 3.2. Ovarian TCGA data
• 4. Discussion
• 5. Acknowledgements
• References
• INTRINSICALLY DISORDERED PROTEINS: ANALYSIS, PREDICTION, SIMULATION, AND BIOLOGY
• Session Introduction Jianhan Chen, Jianlin Cheng, and A. Keith Dunker
• 1. Introduction
• 2. Papers in this Session
• Analysis of IDPs' function and evolution
• Simulation of IDPs' conformation
• Prediction of IDPs
• Acknowledgements
• Quasi-Anharmonic Analysis Reveals Intermediate States in the Nuclear Co-Activator Receptor Binding Domain Ensemble Virginia M. Burger, Arvind Ramanathan, Andrej J. Savol, Christopher B. Stanly, Pratul K. Agarwal, and Chakra S. Chennubhotla
• 1. Introduction
• 2. Approach
• 3. Molecular Simulations for NCBD.
• 4. dQAA: Quasi-anharmonic analysis in the dihedral angle space
• 5. Hierarchical clustering in the dQAA-space to identify meta-stable states
• 6. Intermediate states of ligand-free NCBD access ligand-bound conformations
• 7. Conclusions and Future Work
• References
• Efficient Construction of Disordered Protein Ensembles in a Bayesian Framework with Optimal Selection of Conformations Charles K. Fisher, Orly Ullman, and Collin M. Stultz
• 1. Introduction
• 2. Theory
• 2.1. Optimal Structure Selection
• 2.2. Variational Bayesian Weighting
• 2.3. Variational Bayes with Structure Selection
• 2.3. Approximate Confidence Intervals
• 3. Results and Discussion
• 3.1. Validation with Reference Ensembles
• 3.2. α-Synuclein Ensemble
• 4. Conclusions
• 5. Acknowledgements
• References
• Correlation Between Posttranslational Modification and Intrinsic Disorder in Protein Jianjiong Gao and Dong Xu
• 1. Background
• 2. Results
• 2.1. Correlation of PTM sites and their predicted disorder scores
• 2.2. Correlation of PTM sites and their spatial fluctuations in NMR 3-D structures
• 2.3. Spatial fluctuation changes in 3-D structure due to PTM
• 3. Discussion
• Acknowledgments
• References
• Intrinsic Disorder Within and Flanking the DNA-Binding Domains of Human Transcription Factors Xin Guo, Martha L. Bulyk, and Alexander J. Hartemink
• 1. Introduction
• 2. Materials and Methods
• 2.1. Constructing the TF and non-TF control sets of proteins
• 2.2. Comparing the TF and non-TF control sets of proteins
• 2.3. Identifying DNA-binding domains (DBDs) and their locations within proteins
• 2.4. Predicting intrinsically disordered regions (IDRs) and their locations within proteins using multiple existing methods
• 2.5. Defining disorder features: spatial relationships of IDRs relative to DBDs within TFs.
• 2.6. Calculating statistical significance of disorder features
• 3. Results
• 3.1. Comparing the three methods for predicting IDRs within proteins
• 3.2. Assessing significance of order or disorder within and anking human TF DBDs
• 3.3. Investigating detailed spatial relationships of IDRs relative to DBDs within TFs
• 3.4. Analyzing spatial relationships for some DBD classes prevalent in human TFs
• 3.4.1. Zinc ngers
• 3.4.2. Homeobox
• 3.4.3. HLH
• 4. Discussion
• 5. Acknowledgments
• References
• Intrinsic Protein Disorder and Protein-Protein Interactions Wei-Lun Hsu, Christopher Oldfield, Jingwei Meng, Fei Huang, Bin Xue, Vladimir N. Uversky, Pedro Romero, and A. Keith Dunker
• 1. Introduction
• 2. Results
• 2.1 Disordered hub dataset
• 2.2 Functional consequences of MoRF (or ELM) binding
• 2.3 Binding to multiple partners, conservation at structure-matching sites
• 3. Discussion
• 4. Methods
• 4.1 Disordered hub dataset
• 4.2 Sequence and Structure analysis
• References
• Subclassifying Disordered Proteins by the CH-CDF Plot Method Fei Huang, Christopher Oldfield, Jingwei Meng, Wei-lun Hsu, Bin Xue, Vladimir N. Uversky, Pedro Romero, and A. Keith Dunker
• 1. Introduction
• 2. Results
• 2.1 CH-CDF plot
• 2.2 PDB coverage
• 2.3 Sequence window CH-CDF analysis
• 2.4 Match PDB coverage to disorder prediction
• 2.5 Function analysis for each quadrant
• 3. Discussion
• 3.1 Overview
• 3.2 Structural Partitioning by the CH-CDF plot
• 3.2 The rare protein quadrant (Q1)
• 3.3 Disorder subtypes and IDP functions
• 4. Methods
• 4.1 Protein data
• 4.2 PDB Coverage
• 4.2 GO term analysis
• References
• Coevolved Residues and the Functional Association for Intrinsically Disordered Protein Chan-Seok Jeong and Dongsup Kim
• 1. Introduction
• 2. Materials and methods
• 2.1. Data set.
• 2.2. Multiple sequence alignment construction
• 2.3. Coevolution estimation
• 2.4. Sequence conservation estimation
• 2.5. Disorder conservation estimation
• 2.6. Functional categories
• 3. Results
• 3.1. Distribution of coevolved residues for disordered proteins
• 3.2. Relationship between coevolution and functions
• 4. Discussion
• Acknowledgments
• References
• Cryptic Disorder: An Order-Disorder Transformation Regulates the Function of Nucleophosmin Diana M. Mitrea and Richard W. Kriwacki
• 1. Biological Function and Structural Features of Npm
• 2. Alteration of the electrostatic features of Npm-N through phosphorylation
• 3. In Silico site-directed mutagenesis
• 4. Probing for structural strain in Npm-N
• 5. Mechanistic insights on Npm's order-disorder polymorphism
• 6. Materials and Methods
• References
• Functional Annotation of Intrinsically Disordered Domains by Their Amino Acid Content Using IDD Navigator Ashwini Patil, Shunsuke Teraguchi, Huy Dinh, Kenta Nakai, and Daron M Standley
• 1. Introduction Intrinsically disordered domains
• 2. Methodology
• 2.1. Preparation of IDD dataset
• 2.2. Similarity scores
• 2.2.1. Similarity score based on Euclidean distance
• 2.2.2. BLAST score
• 2.3. Pfam domain and Gene Ontology term prediction
• 2.4. Evaluation of function prediction
• 2.5. Web server
• 3. Results and Discussion
• 3.1 IDD Navigator Function prediction
• 3.2 Comparing different methods in IDD Navigator
• 3.3 Function prediction for IDD clusters
• 3.4 Case Studies
• 3.4.1 GRA15 from T. gondii
• 3.4.2 Cyclon from M. musculus
• 3.4.3 STIM1 from M. musculus
• 3.4.4 ROP16 from T. gondii
• 4. Conclusions
• 5. Acknowledgements
• References
• On the Complementarity of the Consensus-Based Disorder Prediction Zhenling Peng and Lukasz Kurgan
• 1. Introduction
• 2. Methods.
• 2.1. Considered disorder predictors.