The Pattern Recognition in Bioinformatics (PRIB) meeting was established in 2006 under the auspices of the International Association for Pattern Recognition (IAPR) to create a focus for the development and application of pattern recognition techniques in the biological domain. PRIB s aim to explore the full spectrum of pattern recognition application was re?ected in the breadth of techniquesrepresented in this year s subm- sions and in this book. These range from image analysis for biomedical data to systems biology. We werefortunatetohaveinvitedspeakersofthehighestcalibredeliveringkeynotes at…mehr
The Pattern Recognition in Bioinformatics (PRIB) meeting was established in 2006 under the auspices of the International Association for Pattern Recognition (IAPR) to create a focus for the development and application of pattern recognition techniques in the biological domain. PRIB s aim to explore the full spectrum of pattern recognition application was re?ected in the breadth of techniquesrepresented in this year s subm- sions and in this book. These range from image analysis for biomedical data to systems biology. We werefortunatetohaveinvitedspeakersofthehighestcalibredeliveringkeynotes at the conference. These were Pierre Baldi (UC Irvine), Alvis Brazma (EMBL-EBI), GunnarRats ch(MPITubi ngen)andMichaelUnser(EPFL).Weacknowledgesupportof theEUFP7NetworkofExcellencePASCAL2forpartiallyfundingtheinvitedspeakers. Immediately prior to the conference, we hosted half day of tutorial lectures, while a special session on Machine Learningfor IntegrativeGenomics was held immediately after the main conference.Duringthe conference,a poster session was heldwith further discussion. Wewouldlikeonceagaintothankalltheauthorsforthehighqualityofsubmissions, as well as Yorkshire South and the University of Shef?eld for providing logistical help in organizing the conference. Finally, we would like to thank Springer for their help in assembling this proceedings volume and for the continued support of PRIB.
Artikelnr. des Verlages: 12747078, 978-3-642-04030-6
2009
Seitenzahl: 468
Erscheinungstermin: 28. August 2009
Englisch
Abmessung: 235mm x 155mm x 26mm
Gewicht: 704g
ISBN-13: 9783642040306
ISBN-10: 3642040306
Artikelnr.: 26850563
Inhaltsangabe
Evolutionary Parameters in Sequence Families. MProfiler: A Profile Based Method for DNA Motif Discovery. On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification. Joint Tracking of Cell Morphology and Motion. Multiclass Microarray Gene Expression Analysis Based on Mutual Dependency Models. An Efficient Convex Nonnegative Network Component Analysis for Gene Regulatory Network Reconstruction. Using Higher Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana. Sequential Hierarchical Pattern Clustering. Syntactic Pattern Recognition Using Finite Inductive Strings. Evidence Based Clustering of Reads and Taxonomic Analysis of Metagenomic Data. Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors. Definition of Valid Proteomic Biomarkers: A Bayesian Solution. Inferring Meta covariates in Classification. A Multiobjective Evolutionary Algorithm for Numerical Parameter Space Characterization of Reaction Diffusion Systems. Knowledge Guided Docking of WW Domain Proteins and Flexible Ligands. Distinguishing Regional from Within Codon Rate Heterogeneity in DNA Sequence Alignments. A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms. Di codon Usage for Gene Classification. Counting Patterns in Degenerated Sequences. Modelling Stem Cells Lineages with Markov Trees. Bi clustering of Gene Expression Data Using Conditional Entropy. c GAMMA:Comparative Genome Analysis of Molecular Markers. Semi supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics. Classification of Protein Interaction Sentences via Gaussian Processes. MCMC Based Bayesian Inference for Modeling Gene Networks. Efficient Optimal Multi level Thresholding for Biofilm Image Segmentation. A Pattern Classification Approach to DNA Microarray Image Segmentation. Drugs and Drug Like Compounds: Discriminating Approved Pharmaceuticals from Screening Library Compounds. Fast SCOP Classification of Structural Class and Fold Using Secondary Structure Mining in Distance Matrix. Short Segment Frequency Equalization: A Simple and Effective Alternative Treatment of Background Models in Motif Discovery. Bayesian Optimization Algorithm for the Non unique Oligonucleotide Probe Selection Problem. Microarray Time Series Data Clustering via Multiple Alignment of Gene Expression Profiles. Recursive Neural Networks for Undirected Graphs for Learning Molecular Endpoints. Enhancing the Effectiveness of Fingerprint Based Virtual Screening: Use of Turbo Similarity Searching and of Fragment Frequencies of Occurrence. Patterns, Movement and Clinical Diagnosis of Abdominal Adhesions. Class Prediction from Disparate Biological Data Sources Using an Iterative Multi Kernel Algorithm. Cross Platform Analysis with Binarized Gene Expression Data.
Evolutionary Parameters in Sequence Families. MProfiler: A Profile Based Method for DNA Motif Discovery. On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification. Joint Tracking of Cell Morphology and Motion. Multiclass Microarray Gene Expression Analysis Based on Mutual Dependency Models. An Efficient Convex Nonnegative Network Component Analysis for Gene Regulatory Network Reconstruction. Using Higher Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana. Sequential Hierarchical Pattern Clustering. Syntactic Pattern Recognition Using Finite Inductive Strings. Evidence Based Clustering of Reads and Taxonomic Analysis of Metagenomic Data. Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks. Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors. Definition of Valid Proteomic Biomarkers: A Bayesian Solution. Inferring Meta covariates in Classification. A Multiobjective Evolutionary Algorithm for Numerical Parameter Space Characterization of Reaction Diffusion Systems. Knowledge Guided Docking of WW Domain Proteins and Flexible Ligands. Distinguishing Regional from Within Codon Rate Heterogeneity in DNA Sequence Alignments. A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms. Di codon Usage for Gene Classification. Counting Patterns in Degenerated Sequences. Modelling Stem Cells Lineages with Markov Trees. Bi clustering of Gene Expression Data Using Conditional Entropy. c GAMMA:Comparative Genome Analysis of Molecular Markers. Semi supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics. Classification of Protein Interaction Sentences via Gaussian Processes. MCMC Based Bayesian Inference for Modeling Gene Networks. Efficient Optimal Multi level Thresholding for Biofilm Image Segmentation. A Pattern Classification Approach to DNA Microarray Image Segmentation. Drugs and Drug Like Compounds: Discriminating Approved Pharmaceuticals from Screening Library Compounds. Fast SCOP Classification of Structural Class and Fold Using Secondary Structure Mining in Distance Matrix. Short Segment Frequency Equalization: A Simple and Effective Alternative Treatment of Background Models in Motif Discovery. Bayesian Optimization Algorithm for the Non unique Oligonucleotide Probe Selection Problem. Microarray Time Series Data Clustering via Multiple Alignment of Gene Expression Profiles. Recursive Neural Networks for Undirected Graphs for Learning Molecular Endpoints. Enhancing the Effectiveness of Fingerprint Based Virtual Screening: Use of Turbo Similarity Searching and of Fragment Frequencies of Occurrence. Patterns, Movement and Clinical Diagnosis of Abdominal Adhesions. Class Prediction from Disparate Biological Data Sources Using an Iterative Multi Kernel Algorithm. Cross Platform Analysis with Binarized Gene Expression Data.
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