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Herausgeber: 
  • Elena Marchiori
  • Evgeni Tsivtsivadze
  • Tom Heskes
  • Tjeerd M.H. Dijkstra
  • Pattern Recognition in Bioinformatics: 5th IAPR International Conference, PRIB 2010, Nijmegen, The Netherlands, September 22-24, 2010, Proceedings 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2010  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Automated Pattern Recognition / bioinformatics / C / Computational and Systems Biology / Computational Biology/Bioinformatics / Computer applications in industry and technology / computer science / Computeranwendungen in Industrie und Technologie
    ISBN:  9783642160004 
    EAN-Code: 
    9783642160004 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Lecture Notes in Bioinformatics
    #6282 - Lecture Notes in Computer Science  
    Dimensionen:  H / B / D  
    Gewicht:  718 gr 
    Seiten:  442 
    Illustration:  XII, 442 p. 153 illus., schwarz-weiss Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Classification of Biological Sequences.- Sequence-Based Prediction of Protein Secretion Success in Aspergillus niger.- Machine Learning Study of DNA Binding by Transcription Factors from the LacI Family.- Joint Loop End Modeling Improves Covariance Model Based Non-coding RNA Gene Search.- Structured Output Prediction of Anti-cancer Drug Activity.- SLiMSearch: A Webserver for Finding Novel Occurrences of Short Linear Motifs in Proteins, Incorporating Sequence Context.- Towards 3D Modeling of Interacting TM Helix Pairs Based on Classification of Helix Pair Sequence.- Optimization Algorithms for Identification and Genotyping of Copy Number Polymorphisms in Human Populations.- Preservation of Statistically Significant Patterns in Multiresolution 0-1 Data.- Novel Machine Learning Methods for MHC Class I Binding Prediction.- Unsupervised Learning Methods for Biological Sequences.- SIMCOMP: A Hybrid Soft Clustering of Metagenome Reads.- The Complexity and Application of Syntactic Pattern Recognition Using Finite Inductive Strings.- An Algorithm to Find All Identical Motifs in Multiple Biological Sequences.- Discovery of Non-induced Patterns from Sequences.- Exploring Homology Using the Concept of Three-State Entropy Vector.- A Maximum-Likelihood Formulation and EM Algorithm for the Protein Multiple Alignment Problem.- Polynomial Supertree Methods Revisited.- Enhancing Graph Database Indexing by Suffix Tree Structure.- Learning Methods for Gene Expression and Mass Spectrometry Data.- Semi-Supervised Graph Embedding Scheme with Active Learning (SSGEAL): Classifying High Dimensional Biomedical Data.- Iterated Local Search for Biclustering of Microarray Data.- Biologically-aware Latent Dirichlet Allocation (BaLDA) for the Classification of Expression Microarray.- Measuring the Quality of Shifting and Scaling Patterns in Biclusters.- Frequent Episode Mining to Support Pattern Analysis in Developmental Biology.- Time Series Gene Expression Data Classification via L 1-norm Temporal SVM.- Bioimaging.- Sub-grid and Spot Detection in DNA Microarray Images Using Optimal Multi-level Thresholding.- Quantification of Cytoskeletal Protein Localization from High-Content Images.- Pattern Recognition for High Throughput Zebrafish Imaging Using Genetic Algorithm Optimization.- Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis.- Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging.- Molecular Structure Prediction.- A Matrix Algorithm for RNA Secondary Structure Prediction.- Exploiting Long-Range Dependencies in Protein ?-Sheet Secondary Structure Prediction.- Alpha Helix Prediction Based on Evolutionary Computation.- An On/Off Lattice Approach to Protein Structure Prediction from Contact Maps.- Protein Protein Interaction and Network Inference.- Biological Protein-Protein Interaction Prediction Using Binding Free Energies and Linear Dimensionality Reduction.- Employing Publically Available Biological ExpertKnowledge from Protein-Protein Interaction Information.- SFFS-MR: A Floating Search Strategy for GRNs Inference.- Revisiting the Voronoi Description of Protein-Protein Interfaces: Algorithms.- MC4: A Tempering Algorithm for Large-Sample Network Inference.- Flow-Based Bayesian Estimation of Nonlinear Differential Equations for Modeling Biological Networks.

      



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