Algorithms in Bioinformatics: 10th International Workshop, WABI 2010, Liverpool, UK, September 6-8, 2010, Proceedings (Lecture Notes in Computer Science, 6293, Band 6293) - Taschenbuch

EAN (ISBN-13): 9783642152931
ISBN (ISBN-10): 3642152937
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2010
Herausgeber: Springer Berlin
376 Seiten
Gewicht: 0,586 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2009-03-19T05:45:01+01:00 (Vienna)
Detailseite zuletzt geändert am 2023-07-27T19:02:00+02:00 (Vienna)
ISBN/EAN: 9783642152931

ISBN - alternative Schreibweisen:
3-642-15293-7, 978-3-642-15293-1
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: vincent, moulton, moult
Titel des Buches: wabi, bioinformatics, algorithms, workshop, liverpool, lecture notes computer science

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Daten vom Verlag:

Autor/in: Vincent Moulton; Mona Singh
Titel: Lecture Notes in Bioinformatics; Lecture Notes in Computer Science; Algorithms in Bioinformatics - 10th International Workshop, WABI 2010, Liverpool, UK, September 6-8, 2010, Proceedings
Verlag: Springer; Springer Berlin
376 Seiten
Erscheinungsjahr: 2010-08-25
Berlin; Heidelberg; DE
Sprache: Englisch
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
Available
XII, 376 p. 94 illus.

BC; Hardcover, Softcover / Biologie; Biowissenschaften, allgemein; Verstehen; Informatik; algorithms; bioinformatics; complexity; data structures; functional genomics; genetic mapping; metagenomics; ncrna sequencing; sorting; algorithm analysis and problem complexity; Life Sciences; Algorithms; Theory of Computation; Artificial Intelligence; Database Management; Computational and Systems Biology; Algorithmen und Datenstrukturen; Theoretische Informatik; Künstliche Intelligenz; Datenbanken; DV-gestützte Biologie/Bioinformatik; EA

Biomolecular Structure: RNA, Protein and Molecular Comparison.- A Worst-Case and Practical Speedup for the RNA Co-folding Problem Using the Four-Russians Idea.- Sparse Estimation for Structural Variability.- Data Structures for Accelerating Tanimoto Queries on Real Valued Vectors.- Sparsification of RNA Structure Prediction Including Pseudoknots.- Prediction of RNA Secondary Structure Including Kissing Hairpin Motifs.- Reducing the Worst Case Running Times of a Family of RNA and CFG Problems, Using Valiant’s Approach.- Comparative Genomics.- Reconstruction of Ancestral Genome Subject to Whole Genome Duplication, Speciation, Rearrangement and Loss.- Genomic Distance with DCJ and Indels.- Listing All Sorting Reversals in Quadratic Time.- Haplotype and Genotype Analysis.- Discovering Kinship through Small Subsets.- Fixed-Parameter Algorithm for Haplotype Inferences on General Pedigrees with Small Number of Sites.- Haplotypes versus Genotypes on Pedigrees.- Haplotype Inference on Pedigrees with Recombinations and Mutations.- High-throughput Data Analysis: Next Generation Sequencing and Flow Cytometry.- Identifying Rare Cell Populations in Comparative Flow Cytometry.- Fast Mapping and Precise Alignment of AB SOLiD Color Reads to Reference DNA.- Design of an Efficient Out-of-Core Read Alignment Algorithm.- Estimation of Alternative Splicing isoform Frequencies from RNA-Seq Data.- Networks.- Improved Orientations of Physical Networks.- Enumerating Chemical Organisations in Consistent Metabolic Networks: Complexity and Algorithms.- Efficient Subgraph Frequency Estimation with G-Tries.- Phylogenetics.- Accuracy Guarantees for Phylogeny Reconstruction Algorithms Based on Balanced Minimum Evolution.- The Complexity of Inferring a Minimally Resolved Phylogenetic Supertree.-Reducing Multi-state to Binary Perfect Phylogeny with Applications to Missing, Removable, Inserted, and Deleted Data.- An Experimental Study of Quartets MaxCut and Other Supertree Methods.- An Efficient Method for DNA-Based Species Assignment via Gene Tree and Species Tree Reconciliation.- Sequences, Strings and Motifs.- Effective Algorithms for Fusion Gene Detection.- Swiftly Computing Center Strings.- Speeding Up Exact Motif Discovery by Bounding the Expected Clump Size.- Pair HMM Based Gap Statistics for Re-evaluation of Indels in Alignments with Affine Gap Penalties.- Quantifying the Strength of Natural Selection of a Motif Sequence.