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Algorithms for Computational Biology

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Cover of 'Algorithms for Computational Biology'

Table of Contents

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    Book Overview
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    Chapter 1 Comparative Genomics Approaches to Identifying Functionally Related Genes
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    Chapter 2 A Greedy Algorithm for Hierarchical Complete Linkage Clustering
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    Chapter 3 Vester’s Sensitivity Model for Genetic Networks with Time-Discrete Dynamics
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    Chapter 4 Complexity and Polynomial-Time Approximation Algorithms around the Scaffolding Problem
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    Chapter 5 Heuristics for the Sorting by Length-Weighted Inversions Problem on Signed Permutations
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    Chapter 6 On Low Treewidth Graphs and Supertrees
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    Chapter 7 Algorithms for Computational Biology
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    Chapter 8 On the Implementation of Quantitative Model Refinement
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    Chapter 9 HapMonster: A Statistically Unified Approach for Variant Calling and Haplotyping Based on Phase-Informative Reads
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    Chapter 10 Mapping-Free and Assembly-Free Discovery of Inversion Breakpoints from Raw NGS Reads
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    Chapter 11 Algorithms for Computational Biology
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    Chapter 12 On Sorting of Signed Permutations by Prefix and Suffix Reversals and Transpositions
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    Chapter 13 On the Diameter of Rearrangement Problems
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    Chapter 14 Efficiently Enumerating All Connected Induced Subgraphs of a Large Molecular Network
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    Chapter 15 On Algorithmic Complexity of Biomolecular Sequence Assembly Problem
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    Chapter 16 A Closed-Form Solution for Transcription Factor Activity Estimation Using Network Component Analysis
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    Chapter 17 SVEM: A Structural Variant Estimation Method Using Multi-mapped Reads on Breakpoints
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    Chapter 18 Analysis and Classification of Constrained DNA Elements with N-gram Graphs and Genomic Signatures
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    Chapter 19 Inference of Boolean Networks from Gene Interaction Graphs Using a SAT Solver
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    Chapter 20 RRCA: Ultra-Fast Multiple In-species Genome Alignments
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    Chapter 21 Exact Protein Structure Classification Using the Maximum Contact Map Overlap Metric
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Title
Algorithms for Computational Biology
Published by
Springer International Publishing, June 2014
DOI 10.1007/978-3-319-07953-0
ISBNs
978-3-31-907952-3, 978-3-31-907953-0
Editors

Dediu, Adrian-Horia, Martín-Vide, Carlos, Truthe, Bianca

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Netherlands 1 1%
China 1 1%
Unknown 65 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 23%
Researcher 12 17%
Student > Master 10 14%
Student > Postgraduate 5 7%
Student > Bachelor 4 6%
Other 13 19%
Unknown 9 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 25%
Computer Science 15 22%
Engineering 8 12%
Biochemistry, Genetics and Molecular Biology 6 9%
Mathematics 4 6%
Other 6 9%
Unknown 13 19%