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Research in Computational Molecular Biology

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Cover of 'Research in Computational Molecular Biology'

Table of Contents

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    Book Overview
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    Chapter 1 The Second Decade of the International Conference on Research in Computational Molecular Biology (RECOMB)
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    Chapter 2 A MAD-Bayes Algorithm for State-Space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets
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    Chapter 3 Accurate Recovery of Ribosome Positions Reveals Slow Translation of Wobble-Pairing Codons in Yeast
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    Chapter 4 Multitask Matrix Completion for Learning Protein Interactions Across Diseases
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    Chapter 5 pathTiMEx: Joint Inference of Mutually Exclusive Cancer Pathways and Their Dependencies in Tumor Progression
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    Chapter 6 Clonality Inference from Single Tumor Samples Using Low Coverage Sequence Data
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    Chapter 7 Flexible Modelling of Genetic Effects on Function-Valued Traits
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    Chapter 8 MetaFlow: Metagenomic Profiling Based on Whole-Genome Coverage Analysis with Min-Cost Flows
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    Chapter 9 LUTE (Local Unpruned Tuple Expansion): Accurate Continuously Flexible Protein Design with General Energy Functions and Rigid-rotamer-like Efficiency
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    Chapter 10 Improving Bloom Filter Performance on Sequence Data Using \(k\) -mer Bloom Filters
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    Chapter 11 Safe and Complete Contig Assembly Via Omnitigs
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    Chapter 12 Long Single-Molecule Reads Can Resolve the Complexity of the Influenza Virus Composed of Rare, Closely Related Mutant Variants
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    Chapter 13 Structural Variation Detection with Read Pair Information—An Improved Null-Hypothesis Reduces Bias
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    Chapter 14 On Computing Breakpoint Distances for Genomes with Duplicate Genes
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    Chapter 15 New Genome Similarity Measures Based on Conserved Gene Adjacencies
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    Chapter 16 Fast Phylogenetic Biodiversity Computations Under a Non-uniform Random Distribution
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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