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Research in Computational Molecular Biology

Overview of attention for book
Cover of 'Research in Computational Molecular Biology'

Table of Contents

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    Book Overview
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    Chapter 1 Protein Structure by Semidefinite Facial Reduction
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    Chapter 2 Ancestry Inference in Complex Admixtures via Variable-Length Markov Chain Linkage Models
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    Chapter 3 Charge Group Partitioning in Biomolecular Simulation
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    Chapter 4 Increased Methylation Variation in Epigenetic Domains across Cancer Types
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    Chapter 5 Estimating the Accuracy of Multiple Alignments and its Use in Parameter Advising
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    Chapter 6 Quantifying the Dynamics of Coupled Networks of Switches and Oscillators
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    Chapter 7 lobSTR: A Short Tandem Repeat Profiler for Personal Genomes
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    Chapter 8 Hap-seq: An Optimal Algorithm for Haplotype Phasing with Imputation Using Sequencing Data
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    Chapter 9 Ballast : A Ball-Based Algorithm for Structural Motifs
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    Chapter 10 Evolution of Genome Organization by Duplication and Loss: An Alignment Approach
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    Chapter 11 LoopWeaver – Loop Modeling by the Weighted Scaling of Verified Proteins
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    Chapter 12 A Robust Method for Transcript Quantification with RNA-seq Data
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    Chapter 13 Modeling the Breakage-Fusion-Bridge Mechanism: Combinatorics and Cancer Genomics
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    Chapter 14 TrueSight: Self-training Algorithm for Splice Junction Detection Using RNA-seq
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    Chapter 15 Synthetic Sequence Design for Signal Location Search
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    Chapter 16 The Three-Dimensional Architecture of a Bacterial Genome and Its Alteration by Genetic Perturbation
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    Chapter 17 Discovery of Complex Genomic Rearrangements in Cancer Using High-Throughput Sequencing
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    Chapter 18 Network-Based Prediction and Analysis of HIV Dependency Factors
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    Chapter 19 Structure-Guided Deimmunization of Therapeutic Proteins
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    Chapter 20 Evidence for Widespread Association of Mammalian Splicing and Conserved Long-Range RNA Structures
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    Chapter 21 Pathset Graphs: A Novel Approach for Comprehensive Utilization of Paired Reads in Genome Assembly
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    Chapter 22 Finding Maximum Colorful Subtrees in Practice
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    Chapter 23 Recovering the Tree-Like Trend of Evolution Despite Extensive Lateral Genetic Transfer: A Probabilistic Analysis
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    Chapter 24 RESQUE: Network Reduction Using Semi-Markov Random Walk Scores for Efficient Querying of Biological Networks (Extended Abstract)
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    Chapter 25 Detecting SNP-Induced Structural Changes in RNA: Application to Disease Studies
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    Chapter 26 A Model for Biased Fractionation after Whole Genome Duplication
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    Chapter 27 Exact Pattern Matching for RNA Structure Ensembles
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    Chapter 28 Reconstructing Boolean Models of Signaling
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    Chapter 29 Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads: Extended Abstract
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    Chapter 30 Differential Oestrogen Receptor Binding is Associated with Clinical Outcome in Breast Cancer
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    Chapter 31 Simultaneous Reconstruction of Multiple Signaling Pathways via the Prize-Collecting Steiner Forest Problem
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    Chapter 32 Function-Function Correlated Multi-Label Protein Function Prediction over Interaction Networks
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    Chapter 33 Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Tri-Factorization
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    Chapter 34 CNVeM: Copy Number Variation Detection Using Uncertainty of Read Mapping
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    Chapter 35 Structure-Based Whole Genome Realignment Reveals Many Novel Non-coding RNAs
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    Chapter 36 Probabilistic Inference of Viral Quasispecies Subject to Recombination
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    Chapter 37 Simultaneously Learning DNA Motif along with Its Position and Sequence Rank Preferences through EM Algorithm
Attention for Chapter 3: Charge Group Partitioning in Biomolecular Simulation
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Chapter title
Charge Group Partitioning in Biomolecular Simulation
Chapter number 3
Book title
Research in Computational Molecular Biology
Published in
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-29627-7_3
Book ISBNs
978-3-64-229626-0, 978-3-64-229627-7
Authors

Stefan Canzar, Mohammed El-Kebir, René Pool, Khaled Elbassioni, Alpesh K. Malde, Alan E. Mark, Daan P. Geerke, Leen Stougie, Gunnar W. Klau

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 7%
Netherlands 1 4%
Unknown 24 89%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 26%
Researcher 4 15%
Student > Master 3 11%
Student > Ph. D. Student 2 7%
Student > Doctoral Student 2 7%
Other 3 11%
Unknown 6 22%
Readers by discipline Count As %
Chemistry 6 22%
Biochemistry, Genetics and Molecular Biology 5 19%
Computer Science 3 11%
Agricultural and Biological Sciences 2 7%
Chemical Engineering 2 7%
Other 2 7%
Unknown 7 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 April 2012.
All research outputs
#17,131,871
of 21,217,760 outputs
Outputs from Lecture notes in computer science
#5,940
of 8,038 outputs
Outputs of similar age
#108,773
of 142,217 outputs
Outputs of similar age from Lecture notes in computer science
#17
of 23 outputs
Altmetric has tracked 21,217,760 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,038 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 142,217 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.