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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 Reconciliation Revisited: Handling Multiple Optima When Reconciling with Duplication, Transfer, and Loss
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    Chapter 2 SEME: A Fast Mapper of Illumina Sequencing Reads with Statistical Evaluation
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    Chapter 3 Dissecting Cancer Heterogeneity with a Probabilistic Genotype-Phenotype Model
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    Chapter 4 eALPS: Estimating Abundance Levels in Pooled Sequencing Using Available Genotyping Data
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    Chapter 5 Analysis of Metabolic Evolution in Bacteria Using Whole-Genome Metabolic Models
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    Chapter 6 Detecting Protein Conformational Changes in Interactions via Scaling Known Structures
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    Chapter 7 IPED: Inheritance Path Based Pedigree Reconstruction Algorithm Using Genotype Data
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    Chapter 8 An Optimal Algorithm for Building the Majority Rule Consensus Tree
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    Chapter 9 UniNovo : A Universal Tool for de Novo Peptide Sequencing
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    Chapter 10 Efficiently Identifying Significant Associations in Genome-Wide Association Studies
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    Chapter 11 Identification of Ultramodified Proteins Using Top-Down Spectra
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    Chapter 12 Research in Computational Molecular Biology
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    Chapter 13 Assembling Genomes and Mini-metagenomes from Highly Chimeric Reads
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    Chapter 14 Inferring Intra-tumor Heterogeneity from High-Throughput DNA Sequencing Data
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    Chapter 15 NP-MuScL: Unsupervised Global Prediction of Interaction Networks from Multiple Data Sources
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    Chapter 16 High Resolution Modeling of Chromatin Interactions
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    Chapter 17 A Linear Inside-Outside Algorithm for Correcting Sequencing Errors in Structured RNAs
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    Chapter 18 An Accurate Method for Inferring Relatedness in Large Datasets of Unphased Genotypes via an Embedded Likelihood-Ratio Test
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    Chapter 19 Learning Natural Selection from the Site Frequency Spectrum
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    Chapter 20 Considering Unknown Unknowns - Reconstruction of Non-confoundable Causal Relations in Biological Networks
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    Chapter 21 Inference of Tumor Phylogenies with Improved Somatic Mutation Discovery
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    Chapter 22 Abstract: Using the Fast Fourier Transform to Accelerate the Computational Search for RNA Conformational Switches
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    Chapter 23 MethylCRF, an Algorithm for Estimating Absolute Methylation Levels at Single CpG Resolution from Methylation Enrichment and Restriction Enzyme Sequencing Methods
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    Chapter 24 Counting Motifs in the Entire Biological Network from Noisy and Incomplete Data
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    Chapter 25 Research in Computational Molecular Biology
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    Chapter 26 Genome-Wide Survival Analysis of Somatic Mutations in Cancer
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    Chapter 27 Spectral Library Generating Function for Assessing Spectrum-Spectrum Match Significance
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    Chapter 28 SPARSE: Quadratic Time Simultaneous Alignment and Folding of RNAs without Sequence-Based Heuristics
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    Chapter 29 An Algorithm for Constructing Parsimonious Hybridization Networks with Multiple Phylogenetic Trees
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    Chapter 30 Fast and Accurate Calculation of Protein Depth by Euclidean Distance Transform
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    Chapter 31 Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data
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    Chapter 32 Boosting Prediction Performance of Protein-Protein Interaction Hot Spots by Using Structural Neighborhood Properties
Attention for Chapter 13: Assembling Genomes and Mini-metagenomes from Highly Chimeric Reads
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Citations

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538 Mendeley
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Chapter title
Assembling Genomes and Mini-metagenomes from Highly Chimeric Reads
Chapter number 13
Book title
Research in Computational Molecular Biology
Published in
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-37195-0_13
Book ISBNs
978-3-64-237194-3, 978-3-64-237195-0
Authors

Sergey Nurk, Anton Bankevich, Dmitry Antipov, Alexey Gurevich, Anton Korobeynikov, Alla Lapidus, Andrey Prjibelsky, Alexey Pyshkin, Alexander Sirotkin, Yakov Sirotkin, Ramunas Stepanauskas, Jeffrey McLean, Roger Lasken, Scott R. Clingenpeel, Tanja Woyke, Glenn Tesler, Max A. Alekseyev, Pavel A. Pevzner, Nurk, Sergey, Bankevich, Anton, Antipov, Dmitry, Gurevich, Alexey, Korobeynikov, Anton, Lapidus, Alla, Prjibelsky, Andrey, Pyshkin, Alexey, Sirotkin, Alexander, Sirotkin, Yakov, Stepanauskas, Ramunas, McLean, Jeffrey, Lasken, Roger, Clingenpeel, Scott R., Woyke, Tanja, Tesler, Glenn, Alekseyev, Max A., Pevzner, Pavel A.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 538 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Spain 3 <1%
Germany 2 <1%
South Africa 2 <1%
United Kingdom 1 <1%
Netherlands 1 <1%
Brazil 1 <1%
New Zealand 1 <1%
Unknown 523 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 126 23%
Researcher 89 17%
Student > Master 74 14%
Student > Bachelor 71 13%
Other 21 4%
Other 57 11%
Unknown 100 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 155 29%
Biochemistry, Genetics and Molecular Biology 134 25%
Immunology and Microbiology 35 7%
Environmental Science 25 5%
Veterinary Science and Veterinary Medicine 14 3%
Other 59 11%
Unknown 116 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 February 2021.
All research outputs
#15,810,483
of 26,017,215 outputs
Outputs from Lecture notes in computer science
#4,195
of 8,229 outputs
Outputs of similar age
#177,900
of 295,070 outputs
Outputs of similar age from Lecture notes in computer science
#154
of 317 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,229 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 47th percentile – i.e., 47% 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 295,070 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.