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Bioinformatics for DNA Sequence Analysis

Overview of attention for book
Attention for Chapter 12: Computational gene annotation in new genome assemblies using GeneID.
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20 Mendeley
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Chapter title
Computational gene annotation in new genome assemblies using GeneID.
Chapter number 12
Book title
Bioinformatics for DNA Sequence Analysis
Published in
Methods in molecular biology, February 2009
DOI 10.1007/978-1-59745-251-9_12
Pubmed ID
Book ISBNs
978-1-58829-910-9, 978-1-59745-251-9
Authors

Blanco E, Abril JF, Enrique Blanco, Josep F. Abril, Blanco, Enrique, Abril, Josep F.

Editors

David Posada

Abstract

The sequence of many eukaryotic genomes is nowadays available from a personal computer to any researcher in the world-wide scientific community. However, the sequences are worthless without the adequate annotation of the biological meaningful elements. The annotation of the genes, in particular, is a challenging task that can not be tackled without the aid of specific bioinformatics tools. We present in this chapter a simple protocol mainly based on the combination of the program GeneID and other computational tools to annotate the location of a gene, which was previously annotated in D. melanogaster, in the recently assembled genome of D. yakuba.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 30%
Researcher 5 25%
Student > Bachelor 2 10%
Professor 2 10%
Student > Master 2 10%
Other 2 10%
Unknown 1 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 65%
Biochemistry, Genetics and Molecular Biology 4 20%
Medicine and Dentistry 1 5%
Unknown 2 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 05 December 2015.
All research outputs
#7,452,489
of 22,783,848 outputs
Outputs from Methods in molecular biology
#2,316
of 13,094 outputs
Outputs of similar age
#32,779
of 93,211 outputs
Outputs of similar age from Methods in molecular biology
#8
of 37 outputs
Altmetric has tracked 22,783,848 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,094 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 76% of its peers.
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 93,211 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.