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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GAM-NGS: genomic assemblies merger for next generation sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-s7-s6 |
| Pubmed ID | |
| Authors |
Riccardo Vicedomini, Francesco Vezzi, Simone Scalabrin, Lars Arvestad, Alberto Policriti |
| Abstract |
In recent years more than 20 assemblers have been proposed to tackle the hard task of assembling NGS data. A common heuristic when assembling a genome is to use several assemblers and then select the best assembly according to some criteria. However, recent results clearly show that some assemblers lead to better statistics than others on specific regions but are outperformed on other regions or on different evaluation measures. To limit these problems we developed GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weighted graph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions. |
X Demographics
The data shown below were collected from the profiles of 26 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 27% |
| Spain | 2 | 8% |
| United Kingdom | 2 | 8% |
| France | 2 | 8% |
| Sweden | 2 | 8% |
| Canada | 1 | 4% |
| Australia | 1 | 4% |
| Italy | 1 | 4% |
| Norway | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 6 | 23% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 54% |
| Members of the public | 11 | 42% |
| Practitioners (doctors, other healthcare professionals) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 220 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 3% |
| Brazil | 4 | 2% |
| Germany | 3 | 1% |
| Norway | 3 | 1% |
| France | 2 | <1% |
| Australia | 2 | <1% |
| Sweden | 2 | <1% |
| Japan | 2 | <1% |
| United Kingdom | 2 | <1% |
| Other | 10 | 5% |
| Unknown | 184 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 62 | 28% |
| Student > Ph. D. Student | 52 | 24% |
| Student > Master | 24 | 11% |
| Professor > Associate Professor | 15 | 7% |
| Student > Bachelor | 13 | 6% |
| Other | 41 | 19% |
| Unknown | 13 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 118 | 54% |
| Biochemistry, Genetics and Molecular Biology | 34 | 15% |
| Computer Science | 24 | 11% |
| Immunology and Microbiology | 5 | 2% |
| Medicine and Dentistry | 5 | 2% |
| Other | 13 | 6% |
| Unknown | 21 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 10 August 2017.
All research outputs
#1,720,304
of 22,711,242 outputs
Outputs from BMC Bioinformatics
#392
of 7,259 outputs
Outputs of similar age
#14,950
of 196,449 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 120 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,259 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 94% 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 196,449 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.