You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Pathogen Genome Bioinformatics
|
|---|---|
| Chapter number | 10 |
| Book title |
Clinical Bioinformatics
|
| Published in |
Methods in molecular biology, January 2014
|
| DOI | 10.1007/978-1-4939-0847-9_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-0846-2, 978-1-4939-0847-9
|
| Authors |
Vitali Sintchenko, Michael P. V. Roper |
| Abstract |
Recent advances in DNA sequencing technology have made the whole-genome sequencing of pathogens in a clinically relevant turn-around time both technically and economically feasible. The DNA sequencing of pathogens with epidemic potential offers new and exciting opportunities for high-resolution public health surveillance. This chapter outlines major methods and bioinformatics tools for pathogen genome characterization, the identification of infectious disease clusters, as well as for genomics-guided biosurveillance. Existing challenges are also considered. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 7% |
| Belgium | 1 | 7% |
| Unknown | 13 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 27% |
| Researcher | 3 | 20% |
| Student > Master | 2 | 13% |
| Professor | 1 | 7% |
| Other | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 4 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 27% |
| Agricultural and Biological Sciences | 4 | 27% |
| Nursing and Health Professions | 1 | 7% |
| Mathematics | 1 | 7% |
| Immunology and Microbiology | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 3 | 20% |
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 03 July 2014.
All research outputs
#18,374,472
of 22,758,248 outputs
Outputs from Methods in molecular biology
#7,868
of 13,089 outputs
Outputs of similar age
#229,374
of 305,255 outputs
Outputs of similar age from Methods in molecular biology
#294
of 597 outputs
Altmetric has tracked 22,758,248 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 13,089 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% 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 305,255 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 597 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.