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Mendeley readers
Attention Score in Context
| Title |
solveME: fast and reliable solution of nonlinear ME models
|
|---|---|
| Published in |
BMC Bioinformatics, September 2016
|
| DOI | 10.1186/s12859-016-1240-1 |
| Pubmed ID | |
| Authors |
Laurence Yang, Ding Ma, Ali Ebrahim, Colton J. Lloyd, Michael A. Saunders, Bernhard O. Palsson |
| Abstract |
Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challenges: they are much (>30 times) larger than corresponding metabolic reconstructions (M models), are multiscale, and growth maximization is a nonlinear programming (NLP) problem, mainly due to macromolecule dilution constraints. Here, we address these computational challenges. We develop a fast and numerically reliable solution method for growth maximization in ME models using a quad-precision NLP solver (Quad MINOS). Our method was up to 45 % faster than binary search for six significant digits in growth rate. We also develop a fast, quad-precision flux variability analysis that is accelerated (up to 60× speedup) via solver warm-starts. Finally, we employ the tools developed to investigate growth-coupled succinate overproduction, accounting for proteome constraints. Just as genome-scale metabolic reconstructions have become an invaluable tool for computational and systems biologists, we anticipate that these fast and numerically reliable ME solution methods will accelerate the wide-spread adoption of ME models for researchers in these fields. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 68 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 29% |
| Researcher | 12 | 18% |
| Student > Master | 10 | 15% |
| Student > Bachelor | 6 | 9% |
| Professor | 4 | 6% |
| Other | 8 | 12% |
| Unknown | 8 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 15 | 22% |
| Agricultural and Biological Sciences | 12 | 18% |
| Computer Science | 11 | 16% |
| Engineering | 8 | 12% |
| Chemical Engineering | 4 | 6% |
| Other | 8 | 12% |
| Unknown | 10 | 15% |
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 27 September 2016.
All research outputs
#15,384,989
of 22,889,074 outputs
Outputs from BMC Bioinformatics
#5,384
of 7,298 outputs
Outputs of similar age
#202,956
of 321,009 outputs
Outputs of similar age from BMC Bioinformatics
#79
of 124 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 124 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.