| Title |
SVM approach for predicting LogP
|
|---|---|
| Published in |
Molecular Diversity, September 2006
|
| DOI | 10.1007/s11030-006-9036-2 |
| Pubmed ID | |
| Authors |
Quan Liao, Jianhua Yao, Shengang Yuan |
| Abstract |
The logarithm of the partition coefficient between n-octanol and water (logP) is an important parameter for drug discovery. Based upon the comparison of several prediction logP models, i.e. Support Vector Machines (SVM), Partial Least Squares (PLS) and Multiple Linear Regression (MLR), the authors reported SVM model is the best one in this paper. |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Russia | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 28 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 8 | 26% |
| Researcher | 7 | 23% |
| Student > Ph. D. Student | 5 | 16% |
| Student > Master | 2 | 6% |
| Other | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 4 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 6 | 19% |
| Agricultural and Biological Sciences | 6 | 19% |
| Chemistry | 5 | 16% |
| Computer Science | 2 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 7 | 23% |
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 November 2009.
All research outputs
#7,453,126
of 22,785,242 outputs
Outputs from Molecular Diversity
#129
of 463 outputs
Outputs of similar age
#23,516
of 67,480 outputs
Outputs of similar age from Molecular Diversity
#5
of 9 outputs
Altmetric has tracked 22,785,242 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 463 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.