SOM Prediction statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Sites of metabolism prediction chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

SOM Prediction specifications

Information


Unique identifier OMICS_13835
Name SOM Prediction
Alternative name Sites Of Metabolism Prediction
Interface Web user interface
Restrictions to use None
Input data A Ligant file and a CYP
Computer skills Basic
Stability Stable
Maintained Yes

Publication for Sites Of Metabolism Prediction

SOM Prediction in publications

 (8)
PMCID: 5224990
PMID: 28072829
DOI: 10.1371/journal.pone.0169910

[…] performance of the method is characterized by tp (true positive), fp (false positive), fn (false negative), tn (true negative), and specificity (sp) computed., in this report, we have developed a som prediction method for some fmo enzymes using svm with some quantum mechanics and circular fingerprints attributes. the total number of molecular descriptors used in building the som prediction […]

PMCID: 5085718
PMID: 27735849
DOI: 10.3390/ijms17101686

[…] into consideration. for this method, experimental data is not a prerequisite to create the model, so there are no so-called “false negatives”. nevertheless, there are indeed some huge challenges for som prediction by this method. structure-based methods rely on the availability of 3d structures of metabolic enzymes to certain extent []. however, the 3d structures of many enzymes remain unknown. […]

PMCID: 5312304
PMID: 27463020
DOI: 10.18632/oncotarget.10830

[…] into a category if the prediction score for the specific category was sufficiently high. in this study, we used a cutoff value of 0.80 to establish a diagnosis of rcc, which meant that if the som prediction score of a subject was below 0.80, the diagnosis was uncertain. cut-off values are typically user-defined. we achieved a prediction accuracy of 93.48% for healthy subjects and 76.32% […]

PMCID: 4896257
PMID: 29270804
DOI: 10.1186/s13321-016-0119-5

[…] quantum-chemically derived molecular descriptors encoding the reactivity of individual atoms appear to be an intuitive starting-point for model improvements. here, we address the challenge of som prediction with descriptors based on atomic partial charges. to this end we assessed various partial charge schemes with respect to their dependence on quantum mechanical methods as well […]

PMCID: 4790961
PMID: 26974821
DOI: 10.1371/journal.pone.0151536

[…] of variation (cv) values for clay (18.95%), free iron oxides (15.93%), and ph (1.04%). this demonstrates the importance of a practical subsetting strategy for the continued improvement of som prediction with vis–nir spectroscopy., all relevant data are within the paper and its supporting information file., soil organic matter (som) is a key attribute of soil and environmental quality […]


To access a full list of publications, you will need to upgrade to our premium service.

SOM Prediction institution(s)
Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India; Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India; Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India
SOM Prediction funding source(s)
This work is supported by grants from the Department of Biotechnology, Govt of India.

SOM Prediction reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review SOM Prediction