6533b824fe1ef96bd1280981
RESEARCH PRODUCT
ChemInform Abstract: Antimicrobial Activity Characterization in a Heterogeneous Group of Compounds.
Ramón García-domenechJ.v. De Julián-ortizsubject
Heterogeneous groupArtificial neural networkbusiness.industryChemistryTest setPattern recognition (psychology)Pattern recognitionGeneral MedicineArtificial intelligenceLinear analysisLinear discriminant analysisbusinessAntimicrobialdescription
In this work we carry out a study of pattern recognition to detect the microbiological activity in a group of heterogeneous compounds. The structural descriptors utilized are the topological connectivity indexes. The methods followed are stepwise linear discriminant analysis (linear analysis) and artificial neural network (nonlinear analysis). Although both methods are appropriate to differentiate between active and inactive compounds, the artificial neural network is, in this case, more adequate, since it shows in a test set a prediction success of 98%, versus 92% obtained with linear discriminant analysis.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-06-20 | ChemInform |