ArticleInternational journal of molecular sciences2016
Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method.
Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method.Biomolecules · 2020Article
- Investigation of Volatiles in Cork Samples Using Chromatographic Data and the Superposing Significant Interaction Rules (SSIR) Chemometric Tool.Biomolecules · 2020Article
- DesMol2, an Effective Tool for the Construction of Molecular Libraries and Its Application to QSAR Using Molecular Topology.Molecules (Basel, Switzerland) · 2019Article
- Data Analysis in Chemistry and Bio-Medical Sciences.International journal of molecular sciences · 2016Article
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1 author.
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Abstract
The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties.
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