Analysis and Study of Molecule Data Sets Using Snowflake Diagrams of Weighted Maximum Common Subgraph Trees

García, Gonzalo Cerruela; Ruiz, Irene Luque; Gómez‐Nieto, Miguel Ángel

doi:10.1021/ci100484z

Cited by 10 publications

(4 citation statements)

References 46 publications

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“…Some methods produce hierarchical structures representing the buildup of many larger structures from a single fragment by sequential additions. ,,, This is exemplified by the fragment hierarchy method shown in Figure . Other methods produce diagrams representing the ways that a compound can be disassembled into smaller fragments. ,, The scaffold network procedure shown in Figure is an example.…”

Section: Resultsmentioning

confidence: 99%

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Construction and Use of Fragment-Augmented Molecular Hasse Diagrams

Lind

2014

J. Chem. Inf. Model.

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Collections of molecules can be organized in many different ways based on substructures that are common to two or more of the molecules. The article describes a method that builds on the ideas of partial orders and Hasse diagrams and which organizes molecules in a particularly simple and natural way using only sub- and superstructure relations. The method outputs the original molecule collection together with common substructures and a set of relations between fragments and molecules. The result is a complete deconstruction of the original structures into those fragments or building blocks that are shared between two or more molecules. Scaffolds for the R-group analyses that can be performed on the data set are automatically detected. Cyclic and linear substituents are treated in the same way. No rules are incorporated that express any form of domain expertise or judgment. The method should be useful for library profiling, data set navigation, fragment-based screening, identification of activity cliffs, and identification of library subsets that are amenable to fragment-based QSAR.

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Section: Resultsmentioning

confidence: 99%

“…Cerruela Garcia proposed a visualization method applicable to data sets where all compounds share a maximum common substructure. The root node of a tree represents the most common MSC in the data set, and this is put in the center of the picture.…”

Section: Previous Workmentioning

confidence: 99%

Construction and Use of Fragment-Augmented Molecular Hasse Diagrams

Lind

2014

J. Chem. Inf. Model.

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“…Cerruela et al also proposed a similar structure; however, in their proposal the root node contains the MCS of the whole data set. In this case, although the size of this fragment can be quite small (number of nodes and arcs) the root node is never null.…”

Section: Methodsmentioning

confidence: 99%

“…Cerruela et al used weighted maximum subgraph tree (WMCST) for the representation of data sets. This representation is based on a hierarchic structure in which the root node stores the fragment containing the MCS of the data set molecules, the leaf nodes store the molecules and the remaining nodes of the hierarchic structures store the maximum common substructures to the child nodes.…”

Section: Introductionmentioning

confidence: 99%

Advantages of Relative versus Absolute Data for the Development of Quantitative Structure–Activity Relationship Classification Models

Ruiz

Gómez‐Nieto

2017

J. Chem. Inf. Model.

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The appropriate selection of a chemical space represented by the data set, the selection of its chemical data representation, the development of a correct modeling process using a robust and reproducible algorithm, and the performance of an exhaustive training and external validation determine the usability and reproducibility of a quantitative structure-activity relationship (QSAR) classification model. In this paper, we show that the use of relative versus absolute data in the representation of the data sets produces better classification models when the other processes are not modified. Relative data considers a reference frame to measure the chemical characteristics involved in the classification model, refining the data set representation and smoothing the lack of chemical information. Three data sets with different characteristics have been used in this study, and classifications models have been built applying the support vector machine algorithm. For randomly selected training and test sets, values of accuracy and area under the receiver operating characteristic curve close to 100% have been obtained for the generation of the models and external validations in all cases.

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QSAR studies on pyrrolidine amides derivatives as DPP-IV inhibitors for type 2 diabetes

Yang

et al. 2013

Med Chem Res

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Analysis and Study of Molecule Data Sets Using Snowflake Diagrams of Weighted Maximum Common Subgraph Trees

Cited by 10 publications

References 46 publications

Construction and Use of Fragment-Augmented Molecular Hasse Diagrams

Construction and Use of Fragment-Augmented Molecular Hasse Diagrams

Advantages of Relative versus Absolute Data for the Development of Quantitative Structure–Activity Relationship Classification Models

QSAR studies on pyrrolidine amides derivatives as DPP-IV inhibitors for type 2 diabetes

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