Molecular Similarity and Diversity in Chemoinformatics: From Theory to Applications

Maldonado, Ana G.; Petitjean, Michel; Fan, Bo

doi:10.1002/chin.200616274

Cited by 26 publications

(30 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At this point it must be stated that it seemed to be difficult or even impossible to find absolutely neutral criteria for selection -molecular 'diversity' [33,34], an essential point, for example, in quantitative structure activity relationship (QSAR) studies, is a challenging problem. Nevertheless, from a statistical point of view this lack of perfect randomness in these specific cases is negligible.…”

Section: Methodsmentioning

confidence: 99%

Improving the Quality of Published Chemical Names with Nomenclature Software

Eller

2006

Molecules

View full text Add to dashboard Cite

This work deals with the use of organic systematic nomenclature in scientific literature, its quality, and computerized methods for its improvement. Criteria for classification of systematic names in terms of quality/correctness are discussed and applied to a sample set of several hundred names extracted from the literature. The same structures are named with three popular state-of-the-art nomenclature programs -AutoNom 2000, ChemDraw 10.0, and ACD/Name 9.0. When comparing the results, all nomenclature tools show a significantly better performance than 'average chemists'. One program allows the generation not only of IUPAC names but also of CAS-like index names that are compared with the officially registered names. The scope and limitations of nomenclature software are discussed and a comparison of the programs' actual capabilities is given.

show abstract

Section: Methodsmentioning

confidence: 99%

Improving the Quality of Published Chemical Names with Nomenclature Software

Eller

2006

Molecules

View full text Add to dashboard Cite

show abstract

“…Diversity analysis was performed to make sure the structures in the training and test sets are representative of both data set [27,28]. Distance score between two different …”

Section: Diversity Analysismentioning

confidence: 99%

Application of Genetic Programming (GP) in Prediction of Gas Chromatographic Retention Time of some Pesticides

Fatemi¹,

Yali²

2017

Eurasian J Anal Chem

View full text Add to dashboard Cite

In this study, quantitative structure-retention relationship (QSRR) methodology was employed for modeling of gas chromatographic retention time for 74 pesticides. Stepwise multiple linear regression (SW-MLR) was used for the selection of most important descriptors. Multiple linear regression (MLR) and genetic programming (GP) were utilized to develop linear and symbolic regression equation models, respectively. Inspection to statistical parameters of developed MLR and GP models indicates symbolic regression equation via GP can be selected as the best fitted model. For this model, the square correlation coefficients (R 2 ) were 0.943 and 0.911, and the root-mean square errors (RMSE) were 2.56 and 2.77 for the training and test sets, respectively. The built GP model was assessed by leave one out cross-validation (Q 2 cv = 0.79, SPRESS = 2.57) as well as external validation. In addition, the result of sensitivity analysis of GP model suggest structural features and polarity are important factors responsible for gas-chromatographic retention time values of studied pesticides.

show abstract

“…Subset selection methods include dissimilarity-based compound selection which involves calculating pairwise (dis)similarities; clustering which is also based on pairwise similarities; partitioning schemes in which a low dimensional space is defined independent of the compounds themselves which are then mapped onto the space; and optimisation techniques such as simulated annealing and genetic algorithms. Recent comprehensive reviews of diversity analysis are provided by Gorse [9] and Maldonado et al [10] and a review of descriptors is provided by Glen and Adams [11].…”

Section: How Is Diversity Measured?mentioning

confidence: 99%

New directions in library design and analysis

Gillet

2008

Current Opinion in Chemical Biology

View full text Add to dashboard Cite

SummaryThe high costs associated with high throughput screening (HTS) coupled with the limited coverage and bias of current screening collections is such that diversity analysis continues to be an important criterion in lead generation. Whereas early approaches to diversity analysis were based on traditional descriptors such as two dimensional fingerprints a recent emphasis has been on assessing scaffold coverage to ensure that a variety of different chemotypes are represented. Moreover, whether designing diverse or focussed libraries, it is widely recognised that designs should aim to achieve a balance in a number of different properties and multiobjective optimisation provides an effective way of achieving such designs.

show abstract

Molecular Similarity and Diversity in Chemoinformatics: From Theory to Applications

Cited by 26 publications

References 1 publication

Improving the Quality of Published Chemical Names with Nomenclature Software

Improving the Quality of Published Chemical Names with Nomenclature Software

Application of Genetic Programming (GP) in Prediction of Gas Chromatographic Retention Time of some Pesticides

New directions in library design and analysis

Contact Info

Product

Resources

About