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The Blue Obelisk Movement (http://www.blueobelisk.org/) is the name used by a diverse Internet group promoting reusable chemistry via open source software development, consistent and complimentary chemoinformatics research, open data, and open standards. We outline recent examples of cooperation in the Blue Obelisk group: a shared dictionary of algorithms(More)
Web 2.0-style services and capabilities collectively define a comprehensive distributed computing environment that may be considered an alternative or supplement to existing Grid computing approaches for e-Science. Web 2.0 is briefly summarized as building upon network-enabled, stateless services with simple message formats and message exchange patterns to(More)
This work presents the development of Quantitative Structure-Activity Relationship (QSAR) models to predict the biological activity of 179 artemisinin analogues. The structures of the molecules are represented by chemical descriptors that encode topological, geometric, and electronic structure features. Both linear (multiple linear regression) and nonlinear(More)
Polypharmacology provides a new way to address the issue of high attrition rates arising from lack of efficacy and toxicity. However, the development of polypharmacology is hampered by the incomplete SAR data and limited resources for validating target combinations. The PubChem bioassay collection, reporting the activity of compounds in multiple assays,(More)
Computational toxicology is emerging as an encouraging alternative to experimental testing. The Molecular Libraries Screening Center Network (MLSCN) as part of the NIH Molecular Libraries Roadmap has recently started generating large and diverse screening datasets, which are publicly available in PubChem. In this report, we investigate various aspects of(More)
A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds, and fingerprints. The approach enables the(More)
Virtual screening (VS) has become a preferred tool to augment high-throughput screening(1) and determine new leads in the drug discovery process. The core of a VS informatics pipeline includes several data mining algorithms that work on huge databases of chemical compounds containing millions of molecular structures and their associated data. Thus, scaling(More)
The vast increase of pertinent information available to drug discovery scientists means that there is a strong demand for tools and techniques for organizing and intelligently mining this information for manageable human consumption. At Indiana University, we have developed an infrastructure of chemoinformatics Web services that simplifies the access to(More)
A new method for analyzing a structure-activity relationship is proposed. By use of a simple quantitative index, one can readily identify "structure-activity cliffs": pairs of molecules which are most similar but have the largest change in activity. We show how this provides a graphical representation of the entire SAR, in a way that allows the salient(More)
The development of predictive statistical models is a common task in the field of drug design. The process of developing such models involves two main steps: building the model and then deploying the model. Traditionally such models have been deployed using Web page interfaces. This approach restricts the user to using the specified Web page, and using the(More)