Nina Jeliazkova - Web tools for predictive toxicology model building

Document created by Nina Jeliazkova on Aug 22, 2014
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  Publication Details (including relevant citation   information):

    Jeliazkova, N.,   Web tools for predictive toxicology model   building,    Expert Opinion on Drug Metabolism &   Toxicology,2012,   8(5);1-11   doi: 10.1517/17425255.2012.685158

  Abstract:

  Introduction: The development and use   of web tools in chemistry has accumulated more than 15 years of   history already. Powered by the advances in the Internet   technologies, the current generation of web systems are starting   to expand into areas, traditional for desktop applications. The   web platforms integrate data storage, cheminformatics and data   analysis tools. The ease of use and the collaborative potential   of the web is compelling, despite the challenges.

  Areas covered: The topic of this review   is a set of recently published web tools that facilitate   predictive toxicology model building. The focus is on software   platforms, offering web access to chemical structure-based   methods, although some of the frameworks could also provide   bioinformatics or hybrid data analysis functionalities. A number   of historical and current developments are cited. In order to   provide comparable assessment, the following characteristics are   considered: support for workflows, descriptor calculations,   visualization, modeling algorithms, data management and data   sharing capabilities, availability of GUI or programmatic access   and implementation details.

  Expert opinion: The success of the Web   is largely due to its highly decentralized, yet sufficiently   interoperable model for information access. The expected future   convergence between cheminformatics and bioinformatics databases   provides new challenges toward management and analysis of large   data sets. The web tools in predictive toxicology will likely   continue to evolve toward the right mix of flexibility,   performance, scalability, interoperability, sets of unique   features offered, friendly user interfaces, programmatic access   for advanced users, platform independence, results   reproducibility, curation and crowdsourcing utilities,   collaborative sharing and secure access.

 

  Address (URL): http://dx.doi.org/10.1517/17425255.2012.685158

 

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