Similarity methods in chemoinformatics
نویسندگان
چکیده
منابع مشابه
Kernel Methods in Chemoinformatics
Millions of people are suffering from fatal diseases such as cancer, AIDS, and many other bacterial and viral illnesses. The key issue is now how to design lifesaving and cost-effective drugs so that the diseases can be cured and prevented. It would also enable the provision of medicines in developing countries, where approximately 80% of the world population lives. Drug design is a discipline ...
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Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure-activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some...
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It would be unimaginable to prosecute a drug discovery program without applying appropriate chemoinformatics analyses. In recent years a focus on target affinity and activity has been complemented by techniques to address physico-chemical properties such as lipophilicity and solubility, biological properties such as absorption, distribution, metabolism, elimination and toxicity. As such, a roun...
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The increase in the database size of chemical compound requires a longer time in processing for any searching algorithms [1]. With the focus on an algorithm called Turbo Similarity Searching which have been proven to have good accuracy in retrieving actives [2], we propose that this algorithm be implemented on the widely-used many-cores and multi-cores processors which are easily available at l...
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ژورنال
عنوان ژورنال: Annual Review of Information Science and Technology
سال: 2009
ISSN: 0066-4200
DOI: 10.1002/aris.2009.1440430108