Recent Advances in Multi-Task QSAR Modeling for Drug Design
نویسندگان
چکیده
منابع مشابه
Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges
Medicinal chemistry projects involve some steps aiming to develop a new drug, such as the analysis of biological targets related to a given disease, the discovery and the development of drug candidates for these targets, performing parallel biological tests to validate the drug effectiveness and side effects. Approaches as quantitative study of activity-structure relationships (QSAR) involve th...
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Modern drug discovery is characterized by the production of vast quantities of compounds and the need to examine these huge libraries in short periods of time. The need to store, manage and analyze these rapidly increasing resources has given rise to the field known as computer-aided drug design (CADD). CADD represents computational methods and resources that are used to facilitate the design a...
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Physics-based modeling of sound sources, such as of musical instruments and speech production, is based on several different modeling paradigms or methodologies. These can be roughly categorized as finite difference schemes, mass-spring models, modal decomposition methods, digital waveguide models, wave digital filter models, and source-filter models. The three first methods are based on the us...
متن کاملRecent Advances in Fragment-Based QSAR and Multi-Dimensional QSAR Methods
This paper provides an overview of recently developed two dimensional (2D) fragment-based QSAR methods as well as other multi-dimensional approaches. In particular, we present recent fragment-based QSAR methods such as fragment-similarity-based QSAR (FS-QSAR), fragment-based QSAR (FB-QSAR), Hologram QSAR (HQSAR), and top priority fragment QSAR in addition to 3D- and nD-QSAR methods such as comp...
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Although artificial neural networks have occasionally been used for Quantitative Structure-Activity/Property Relationship (QSAR/QSPR)studies in the past, the literature has of late been dominated by other machine learning techniques such as random forests. However, a variety of new neural net techniques along with successful applications in other domains have renewed interest in network approac...
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ژورنال
عنوان ژورنال: Pharmaceutical Sciences
سال: 2015
ISSN: 2383-2886
DOI: 10.15171/ps.2015.33