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• W2259538443 abstract "Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data." @default.
• W2259538443 created "2016-06-24" @default.
• W2259538443 creator A5034837231 @default.
• W2259538443 creator A5037657152 @default.
• W2259538443 creator A5046305086 @default.
• W2259538443 creator A5054311881 @default.
• W2259538443 creator A5065659822 @default.
• W2259538443 creator A5068092661 @default.
• W2259538443 creator A5073568638 @default.
• W2259538443 date "2015-08-17" @default.
• W2259538443 modified "2023-10-12" @default.
• W2259538443 title "Drug–target interaction prediction: databases, web servers and computational models" @default.
• W2259538443 cites W1466286227 @default.
• W2259538443 cites W1540649941 @default.
• W2259538443 cites W1541232310 @default.
• W2259538443 cites W1895993106 @default.
• W2259538443 cites W1966751442 @default.
• W2259538443 cites W1967032556 @default.
• W2259538443 cites W1968682237 @default.
• W2259538443 cites W1971106435 @default.
• W2259538443 cites W1971387816 @default.
• W2259538443 cites W1971825415 @default.
• W2259538443 cites W1974884542 @default.
• W2259538443 cites W1975426150 @default.
• W2259538443 cites W1978370150 @default.
• W2259538443 cites W1979537657 @default.
• W2259538443 cites W1984084871 @default.
• W2259538443 cites W1995089537 @default.
• W2259538443 cites W1995905328 @default.
• W2259538443 cites W2002221644 @default.
• W2259538443 cites W2004364785 @default.
• W2259538443 cites W2008840001 @default.
• W2259538443 cites W2010750139 @default.
• W2259538443 cites W2015393683 @default.
• W2259538443 cites W2015604457 @default.
• W2259538443 cites W2018408116 @default.
• W2259538443 cites W2018518196 @default.
• W2259538443 cites W2027482274 @default.
• W2259538443 cites W2029152175 @default.
• W2259538443 cites W2029197596 @default.
• W2259538443 cites W2033591223 @default.
• W2259538443 cites W2035753075 @default.
• W2259538443 cites W2044002635 @default.
• W2259538443 cites W2044424923 @default.
• W2259538443 cites W2048565304 @default.
• W2259538443 cites W2057635677 @default.
• W2259538443 cites W2060145168 @default.
• W2259538443 cites W2062941476 @default.
• W2259538443 cites W2064264167 @default.
• W2259538443 cites W2066201825 @default.
• W2259538443 cites W2068351024 @default.
• W2259538443 cites W2069898171 @default.
• W2259538443 cites W2070171305 @default.
• W2259538443 cites W2074370114 @default.
• W2259538443 cites W2080770317 @default.
• W2259538443 cites W2085034490 @default.
• W2259538443 cites W2086286404 @default.
• W2259538443 cites W2087064593 @default.
• W2259538443 cites W2096021562 @default.
• W2259538443 cites W2096541451 @default.
• W2259538443 cites W2096864392 @default.
• W2259538443 cites W2099754222 @default.
• W2259538443 cites W2100811683 @default.
• W2259538443 cites W2105668062 @default.
• W2259538443 cites W2108069034 @default.
• W2259538443 cites W2109991441 @default.
• W2259538443 cites W2112189758 @default.
• W2259538443 cites W2113951828 @default.
• W2259538443 cites W2126671570 @default.
• W2259538443 cites W2128137143 @default.
• W2259538443 cites W2128966273 @default.
• W2259538443 cites W2131773109 @default.
• W2259538443 cites W2138427043 @default.
• W2259538443 cites W2138512826 @default.
• W2259538443 cites W2139516171 @default.
• W2259538443 cites W2139736926 @default.
• W2259538443 cites W2140595402 @default.
• W2259538443 cites W2142572836 @default.
• W2259538443 cites W2144563439 @default.
• W2259538443 cites W2152970345 @default.
• W2259538443 cites W2153838454 @default.
• W2259538443 cites W2154896031 @default.
• W2259538443 cites W2156012049 @default.
• W2259538443 cites W2160203886 @default.
• W2259538443 cites W2161607603 @default.
• W2259538443 cites W2165188181 @default.
• W2259538443 cites W2165240999 @default.
• W2259538443 cites W2165674132 @default.
• W2259538443 cites W2166550586 @default.
• W2259538443 cites W2167212630 @default.
• W2259538443 cites W2168938595 @default.
• W2259538443 cites W2169815691 @default.
• W2259538443 cites W2171482501 @default.
• W2259538443 cites W3101634756 @default.
• W2259538443 cites W4232866872 @default.
• W2259538443 cites W4244606935 @default.
• W2259538443 cites W4245543257 @default.
• W2259538443 doi "https://doi.org/10.1093/bib/bbv066" @default.

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