Matches in SemOpenAlex for { <https://semopenalex.org/work/W4309781919> ?p ?o ?g. }
- W4309781919 endingPage "316" @default.
- W4309781919 startingPage "301" @default.
- W4309781919 abstract "Discovering new medicines is the hallmark of the human endeavor to live a better and longer life. Yet the pace of discovery has slowed down as we need to venture into more wildly unexplored biomedical space to find one that matches today’s high standard. Modern AI-enabled by powerful computing, large biomedical databases, and breakthroughs in deep learning offers a new hope to break this loop as AI is rapidly maturing, ready to make a huge impact in the area. In this paper, we review recent advances in AI methodologies that aim to crack this challenge. We organize the vast and rapidly growing literature on AI for drug discovery into three relatively stable sub-areas: (a) representation learning over molecular sequences and geometric graphs; (b) data-driven reasoning where we predict molecular properties and their binding, optimize existing compounds, generate de novo molecules, and plan the synthesis of target molecules; and (c) knowledge-based reasoning where we discuss the construction and reasoning over biomedical knowledge graphs. We will also identify open challenges and chart possible research directions for the years to come." @default.
- W4309781919 created "2022-11-29" @default.
- W4309781919 creator A5002423798 @default.
- W4309781919 creator A5051630302 @default.
- W4309781919 creator A5085471517 @default.
- W4309781919 date "2022-11-18" @default.
- W4309781919 modified "2023-10-10" @default.
- W4309781919 title "Learning to discover medicines" @default.
- W4309781919 cites W1496604422 @default.
- W4309781919 cites W1501531009 @default.
- W4309781919 cites W1508604947 @default.
- W4309781919 cites W1601495365 @default.
- W4309781919 cites W1975147762 @default.
- W4309781919 cites W1988037271 @default.
- W4309781919 cites W1993046136 @default.
- W4309781919 cites W1999638776 @default.
- W4309781919 cites W2006603906 @default.
- W4309781919 cites W2024213882 @default.
- W4309781919 cites W2025800893 @default.
- W4309781919 cites W2028279608 @default.
- W4309781919 cites W2034549041 @default.
- W4309781919 cites W2038702914 @default.
- W4309781919 cites W2064675550 @default.
- W4309781919 cites W2102461176 @default.
- W4309781919 cites W2151502664 @default.
- W4309781919 cites W2153838454 @default.
- W4309781919 cites W2170146596 @default.
- W4309781919 cites W2170973067 @default.
- W4309781919 cites W2171234651 @default.
- W4309781919 cites W2176516200 @default.
- W4309781919 cites W2200017991 @default.
- W4309781919 cites W2299918954 @default.
- W4309781919 cites W2346452181 @default.
- W4309781919 cites W2405035126 @default.
- W4309781919 cites W2558715006 @default.
- W4309781919 cites W2558999090 @default.
- W4309781919 cites W2565684601 @default.
- W4309781919 cites W2605952223 @default.
- W4309781919 cites W2744129621 @default.
- W4309781919 cites W2753953057 @default.
- W4309781919 cites W2777416523 @default.
- W4309781919 cites W2781821160 @default.
- W4309781919 cites W2785947426 @default.
- W4309781919 cites W2786016794 @default.
- W4309781919 cites W2789889445 @default.
- W4309781919 cites W2794875394 @default.
- W4309781919 cites W2801253218 @default.
- W4309781919 cites W2898402099 @default.
- W4309781919 cites W2901527454 @default.
- W4309781919 cites W2909240409 @default.
- W4309781919 cites W2910734083 @default.
- W4309781919 cites W2949311246 @default.
- W4309781919 cites W2949867299 @default.
- W4309781919 cites W2956961449 @default.
- W4309781919 cites W2959938226 @default.
- W4309781919 cites W2962886429 @default.
- W4309781919 cites W2962949667 @default.
- W4309781919 cites W2963396480 @default.
- W4309781919 cites W2966357564 @default.
- W4309781919 cites W2966787092 @default.
- W4309781919 cites W2972608805 @default.
- W4309781919 cites W2972741532 @default.
- W4309781919 cites W2989848927 @default.
- W4309781919 cites W2994158303 @default.
- W4309781919 cites W3001465925 @default.
- W4309781919 cites W3005769002 @default.
- W4309781919 cites W3014805132 @default.
- W4309781919 cites W3016077459 @default.
- W4309781919 cites W3018980093 @default.
- W4309781919 cites W3029836473 @default.
- W4309781919 cites W3032123378 @default.
- W4309781919 cites W3037979089 @default.
- W4309781919 cites W3045928028 @default.
- W4309781919 cites W3093988619 @default.
- W4309781919 cites W3094062017 @default.
- W4309781919 cites W3096561213 @default.
- W4309781919 cites W3098269892 @default.
- W4309781919 cites W3099152386 @default.
- W4309781919 cites W3104097132 @default.
- W4309781919 cites W3104956673 @default.
- W4309781919 cites W3107527779 @default.
- W4309781919 cites W3125468681 @default.
- W4309781919 cites W3128361605 @default.
- W4309781919 cites W3133458480 @default.
- W4309781919 cites W3136918052 @default.
- W4309781919 cites W3146944767 @default.
- W4309781919 cites W3159653252 @default.
- W4309781919 cites W3162048269 @default.
- W4309781919 cites W3165706714 @default.
- W4309781919 cites W3175786839 @default.
- W4309781919 cites W3177828909 @default.
- W4309781919 cites W3200503833 @default.
- W4309781919 cites W3206585172 @default.
- W4309781919 cites W3210813272 @default.
- W4309781919 cites W3217042593 @default.
- W4309781919 cites W3217681006 @default.
- W4309781919 cites W4205352280 @default.
- W4309781919 cites W4284974145 @default.