By Π Π°ΠΌΡΡΠ½Π΄Π°Ρ ΠΡ Π°ΡΠ°Ρ , β¦
Π Π°ΠΌΡΡΠ½Π΄Π°Ρ Π., ΠΡΡΠΌΠ°Π½ Π., Π£ΠΎΠ»ΡΠ΅ΡΡ Π., ΠΠ°Π½Π΄Π΅ Π., 2020
ΠΠ»ΡΠ±ΠΎΠΊΠΎΠ΅ ΠΎΠ±ΡΡΠ΅Π½ΠΈΠ΅ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΠ΅Ρ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΡΡΠΏΠ΅Ρ ΠΈ Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ ΠΎΠ±Π»Π°ΡΡΡΡ , Π°ΠΊΡΠΈΠ²Π½ΠΎ ΠΏΡΠΎΠ½ΠΈΠΊΠ°Ρ Π² ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΡΠ΅ Π½Π°ΡΡΠ½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎ Π² Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡ ΠΈ ΡΠΌΠ΅ΠΆΠ½ΡΠ΅ Π΄ΠΈΡΡΠΈΠΏΠ»ΠΈΠ½Ρ. ΠΡΠ° ΠΊΠ½ΠΈΠ³Π° ΠΈΡΡΠ»Π΅Π΄ΡΠ΅Ρ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Π³Π»ΡΠ±ΠΎΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ Π² ΡΠ°ΠΊΠΈΡ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡΡ , ΠΊΠ°ΠΊ Π³Π΅Π½ΠΎΠΌΠΈΠΊΠ°, Ρ ΠΈΠΌΠΈΡ, Π±ΠΈΠΎΡΠΈΠ·ΠΈΠΊΠ°, ΠΌΠΈΠΊΡΠΎΡΠΊΠΎΠΏΠΈΡ ΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½Π°, ΠΎΡ Π²Π°ΡΡΠ²Π°Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΡΠ²ΡΠ·Π°Π½Π½ΡΠ΅ Ρ ΠΆΠΈΠ²ΡΠΌΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·ΠΌΠ°ΠΌΠΈ. ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΡΠ΅ ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠ΅ Π°ΡΡ ΠΈΡΠ΅ΠΊΡΡΡΡ Π³Π»ΡΠ±ΠΎΠΊΠΈΡ ΡΠ΅ΡΠ΅ΠΉ ΠΏΠΎΠ΄Ρ ΠΎΠ΄ΡΡ Π΄Π»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΡΠΈΠΊΠΎΠ² ΠΈ ΡΡΠ΅Π½ΡΡ , Π·Π°Π½ΠΈΠΌΠ°ΡΡΠΈΡ ΡΡ ΡΠΎΠ·Π΄Π°Π½ΠΈΠ΅ΠΌ Π½ΠΎΠ²ΡΡ Π»Π΅ΠΊΠ°ΡΡΡΠ² ΠΈΠ»ΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΠΌΠΈ Π² ΠΎΠ±Π»Π°ΡΡΠΈ Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ Π³Π΅Π½Π΅ΡΠΈΠΊΠΈ.
Bharath Ramsundar, Peter Eastman, Patrick Walters, V. Pande, 2020
Deep learning has achieved impressive successes across many industries and is increasingly integrated into applied scientific research, particularly in biology and related fields. This book explores the application of deep learning in areas such as genomics, chemistry, biophysics, microscopy, and medicine, covering research related to living organisms. The standard deep network architectures presented are well-suited for developers and scientists engaged in drug discovery or research in biology and genetics. The book includes practical examples, detailing the full cycle of new drug discovery, a complex scientific challenge at the intersection of physics, chemistry, biology, and medicine.