title: Application of wavelet-based tools to study the dynamics of biological processes.
abstract: The article makes use of three different examples (sensory information processing in the rat trigeminal complex, intracellular interaction in snail neurons and multimodal dynamics in nephron autoregulation) to demonstrate how modern approaches to time-series analysis based on the wavelet-transform can provide information about the underlying complex biological processes.
authors.affiliation: Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410026 Saratov, Russia. pavlov@chaos.ssu.runnet.ru
authors.forename: Alexey N
authors.initials: AN
authors.lastname: Pavlov
authors.forename: Valeri A
authors.initials: VA
authors.lastname: Makarov
authors.forename: Erik
authors.initials: E
authors.lastname: Mosekilde
authors.forename: Olga V
authors.initials: OV
authors.lastname: Sosnovtseva
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006973:Hypertension / Q000378:metabolism; D008432:Mathematical Computing; D053858:Metabolic Networks and Pathways; D008857:Microscopy, Interference; D009399:Nephrons / Q000378:metabolism; D009474:Neurons / Q000502:physiology; D009991:Oscillometry; D051381:Rats; D011918:Rats, Inbred SHR; D012815:Signal Processing, Computer-Assisted; D012908:Snails / Q000378:metabolism; D012984:Software; D014278:Trigeminal Nuclei / Q000378:metabolism