User profiles for Oleg Favorov
Oleg V. FavorovUniversity of North Carolina at Chapel Hill Verified email at email.unc.edu Cited by 4266 |
Role of primary somatosensory cortex in the coding of pain
CJ Vierck, BL Whitsel, OV Favorov, AW Brown… - Pain, 2013 - journals.lww.com
Interactions between subregions of somatosensory cortex during nociceptive stimulation
are accompanied by clinically relevant alterations of cortical responses to myelinated and …
are accompanied by clinically relevant alterations of cortical responses to myelinated and …
QuShape: rapid, accurate, and best-practices quantification of nucleic acid probing information, resolved by capillary electrophoresis
Chemical probing of RNA and DNA structure is a widely used and highly informative approach
for examining nucleic acid structure and for evaluating interactions with protein and small-…
for examining nucleic acid structure and for evaluating interactions with protein and small-…
Dynamic representations of the somatosensory cortex
M Tommerdahl, OV Favorov, BL Whitsel - Neuroscience & Biobehavioral …, 2010 - Elsevier
Neural representation of somatosensory events undergoes major transformation in the
primary somatosensory cortex (SI) from its original, more or less isomorphic, form found at the …
primary somatosensory cortex (SI) from its original, more or less isomorphic, form found at the …
Single-molecule correlated chemical probing of RNA
PJ Homan, OV Favorov, CA Lavender… - Proceedings of the …, 2014 - pnas.org
Complex higher-order RNA structures play critical roles in all facets of gene expression;
however, the through-space interaction networks that define tertiary structures and govern …
however, the through-space interaction networks that define tertiary structures and govern …
Demonstration of discrete place‐defined columns—segregates—in the cat SI
OV Favorov, ME Diamond - Journal of Comparative Neurology, 1990 - Wiley Online Library
… These new data, as well as quantitative analyses of maxRF data collected in earlier
experiments (Favorov et al., ’87), constitute the results of this study. Our purpose is twofold: (1) to …
experiments (Favorov et al., ’87), constitute the results of this study. Our purpose is twofold: (1) to …
SHAPE-enabled fragment-based ligand discovery for RNA
MJ Zeller, O Favorov, K Li, A Nuthanakanti… - Proceedings of the …, 2022 - pnas.org
The transcriptome represents an attractive but underused set of targets for small-molecule
ligands. Here, we devise a technology that leverages fragment-based screening and SHAPE-…
ligands. Here, we devise a technology that leverages fragment-based screening and SHAPE-…
Minicolumnar organization within somatosensory cortical segregates: I. Development of afferent connections
OV Favorov, DG Kelly - Cerebral Cortex, 1994 - academic.oup.com
… (Favorov and Whitsel, 1988a; Favorov and Diamond, 1990). In the following companion article
(Favorov … A brief report on this work has appeared elsewhere (Favorov and Kelly, 1991). …
(Favorov … A brief report on this work has appeared elsewhere (Favorov and Kelly, 1991). …
Spatial organization of the peripheral input to area 1 cell columns. I. The detection of 'segregates'
O Favorov, BL Whitsel - Brain Research Reviews, 1988 - Elsevier
Extracellular single neuron recording methods are used to study the RFs of neurons
comprising area 1 cell columns in unanesthetized Macaca fascicularis monkeys. The RF data …
comprising area 1 cell columns in unanesthetized Macaca fascicularis monkeys. The RF data …
Quantification of mild traumatic brain injury via cortical metrics: analytical methods
Mild traumatic brain injuries are difficult to diagnose or assess with commonly used diagnostic
methods. However, the functional state of cerebral cortical networks can be rapidly and …
methods. However, the functional state of cerebral cortical networks can be rapidly and …
Neocortical layer 4 as a pluripotent function linearizer
OV Favorov, O Kursun - Journal of neurophysiology, 2011 - journals.physiology.org
A highly effective kernel-based strategy used in machine learning is to transform the input
space into a new “feature” space where nonlinear problems become linear and more readily …
space into a new “feature” space where nonlinear problems become linear and more readily …