Zobrazeno 1 - 10
of 257
pro vyhledávání: '"GRUDININ, Sergei"'
Autor:
Darankoum, Davy, Villalba, Manon, Allioux, Clelia, Caraballo, Baptiste, Dumont, Carine, Gronlier, Eloise, Roucard, Corinne, Roche, Yann, Habermacher, Chloe, Grudinin, Sergei, Volle, Julien
Epilepsy represents the most prevalent neurological disease in the world. One-third of people suffering from mesial temporal lobe epilepsy (MTLE) exhibit drug resistance, urging the need to develop new treatments. A key part in anti-seizure medicatio
Externí odkaz:
http://arxiv.org/abs/2410.03385
Analyzing volumetric data with rotational invariance or equivariance is an active topic in current research. Existing deep-learning approaches utilize either group convolutional networks limited to discrete rotations or steerable convolutional networ
Externí odkaz:
http://arxiv.org/abs/2404.15979
Effective recognition of spatial patterns and learning their hierarchy is crucial in modern spatial data analysis. Volumetric data applications seek techniques ensuring invariance not only to shifts but also to pattern rotations. While traditional me
Externí odkaz:
http://arxiv.org/abs/2403.19612
Autor:
Hatch, Harold W., Bergonzo, Christina, Blanco, Marco A., Yuan, Guangcui, Grudinin, Sergei, Lund, Mikael, Curtis, Joseph E., Grishaev, Alexander V., Liu, Yun, Shen, Vincent K.
Publikováno v:
Journal of Chemical Physics; 9/7/2024, Vol. 161 Issue 9, p1-14, 14p
In this work, we introduce 6D Convolutional Neural Network (6DCNN) designed to tackle the problem of detecting relative positions and orientations of local patterns when processing three-dimensional volumetric data. 6DCNN also includes SE(3)-equivari
Externí odkaz:
http://arxiv.org/abs/2107.12078
The potential of deep learning has been recognized in the protein structure prediction community for some time, and became indisputable after CASP13. In CASP14, deep learning has boosted the field to unanticipated levels reaching near-experimental ac
Externí odkaz:
http://arxiv.org/abs/2105.07407
Processing information on 3D objects requires methods stable to rigid-body transformations, in particular rotations, of the input data. In image processing tasks, convolutional neural networks achieve this property using rotation-equivariant operatio
Externí odkaz:
http://arxiv.org/abs/2011.07980
Akademický článek
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Autor:
Pagès, Guillaume, Grudinin, Sergei
Motivation: Thanks to the recent advances in structural biology, nowadays three-dimensional structures of various proteins are solved on a routine basis. A large portion of these contain structural repetitions or internal symmetries. To understand th
Externí odkaz:
http://arxiv.org/abs/1810.12026
The computational prediction of a protein structure from its sequence generally relies on a method to assess the quality of protein models. Most assessment methods rank candidate models using heavily engineered structural features, defined as complex
Externí odkaz:
http://arxiv.org/abs/1801.06252