Contrastive representation learning for 3d protein structures
Learning from 3D protein structures has gained wide interest in protein modeling and
structural bioinformatics. Unfortunately, the number of available structures is orders of …
structural bioinformatics. Unfortunately, the number of available structures is orders of …
[HTML][HTML] GEO-Nav: A geometric dataset of voltage-gated sodium channels
Voltage-gated sodium (Nav) channels constitute a prime target for drug design and
discovery, given their implication in various diseases such as epilepsy, migraine and ataxia …
discovery, given their implication in various diseases such as epilepsy, migraine and ataxia …
SHREC 2020: Multi-domain protein shape retrieval challenge
Proteins are natural modular objects usually composed of several domains, each domain
bearing a specific function that is mediated through its surface, which is accessible to vicinal …
bearing a specific function that is mediated through its surface, which is accessible to vicinal …
A joint learning approach based on self-distillation for keyphrase extraction from scientific documents
Keyphrase extraction is the task of extracting a small set of phrases that best describe a
document. Most existing benchmark datasets for the task typically have limited numbers of …
document. Most existing benchmark datasets for the task typically have limited numbers of …
SHREC 2021: Retrieval and classification of protein surfaces equipped with physical and chemical properties
This paper presents the methods that have participated in the SHREC 2021 contest on
retrieval and classification of protein surfaces on the basis of their geometry and …
retrieval and classification of protein surfaces on the basis of their geometry and …
Deformable protein shape classification based on deep learning, and the fractional Fokker–Planck and Kähler–Dirac equations
The classification of deformable protein shapes, based solely on their macromolecular
surfaces, is a challenging problem in protein–protein interaction prediction and protein …
surfaces, is a challenging problem in protein–protein interaction prediction and protein …
Nonrigid 3D shape retrieval with HAPPS: a novel hybrid augmented point pair signature
A robust, yet computationally efficient signature for describing 3D shape remains a
challenge for 3D computer vision and related applications. Having a signature that is …
challenge for 3D computer vision and related applications. Having a signature that is …
Enhancing Protein Classification with Graph Convolutional Neural Networks
A Mechache, H Kheddouci - International Conference on Pattern …, 2024 - Springer
Proteins are essential components of our lives. This has made their classification a very
active research field. Most research focuses on classifying proteins based on their structure …
active research field. Most research focuses on classifying proteins based on their structure …
Surface-based protein domains retrieval methods from a SHREC2021 challenge
Proteins are essential to nearly all cellular mechanism and the effectors of the cells activities.
As such, they often interact through their surface with other proteins or other cellular ligands …
As such, they often interact through their surface with other proteins or other cellular ligands …
3D Deformable Protein Shapes Classification based on Triangles-Stars and Composite Deep Neural Networks
In this paper, the problem of 3D protein deformable shape classification is addressed.
Proteins are macromolecules with deformable shapes, their classification based only on …
Proteins are macromolecules with deformable shapes, their classification based only on …