Search Results for author:
Found 6 papers, 2 papers with code
Stable Autonomous Flow Matching
Despite this, connections between control theory and generative models in the literature are sparse, even though there are several machine learning applications with physically stable data points.
Protein Structure Prediction until CASP15
In Dec 2020, the results of AlphaFold2 were presented at CASP14, sparking a revolution in the field of protein structure predictions.
Protein sequence-to-structure learning: Is this the end(-to-end revolution)?
The potential of deep learning has been recognized in the protein structure prediction community for some time, and became indisputable after CASP13.
Using micro- and macro-level network metrics unveils top communicative gene modules in psoriasis
Methods: In order to cast light on the complex molecular interactions in psoriasis vulgaris at both protein-protein interactions and transcriptomics levels, we analyzed a set of microarray gene expression analysis consisting of 170 paired lesional and non-lesional samples.
GraphQA: Protein Model Quality Assessment using Graph Convolutional Network
Proteins are ubiquitous molecules whose function in biological processes is determined by their 3D structure.
Deep transfer learning in the assessment of the quality of protein models
RESULTS: We first introduce a deep neural network architecture to predict model quality using significantly fewer input features than state-of-the-art methods.
