Proteins play a central role in biology from immune recognition to brain activity. While major advances in machine learning have improved our ability to predict protein structure from sequence, determining protein function from structure remains a major challenge. Here, we introduce Holographic Convolutional Neural Network (H-CNN) for proteins, which is a physically motivated machine learning approach to model amino acid preferences in protein structures. H-CNN reflects physical interactions in a protein structure and recapitulates the functional information stored in evolutionary data. H-CNN accurately predicts the impact of mutations on protein function, including stability and binding of protein complexes. Our interpretable computational...
University of Minnesota Ph.D. dissertation. July 2013. Major. Computer science. Advisor: George Kary...
Motivation: SCOPe 2.07 is a dataset of 276,231 protein domains that have been partitioned into varyi...
Determining the different conformational states of a protein and the transition paths between them i...
Proteins are the basic building blocks of biological organisms, and are responsible for a variety of...
Flexibility is often a key determinant of protein func- tion. To elucidate the link between their m...
Life is orchestrated via an interplay of many biomolecules. Any understanding of biomolecular functi...
Research has shown that the functionalities of proteins are largely influenced by their three dimens...
Deep learning, a powerful methodology for data-driven modelling, has been shown to be useful in tack...
International audienceBackground. The availability of large databases containing high resolution thr...
Recent advances in protein function prediction exploit graph-based deep learning approaches to corre...
Abstract Background Central to protein biology is the understanding of how structural elements give ...
The ability to correctly predict the functional role of proteins from their amino acid sequences wou...
Thesis (Ph.D.)--University of Washington, 2022Understanding the rules of protein structure folding h...
A protein performs biological functions by folding to a particular 3D structure. To accurately model...
Machine learning (ML) has been an important arsenal in computational biology used to elucidate prote...
University of Minnesota Ph.D. dissertation. July 2013. Major. Computer science. Advisor: George Kary...
Motivation: SCOPe 2.07 is a dataset of 276,231 protein domains that have been partitioned into varyi...
Determining the different conformational states of a protein and the transition paths between them i...
Proteins are the basic building blocks of biological organisms, and are responsible for a variety of...
Flexibility is often a key determinant of protein func- tion. To elucidate the link between their m...
Life is orchestrated via an interplay of many biomolecules. Any understanding of biomolecular functi...
Research has shown that the functionalities of proteins are largely influenced by their three dimens...
Deep learning, a powerful methodology for data-driven modelling, has been shown to be useful in tack...
International audienceBackground. The availability of large databases containing high resolution thr...
Recent advances in protein function prediction exploit graph-based deep learning approaches to corre...
Abstract Background Central to protein biology is the understanding of how structural elements give ...
The ability to correctly predict the functional role of proteins from their amino acid sequences wou...
Thesis (Ph.D.)--University of Washington, 2022Understanding the rules of protein structure folding h...
A protein performs biological functions by folding to a particular 3D structure. To accurately model...
Machine learning (ML) has been an important arsenal in computational biology used to elucidate prote...
University of Minnesota Ph.D. dissertation. July 2013. Major. Computer science. Advisor: George Kary...
Motivation: SCOPe 2.07 is a dataset of 276,231 protein domains that have been partitioned into varyi...
Determining the different conformational states of a protein and the transition paths between them i...