Add to ORKGThis chapter contains sections titled: Introduction, Kernel Matrix Completion, Information Geometry of Positive Definite Matrices, Approximating an Incomplete Kernel Matrix, Protein Structure Classification Experiment, Conclusion
Protein subcellular localization is a crucial ingredient to many important inferences about cellular...
Abstract: Protein subcellular localization is a crucial ingredient to many important inferences abou...
Biological sequence classification (such as protein remote homology detection) solely based on seque...
The thesis describes the application of kernel methods and, in particular, the support vector machin...
University of Minnesota Ph.D. dissertation. Major: Computer Science. Advisor: George Karypis. 1 comp...
Motivation: This work aims to develop computational methods to annotate protein structures in an aut...
We propose a kernel method for predicting the function of proteins that makes use of 3D structural i...
International audienceMOTIVATION: This work aims to develop computational methods to annotate protei...
The focus of this thesis is to develop computational techniques for analysis of protein structures. ...
Determining protein sequence similarity is an important task for protein classification and homology...
Sequence and structure are complementary pieces of information that can be used to infer protein fun...
The ability to identify protein binding sites and to detect specific amino acid residues that contri...
Structural alignments are the most widely used tools for comparing proteins with low sequence simila...
Determining protein structure and function experimentally is both costly and time consuming. Transfe...
AbstractThe amino acid sequence of a protein is the key to understanding its structure and ultimatel...
Protein subcellular localization is a crucial ingredient to many important inferences about cellular...
Abstract: Protein subcellular localization is a crucial ingredient to many important inferences abou...
Biological sequence classification (such as protein remote homology detection) solely based on seque...
The thesis describes the application of kernel methods and, in particular, the support vector machin...
University of Minnesota Ph.D. dissertation. Major: Computer Science. Advisor: George Karypis. 1 comp...
Motivation: This work aims to develop computational methods to annotate protein structures in an aut...
We propose a kernel method for predicting the function of proteins that makes use of 3D structural i...
International audienceMOTIVATION: This work aims to develop computational methods to annotate protei...
The focus of this thesis is to develop computational techniques for analysis of protein structures. ...
Determining protein sequence similarity is an important task for protein classification and homology...
Sequence and structure are complementary pieces of information that can be used to infer protein fun...
The ability to identify protein binding sites and to detect specific amino acid residues that contri...
Structural alignments are the most widely used tools for comparing proteins with low sequence simila...
Determining protein structure and function experimentally is both costly and time consuming. Transfe...
AbstractThe amino acid sequence of a protein is the key to understanding its structure and ultimatel...
Protein subcellular localization is a crucial ingredient to many important inferences about cellular...
Abstract: Protein subcellular localization is a crucial ingredient to many important inferences abou...
Biological sequence classification (such as protein remote homology detection) solely based on seque...