A carregar...
Publicação
Classification and Scoring of Protein Complexes
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 9.97 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Proteins interactions mediate all biological systems in a cell; understanding their interactions
means understanding the processes responsible for human life. Their structure can
be obtained experimentally, but such processes frequently fail at determining structures
of protein complexes. To address the issue, computational methods have been developed
that attempt to predict the structure of a protein complex, using information of its constituents.
These methods, known as docking, generate thousands of possible poses for
each complex, and require effective and reliable ways to quickly discriminate the correct
pose among the set of incorrect ones. In this thesis, a new scoring function was developed
that uses machine learning techniques and features extracted from the structure of the
interacting proteins, to correctly classify and rank the putative poses. The developed
function has shown to be competitive with current state-of-the-art solutions.
Descrição
Palavras-chave
Machine Learning Bioinformatics Protein-Protein Interactions Docking