Logistic regression models to predict solvent accessible residues using sequence- and homology-based qualitative and quantitative descriptors applied to a domain-complete X-ray structure learning set

A working example of relative solvent accessibility (RSA) prediction for proteins is presented. Novel logistic regression models with various qualitative descriptors that include amino acid type and quantitative descriptors that include 20- and six-term sequence entropy have been built and validated...

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Detalles Bibliográficos
Autores principales: Nepal, Reecha, Spencer, Joanna, Bhogal, Guneet, Nedunuri, Amulya, Poelman, Thomas, Kamath, Thejas, Chung, Edwin, Kantardjieff, Katherine, Gottlieb, Andrea, Lustig, Brooke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2015
Materias:
Teaching and Education
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665666/
https://www.ncbi.nlm.nih.gov/pubmed/26664348
http://dx.doi.org/10.1107/S1600576715018531

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665666/
https://www.ncbi.nlm.nih.gov/pubmed/26664348
http://dx.doi.org/10.1107/S1600576715018531

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