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
Titel:
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
Auteur:
Nepal, Reecha Spencer, Joanna Bhogal, Guneet Nedunuri, Amulya Poelman, Thomas Kamath, Thejas Chung, Edwin Kantardjieff, Katherine Gottlieb, Andrea Lustig, Brooke
Verschenen in:
Journal of applied crystallography
Paginering:
Jaargang 48 (2015) nr. 6 pagina's 1976-1984
Jaar:
2015-02-01
Inhoud:
Uitgever:
International Union of Crystallography, 5 Abbey Square, Chester, Cheshire CH1 2HU, England