Work

Solving the molecular distance geometry problem with inaccurate distance data

Year: 2013

Type: article

Abstract: We present a new iterative algorithm for the molecular distance geometry problem with inaccurate and sparse data, which is based on the solution of linear systems, maximum cliques, and a minimization of nonlinear least-squares function. Computational results with real protein structures are presented in order to validate our approach.

Source: BMC Bioinformatics

DOI: 10.1186/1471-2105-14-s9-s7

Authors: Michael Souza, Carlile Lavor, Albert Muritiba, Nelson Maculan

Institutions: Universidade Federal do Ceará, Universidade Estadual de Campinas (UNICAMP), Universidade Federal do Rio de Janeiro

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,990

Funders: Fundação de Amparo à Pesquisa do Estado de São Paulo, Conselho Nacional de Desenvolvimento Científico e Tecnológico