UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

ABSTRACT:

Background

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions.

Results

uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of

SUBMITTER: Adamczak R 

PROVIDER: S-EPMC5198500 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature