Searching across hundreds of databases
Fueled by rapid progress in high-throughput sequencing, the size of public sequence databases doubles every two years. Searching the ever larger and more redundant databases is getting increasingly inefficient. Clustering can help to organize sequences into homologous and functionally similar groups and can improve the speed, sensitivity, and readability of homology searches. However, because the clustering time is quadratic in the number of sequences, standard sequence search methods are becoming impracticable.
Pubmed ID: 23945046 RIS Download
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It provides databases and tools useful for analyzing protein structures and their sequences. It is partially derived from, and augments the SCOP: Structural Classification of Proteins database, a database created by manual inspection and abetted by a battery of automated methods, aims to provide a detailed and comprehensive description of the structural and evolutionary relationships between all proteins whose structure is known. Most of the resources provided here depend upon the coordinate files maintained and distributed by the Protein Data Bank. Sponsors: This work is supported by grants from the NIH (1-P50-GM62412, 1-K22-HG00056) and the Searle Scholars Program (01-L-116), and by the US Department of Energy under contract DE-AC03-76SF00098.
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