The ASTRAL compendium for protein structure and sequence analysis

By Steven E. Brenner, Patrice Koehl, Michael Levitt. 2000

511 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Hidden Markov model speed heuristic and iterative HMM search procedure (2010, neutral): “5 database filtered for 40% identity [5,11-13].”
MRFalign: Protein Homology Detection through Alignment of Markov Random Fields (2014, methodology): “Early methods such as [24] usually conduct straightforward comparison of feature vectors, but are not very sensitive [25].”
SCOPe: Structural Classification of Proteins—extended, integrating SCOP and ASTRAL data and classification of new structures (2013, methodology): “The SCOPe website offers a modest redesign of the SCOP website, presenting all SCOPe, SCOP and ASTRAL data through a single, unified web interface.”
Sequence clustering strategies improve remote homology recognitions while reducing search times. (2002, background): “The ASTRAL compendium (Brenner et al., 2000) at http://astral.stanford.edu/ provides a series of SCOP domain sequence databases clustered at different identities.”
SCOPe: Manual Curation and Artifact Removal in the Structural Classification of Proteins – extended Database (2016, background): “06 with a 95% sequence identity threshold (see [8] for details), the tagless set contains 25,631 representatives (out of 180,206 total PDB chains in ASTRAL 2.”
MUSCLE: multiple sequence alignment with high accuracy and high throughput. (2004, methodology): “The Twilight set contains 1994 domains from the Astral database (26) with pairwise sequence similarity e-values <1, divided into 236 folds according to the SCOP classi®cation (27).”
HorA web server to infer homology between proteins using sequence and structural similarity (2009, background): “69 domains with less than 40% sequence identity obtained from ASTRAL (21) are paired in an all-on-all fashion.”
ASTRAL compendium enhancements (2002, methodology): “As shown in Figure 2, each set is fully compared against itself using BLAST (10), and subsets are created using the three similarity criteria (BLAST E-values, sequence identity and SCOP classification) described previously (5).”
GR-Align: fast and flexible alignment of protein 3D structures using graphlet degree similarity (2014, background): “Astral_40 (Brenner et al., 2000) is a derivative of SCOP database, so that it only contains protein domains having540% sequence identity.”
MUFOLD: A new solution for protein 3D structure prediction (2010, methodology): “The 200 target proteins were selected from the July 2005 release of Astral database,48 and they satisfy the following criteria: (1) length (cid”
A simple and fast secondary structure prediction method using hidden neural networks (2005, methodology): “The test and training sets were built using the PDB25 set (25% maximum sequence identity) grouped together by ASTRAL (Brenner et al., 2000).”