Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships.

By Steven E. Brenner, Cyrus Chothia, Tim J. P. Hubbard. 1998

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Citations in the corpus

Hidden Markov model speed heuristic and iterative HMM search procedure (2010, background): “Current datasets of homologous proteins primarily utilize either protein structure or sequence conservation to infer homology [8-10].”
Evaluating Protein Transfer Learning with TAPE (2019, background): “Other approaches besides sequence identity ﬁltering also exist, depending on the generalization the task attempts to test [20].”
Sensitive protein alignments at tree-of-life scale using DIAMOND (2021, background): “Establishing a ground truth on the basis of SCOP domains has been considered the gold standard for benchmarking protein aligners 13 .”
Comparative Protein Structure Modeling Using MODELLER (2007, methodology): “Brenner et al. (1998) showed that these methods detect only ∼ 18% of the homologous pairs at less than 40% sequence identity, while they identify more than 90% of the relationships when sequence identity is between 30% and 40% (Brenner et al., 1998 sequence identity, indicated that BLAST is able to…”
A comparison of profile hidden Markov model procedures for remote homology detection. (2002, methodology): “In order to see the performance of HMMER and SAM in the context of other sequence comparison methods, we re-ran test 2 on PSI-BLAST (11), the most popular iterative profile method, and WU-BLAST (http://sapiens.wustl.edu/blast), one of the best pairwise methods in Brenner et al. ( 17 ).”
Pcons: A neural‐network–based consensus predictor that improves fold recognition (2001, background): “In several recent studies the ability of different methods to detect proteins that share the same fold has been studied (Abagyan and Batalov 1997; Di Francesco et al. 1997; Park et al. 1997, 1998; Brenner et al. 1998; Lindahl and Elofsson 2000).”
UniqueProt: creating representative protein sequence sets (2003, background): “Arguably, the feature that is most conserved with evolutionarily diverging sequences is protein structure (8–10).”
Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs. (2004, methodology): “Furthermore, it has become more common to use statistical scoring schemes, especially E -values in BLAST, to measure the statistical significance of the homology in order to determine the orthologs across organisms (Tatusov et al. 1997; Brenner et al. 1998).”
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction (2006, methodology): “The SCOP structural classification database [33,34] has become the most common standard used for the benchmarking of protein structure prediction methods [3,11,28,40] and was used in this work.”
Statistical analysis of amino acid patterns in transmembrane helices: the GxxxG motif occurs frequently and in association with beta-branched residues at neighboring positions. (2000, methodology): “…of proteins in the database, homology elimination at the level of the TMDs was a practical and effective alternative to more complex and intensive clustering procedures at the protein level (Boberg et al., 1992; Brenner et al., 1998; Gerstein, 1998; Hobohm & Sander, 1994; Hobohm et al., 1992).”
OMA, A Comprehensive, Automated Project for the Identification of Orthologs from Complete Genome Data: Introduction and First Achievements (2005, methodology): “The use of BLAST [5] was evaluated, but in the present case, we considered the speed increase not sufficient to compensate the loss in sensitivity [20].”
Using the Basic Local Alignment Search Tool (BLAST). (2007, background): “The most recent gapped BLAST, or BLAST2, is recommended, in part because older versions of BLAST are slower and reported to overestimate the significance of database matches (Brenner et al. 1998).”
Comparative Protein Structure Modeling Using MODELLER (2016, methodology): “Brenner et al. (1998) showed that these methods detect only 18% of the homologous pairs at less than 40% sequence identity, while they identify more than 90% of the relationships when sequence identity is between 30% and 40% (Brenner et al., 1998).”
Comparison of sequence profiles. Strategies for structural predictions using sequence information (2008, background): “Also, other measures of sequence similarity, such as statistical significance of the alignment, allow for better distinction between homologies and spurious sequence similarities ~ Brenner et al., 1998 !”
Evaluation and improvement of multiple sequence methods for protein secondary structure prediction (1999, background): “Recently, deﬁciencies in percentage identity have been quantiﬁed by Brenner et al. (1998) when scoring protein sequence database searches.”
Comparative Protein Structure Modeling Using Modeller (2006, methodology): “Brenner et al. (1998) showed that these methods detect only ~18% of the homologous pairs at less than 40% sequence identity, while they identify more than 90% of the relationships when sequence identity is between 30% and 40% (Brenner et al., 1998).”