Intermediate sequences increase the detection of homology between sequences.

By Jong H. Park, Sarah A. Teichmann, Tim J. P. Hubbard, Cyrus Chothia. 1997

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Citations in the corpus

MRFalign: Protein Homology Detection through Alignment of Markov Random Fields (2014, background): “Sequence signature libraries [14] and intermediate sequence based methods [15,16] are also developed to make use of evolutionary information of a protein.”
Improvement of the GenTHREADER Method for Genomic Fold Recognition (2003, methodology): “, 1997), ISS (Park et al., 1997), SAM-T98 (Park et al.”
RSDB: representative protein sequence databases have high information content (2000, background): “We found that to achieve a low rate of false positive homology predictions in our experiments (Park et al., 1997), effective parameters for detecting true sequence relationships are h = 0.000 5 and j = 5–10.”
Comparison of sequence profiles. Strategies for structural predictions using sequence information (2008, methodology): “However, other approaches, such as Intermediate Sequence Search ~ Park et al., 1997 ! or starting PSI-BLAST search from different proteins from the homologous family ~ Aravind & Koo-nin, 1999 !”
Sequence clustering strategies improve remote homology recognitions while reducing search times. (2002, methodology): “IPS is more powerful in distant homology detection than ISS because it uses an intermediate profile instead of a single intermediate sequence to establish remote homology.”
Sequence comparisons using multiple sequences detect three times as many remote homologues as pairwise methods. (1998, methodology): “…hidden Markov models (HMMs; Krogh et al., 1994; Baldi et al., 1994; Eddy, 1995, 1996; Eddy et al., 1995; Hughey & Krogh, 1996), the position-speci®c-iterated (PSI) version of BLAST (Altschul et al., 1997), PROBE (Neuwald et al., 1997), and intermediate sequence searches (ISS; Park et al., 1997).”
Exploiting evolutionary relationships for predicting protein structures (2003, methodology): “Intermediate sequence search methods (Park et al., 1997) perform pairwise sequence alignments between the target and the database of known structures and, if no sequence similarity with a protein of known structure, the search is iteratively repeated using as queries all the sequences evolutionary…”
Alignment of protein sequences by their profiles (2004, background): “A number of studies assessed both the sensitivity of alignment methods in the detection of remote homologs (Park et al. 1997; Muller et al. 1999; Kelley et al. 2000; Rychlewski et al. 2000; Yona and Levitt 2000; Panchenko 2003; Sadreyev and Grishin 2003) and alignment accuracy (Jaroszewski et al.”
Practical limits of function prediction (2000, methodology): “12,16,22 The analysis of protein function was performed at four different levels: ( i ) enzymatic function classiﬁcation , representing a standard deﬁnition of the chemical model of the protein enzymatic function; ( ii ) functional annotations in the form of keywords , describing the biochemical…”
Pcons: A neural‐network–based consensus predictor that improves fold recognition (2001, methodology): “One way to study this is to sort the models according to the score and then plot the cumulative number of correct models versus incorrect models, as has been done in several earlier studies (Park et al. 1997, 1998).”
Multiple Sequence Alignment Based on Profile Alignment of Intermediate Sequences (2007, methodology): “Although most intermediate sequence search strategies define an intermediate sequence either as a common hit from database search that links two input sequences (Park et al. 1997; Gerstein 1998), or as hits that form a chain linking two input sequences (Salamov et al.”
Finding weak similarities between proteins by sequence profile comparison. (2003, background): “There are different ways to infer the connections between protein sequences in the sequence space; one group of methods tries to relate the two sequences being matched through the third sequence (3,4), while others detect increasingly divergent members of a given family by constructing multiple sequ”