Protein threading using PROSPECT: Design and evaluation
201 citations recorded by the source corpus.
Subfields: Materials Chemistry, Molecular Biology
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Citations in the corpus
- Protein threading using residue co-variation and deep learning (2018, methodology): “Pairwise information such as contact potential and predicted contacts/distance have been attempted by a few methods including PROSPECT (Xu and Xu, 2000), RAPTOR (Xu et al.”
- LOMETS: A local meta-threading-server for protein structure prediction (2007, methodology): “LOMETS server takes predictions from nine different servers that represent a diverse set of state-of-the-art threading algorithms, i.e. FUGUE (13), HHSEARCH (14), PROSPECT2 (15), SAM-T02 (16), SPARKS2 (17), SP3 (18) programs were copied from other laboratories and the last three developed in our own ”
- Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations (2021, background): “It integrates 11 state-of-the-art threading programs: one contact-based threading program CEthreader (Zheng et al., 2019b), three profile HMM-based threading programs HHpred (Meier and So¨ding, 2015), HHsearch (So¨ding, 2005), and PRC (Madera, 2008), and seven profile-based threading programs FFAS3D (”
- Detecting distant-homology protein structures by aligning deep neural-network based contact maps (2019, background): “Several efforts have been previously made to incorporate pair-wise contacts into dynamic programming and subsequent threading alignments [12,13,26,27].”
- Comparing two K-category assignments by a K-category correlation coefficient (2004, unknown): “…et al., 1998), jpred (Cuff and Barton, 1999), psipred(Jones, 1999), prof king (Ouali and King, 1999), apssp2(Raghava, 2000), prospect(Xu and Xu, 2000), phdpsi(Przybylski and Rost, 2001), sspro2(Pollastri et al., 2002), profsec(Rost, 2003). tion problem(Rost and Sander, 1993; Koh et…”
- Ab initio modeling of small proteins by iterative TASSER simulations (2007, unknown): “Historically, protein structure prediction was classified into three categories: (i) comparative modeling [3,4], (ii) threading [5-9], and (iii) ab initio folding [10-15].”
- The JCSG MR pipeline: optimized alignments, multiple models and parallel searches (2007, methodology): “D64, 133–140 Other advanced fold-recognition methods based on sequences profiles or similar methods of using evolutionary information include 3D-PSSM (Kelley et al., 2000), FUGUE (Shi et al., 2001), BIOINBGU (Fischer, 2000), PROSPECT (Xu & Xu, 2000) and SAMT98 (Karplus et al., 1998).”
- Using iterative fragment assembly and progressive sequence truncation to facilitate phasing and crystal structure determination of distantly related proteins. (2016, unknown): “I-TASSER The query sequence is first threaded through a nonredundant structure library derived from the Protein Data Bank (PDB) to search for structural templates and supersecondary-structure motifs using LOMETS (Wu & Zhang, 2007), a meta-threading algorithm consisting of eight distinct programs: FF”
- EVA: evaluation of protein structure prediction servers (2003, background): “... (24) SwissModel http://www.expasy.org/swissmod/ T Schwede, MC Peitsch and N Guex (30) Threading/fold recognition 3D-PSSM http://www.sbg.bio.ic.ac.uk/~3dpssm L Kelley, B Maccallum and M Sternberg (31) BLAST http://www.ncbi.nlm.nih.gov/BLAST S Karlin and S Altschul (32) FUGUE http://www-cryst.bioc”
- SPARKS 2 and SP3 servers in CASP6 (2005, background): “18–23 More recent work attempts to optimally combine the sequence and structure information for a more accurate/sensitive fold recognition.”