Cascaded multiple classifiers for secondary structure prediction

By M. Ouali, Ross D. King. 2000

348 citations recorded by the source corpus.

How researchers see this paper

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

Citations in the corpus

Decision trees for hierarchical multi-label classification (2008, unknown): “The program PROF (Ouali and King 2000) was used to this end.”
Machine learning for discovering missing or wrong protein function annotations (2019, methodology): “In the case of an unknown structure, the software PROF [45] was used to predict it.”
GeneSilico protein structure prediction meta-server (2003, unknown): “2. Secondary structure prediction methods PSIPRED (13), SAM-T02 (14) and PROF ( 15 ).”
The MPI Bioinformatics Toolkit for protein sequence analysis (2006, unknown): “…structure section, Quick2D integrates the results of various secondary structure prediction programs, such as PSIPRED (18), JNET (19) and PROFKing (20), the transmembrane prediction of MEMSAT2 (21) and HMMTOP (22) and the disorder prediction of DISOPRED (23) into a single colored view.”
Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction (2013, background): “The secondary structure is not known for all yeast genes; however, it can be predicted from the protein sequence with reasonable accuracy, using Prof [24].”
EVA: evaluation of protein structure prediction servers (2003, unknown): “... F Pazos, O Olmea and A Valencia (37–39) Secondary structure APSSP2 http://www.imtech.res.in/raghava/apssp2/ G Raghava (40) Jpred http://jura.ebi.ac.uk:8888/ JA Cuff and GJ Barton (41) PHDsec http://cubic.bioc.columbia.edu/predictprotein B Rost and C Sander (42) PHDpsi http://cubic.bioc.columbia.”
Review: protein secondary structure prediction continues to rise. (2001, unknown): “(i) Ouali and King ( 64 ) combine neural networks and rule-based statistics in a cascade of classifiers.”
A simple and fast secondary structure prediction method using hidden neural networks (2005, unknown): “For example, in the Prof method (Ouali and King, 2000), the final prediction results were obtained using four layers, a large number of NNs, combined with linear discrimination of multiple cascaded classifiers.”