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Apr 18, 2024 · A web server to gather information about three-dimensional (3-D) structure and function of proteins.
Jul 1, 2019 · Sequence name (optional) : Paste a protein sequence below : help. Output width : Parameters. Number of conformational states : Similarity threshold : Window width : User : public Last modification time : Thu Jun 6 13:29:05 2024. Current time : Tue Jul 2 06:08:56 2024.
Dec 1, 1995 · This improved SOPM method (SOPMA) correctly predicts 69.5% of amino acids for a three-state description of the secondary structure (α-helix, β-sheet and coil) in a whole database containing 126 chains of non-homologous (less than 25% identity) proteins.
This improved SOPM method (SOPMA) correctly predicts 69.5% of amino acids for a three-state description of the secondary structure (alpha-helix, beta-sheet and coil) in a whole database containing 126 chains of non-homologous (less than 25% identity) proteins.
SOPMA (Self-Optimized Prediction Method with Alignment) is an improvement of SOPM method. These methods are based on the homologue method of Levin et al.. The improvent takes place in the fact that SOPMA takes into account information from an alignment of sequences belonging to the same family.
Mar 18, 2019 · SOPMA is a improved method of SOPM, which correctly predicts 69.5% of amino acids for a three-state description of the secondary structure (alpha-helix, beta-sheet, and coil) in a whole...
The secondary structure evaluation of protein is carried out with the help of Self Optimized Prediction Method with Alignment (SOPMA) [16]. The secondary structure indicates whether a given amino...
May 5, 2017 · SOPMA (Self-Optimized Prediction Method with Alignment) is a modified version of SOPM (Self-Optimized Prediction Method) predicting the secondary structure of a protein based on homologue method (Fig. 5.3). The SOPMA derived account information from an alignment of sequences belonging to the same family.
Using SOPMA, the predicted secondary structure of the protein sequences revealed the predominance of the random coil.
Choose methods : SOPM (Geourjon and Deleage, 1994) Choose parameters SOPMA (Geourjon and Deleage, 1995) Choose parameters HNN (Guermeur, 1997) MLRC on GOR4, SIMPA96 and SOPMA (Guermeur et al., 1998) When MLRC is checked GOR4, SOPMA and SIMPA96 predictions are not displayed.
