NNvPDB: Neural Network based Protein Secondary Structure Prediction with PDB Validation
| Autor: | Sakthivel, Seethalakshmi, S.K.M, Habeeb |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Sequence
online server Artificial neural network Computer science neural network Protein Data Bank (RCSB PDB) General Medicine Web Server computer.software_genre Protein secondary structure prediction automatic validation Electromagnetic coil Server Helix Data mining protein secondary structure computer Protein secondary structure |
| Zdroj: | Bioinformation |
| ISSN: | 0973-2063 0973-8894 |
| Popis: | The predicted secondary structural states are not cross validated by any of the existing servers. Hence, information on the level of accuracy for every sequence is not reported by the existing servers. This was overcome by NNvPDB, which not only reported greater Q3 but also validates every prediction with the homologous PDB entries. NNvPDB is based on the concept of Neural Network, with a new and different approach of training the network every time with five PDB structures that are similar to query sequence. The average accuracy for helix is 76%, beta sheet is 71% and overall (helix, sheet and coil) is 66%. Availability http://bit.srmuniv.ac.in/cgi-bin/bit/cfpdb/nnsecstruct.pl |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|