Cargando…
Prediction of enzymes and non-enzymes from protein sequences based on sequence derived features and PSSM matrix using artificial neural network
The problem of predicting the enzymes and non-enzymes from the protein sequence information is still an open problem in bioinformatics. It is further becoming more important as the number of sequenced information grows exponentially over time. We describe a novel approach for predicting the enzymes...
Autores principales: | Naik, Pradeep Kumar, Mishra, Viplav Shankar, Gupta, Mukul, Jaiswal, Kunal |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Biomedical Informatics Publishing Group
2007
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2248448/ https://www.ncbi.nlm.nih.gov/pubmed/18288334 |
Ejemplares similares
-
Prediction of MHC binding peptide using Gibbs motif sampler, weight matrix and artificial neural network
por: Singh, Satarudra Prakash, et al.
Publicado: (2008) -
Structure modeling and comparative genomics for epimerase enzyme (Gal10p)
por: Sharma, Ashwani, et al.
Publicado: (2010) -
RetroPred: A tool for prediction, classification and extraction of non-LTR retrotransposons (LINEs & SINEs) from the genome by integrating PALS, PILER, MEME and ANN
por: Naik, Pradeep Kumar, et al.
Publicado: (2008) -
Comparative modeling of DszC, an enzyme in biodesulfurization, and performing in silico point mutation for increasing tendency to oil
por: Torktaz, Ibrahim, et al.
Publicado: (2012) -
Algorithm to find distant repeats in a single protein sequence
por: Banerjee, Nirjhar, et al.
Publicado: (2008)