شماره ركورد كنفرانس :
3140
عنوان مقاله :
Comparison between Spatial Statistics Model and Bidirectional Hidden Markov Model for Assignment of Protein Sequences
عنوان به زبان ديگر :
Comparison between Spatial Statistics Model and Bidirectional Hidden Markov Model for Assignment of Protein Sequences
پديدآورندگان :
Rezaei Wahid نويسنده Faculty of Mathematical Science- Tarbiat Modares University - Tehran - Iran , Mohammadzadeh Mohsen نويسنده Faculty of Mathematical Science- Tarbiat Modares University - Tehran - Iran , Pezeshk Hamid نويسنده School of Mathematics - Statistics and Computer Science - College of Science - University of Tehran and Bioinformatics Research Group - Institute for Research in Fundamental Sciences (IPM) - Iran
كليدواژه :
Rectangular lattice , BPHMM , Spatial Statistic , Bidirectional profile hidden Markov Model
عنوان كنفرانس :
يازدهمين كنفرانس آمار ايران
چكيده لاتين :
Profile hidden Markov model (PHMM) is widely used in assigning protein sequences to protein families. In PHAIM, the homologous sequences are assigned to the protein families asing the information of the left side of a residue. In this paper, the information of both left and right sides of a residue in a profile are considered. For this purpose bidirectional profile hidden Markov model (BPHMM) is used. Also, we employ a new method based on spatial statistics on a rectangular lattice for considering the whole information of a site, i.e., left, right, top and bottom sides of residues. We then compare the performance of BPHMM and spatial method by applying them on the real ten top protein profiles from Pfan database. Results show that using the spatial model for sequence assignment increases the number of correctly assigned protein sequences to profiles compared to BPHMM.
شماره مدرك كنفرانس :
4219389
