Title :
Inferring transmembrane region counts with hydropathy index/charge two dimensional trajectories of stochastic dynamical systems
Author :
Muramatsu, D. ; Hashimoto, S. ; Tsunashima, T. ; Kaburagi, T. ; Sasaki, M. ; Matsumoto, T.
Author_Institution :
Dept. of Electr. Eng. & Bioscience, Waseda Univ., Tokyo, Japan
Abstract :
A new algorithm is proposed for inferring the number of transmembrane regions of transmembrane proteins from two dimensional vector trajectories consisting of hydropathy index and charge of amino acids by stochastic dynamical system models. The prediction accuracy of a preliminary experiment is 94%. Since no fine-tuning is done, this appears encouraging.
Keywords :
biomembranes; molecular biophysics; proteins; stochastic systems; amino acids; hydropathy charge; hydropathy index; stochastic dynamical systems; transmembrane proteins; transmembrane region counts; vector trajectories; Accuracy; Amino acids; Biomembranes; Data mining; Equations; Feature extraction; Hidden Markov models; Machine learning algorithms; Protein engineering; Stochastic systems;
Conference_Titel :
Neural Networks for Signal Processing, 2003. NNSP'03. 2003 IEEE 13th Workshop on
Print_ISBN :
0-7803-8177-7
DOI :
10.1109/NNSP.2003.1318008
