Fuzzy Grammar-based Prediction of Amyloidogenic Regions
نویسنده
چکیده
In this paper, we address the problem of predicting the location of amyloidogenic regions in proteins. The language of protein sequence can be described by using a formal system such as fuzzy context-free grammar, and the problem of amyloidogenic region recognition can be replaced by fuzzy grammar induction. The induced fuzzy grammar achieved 70.6% accuracy and 96.7% specificity on a recently published amyloidogenic dataset. Our results are comparable to other methods dedicated to recognize amyloid proteins.
منابع مشابه
FoldAmyloid: a method of prediction of amyloidogenic regions from protein sequence
MOTIVATION Amyloidogenic regions in polypeptide chains are very important because such regions are responsible for amyloid formation and aggregation. It is useful to be able to predict positions of amyloidogenic regions in protein chains. RESULTS Two characteristics (expected probability of hydrogen bonds formation and expected packing density of residues) have been introduced by us to detect...
متن کاملPrediction of Amyloidogenic and Disordered Regions in Protein Chains
The determination of factors that influence protein conformational changes is very important for the identification of potentially amyloidogenic and disordered regions in polypeptide chains. In our work we introduce a new parameter, mean packing density, to detect both amyloidogenic and disordered regions in a protein sequence. It has been shown that regions with strong expected packing density...
متن کاملMotif mining: an assessment and perspective for amyloid fibril prediction tool
Amyloid fibril forming regions in protein sequences are associated with a number of diseases. Experimental evidences compel in favor of the hypothesis that short motif regions are responsible for its amyloidogenic behavior. Thus, identifying these short peptides is critical in understanding the cause of diseases associated with aggregation of proteins and developing sequencetargeted anti-aggreg...
متن کاملA Novel Fuzzy Based Method for Heart Rate Variability Prediction
Abstract In this paper, a novel technique based on fuzzy method is presented for chaotic nonlinear time series prediction. Fuzzy approach with the gradient learning algorithm and methods constitutes the main components of this method. This learning process in this method is similar to conventional gradient descent learning process, except that the input patterns and parameters are stored in mem...
متن کاملNeuro-Fuzzy Based Algorithm for Online Dynamic Voltage Stability Status Prediction Using Wide-Area Phasor Measurements
In this paper, a novel neuro-fuzzy based method combined with a feature selection technique is proposed for online dynamic voltage stability status prediction of power system. This technique uses synchronized phasors measured by phasor measurement units (PMUs) in a wide-area measurement system. In order to minimize the number of neuro-fuzzy inputs, training time and complication of neuro-fuzzy ...
متن کامل