This paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. Since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. These features are the occurrence probabilities of six exchange groups in the seque...

this paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. these features are the occurrence probabilities of six exchange groups in the seque...

the present work was designed to classify and differentiate between the dehalogenase enzyme to non–dehalogenases (other hydrolases) by taking the amino acid propensity at the core, surface and both the parts. the data sets were made on an individual basis by selecting the 3d structures of protein available in the pdb (protein data bank). the prediction of the core amino acid were predicted by i...

conclusions the growth rate of information in bioinformatics databases could facilitate studies of live organisms prior to observation studies. two different protein classes could be causative agents of one disease. however, two related diseases from one disease group could consist of different protein classes. future research in the field of proteomics could allow modern insight to reshuffling...

MOTIVATION The classification of proteins expressed by an organism is an important step in understanding the molecular biology of that organism. Traditionally, this classification has been performed by human experts. Human knowledge can recognise the functional properties that are sufficient to place an individual gene product into a particular protein family group. Automation of this task usua...

The present work was designed to classify and differentiate between the dehalogenase enzyme to non–dehalogenases (other hydrolases) by taking the amino acid propensity at the core, surface and both the parts. The data sets were made on an individual basis by selecting the 3D structures of protein available in the PDB (Protein Data Bank). The prediction of the core amino acid were predicted by I...

Seed proteins of eight species of the genus Suaeda (Chenopodiaceae) were compared by means of polyacrylamide disc gel electrophoresis. Different samples of the same species showed not less than 89% similarities, and geographical separation had no remarkable effect on seed protein patterns of the same species. Morphological heterogenity, that creates difficulties in infrageneric classificat...