Open AccessFormal concept analysis for amino acids classification and visualization
Author(s) -
Adrian-Sorin Telcian,
Daniela-Maria Cristea,
Ioan Sima
Publication year - 2020
Publication title -
acta universitatis sapientiae. informatica
Language(s) - English
Resource type - Journals
eISSN - 2066-7760
pISSN - 1844-6086
DOI - 10.2478/ausi-2020-0002
Subject(s) - formal concept analysis , visualization , computer science , hasse diagram , data mining , chemistry , theoretical computer science , mathematics , algorithm , discrete mathematics , partially ordered set
Formal concept analysis (FCA) is a method based on lattice theory, widely used for data visualization, data analysis and knowledge discovery. Amino acids (AAs) are chemical molecules that constitute the proteins. In this paper is presented a new and easy way of visualizing of the structure and properties of AAs. In addition, we performed a new Hydrophobic-Polar classification of AAs using FCA. For this, the 20 proteinogenic AAs were clustered, classified by hydrophobicity and visualized in Hasse-diagrams. Exploring and processing the dataset was done with Elba and ToscanaJ, some FCA tools and Conceptual Information System (CIS).