TY - M-10000
AU - Patel, Krupali
AU - Patel, Pravinbhai
TI - Use Apriori, Genetic Algorithm and Fuzzy Logic to Foretell the Most Common Amino Acid Sequence
T2 - Scientific Research Journal of Science, Engineering and Technology

PY - 2023
VL - 1
IS - 1
SN - 2584-0584

AB - Data mining is the practise of discovering connections between seemingly unrelated pieces of biological information. Rapid progress in genomics and proteomics in recent years has resulted in an abundance of biological data. Thus, categorising biological sequences and structures according to essential properties and functions is a pressing issue in the field of biological data processing. Many methods have been used to generate recurrent patterns from published works for use in a wide range of contexts. The frequency with which this algorithm was produced has diminished. Because of this, it's completely pointless. In this case, I want to use two different methods to compare the common pattern and optimise the data. Hence, we find it to be of great value. The contaminated protein sequence is the root cause of several human illnesses, and our method is designed to extract the amino acids that are both hidden and most dominant in the sequence. We deal with this issue by employing a combination of the apriori algorithm, the genetic algorithm, and strong association rules for pattern prediction. Apply fuzzy logic to the optimisation of data and the identification of intriguing common patterns in the protein sequence database. This Recurring Pattern is quite helpful in the Pharmaceutical Industry.

KW -  Genetic Algorithms
KW - Protein structure analysis
KW -  Association methods
KW -  Fuzzy Systems for mining biological data
DO -