TY - GEN
T1 - DNA Pattern Matching Algorithms within Sorghum bicolor Genome
T2 - 7th International Conference on Informatics and Computational Sciences, ICICoS 2024
AU - Yonia, Dwika Lovitasari
AU - Hidayati, Shintami Chusnul
AU - Sarno, Riyanarto
AU - Septiyanto, Abdullah Faqih
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Sorghum bicolor, a vital cereal crop with significant roles in agriculture and biofuel production, presents a complex genome that poses substantial challenges for genetic analysis and improvement. This study provides a comprehensive comparison of DNA pattern-matching algorithms applied to the Sorghum bicolor genome, focusing on the accuracy, efficiency, and effectiveness of each technique. The algorithms evaluated include the simple Brute Force method, the efficient BoyerMoore algorithm, the linear-time Knuth-Morris-Pratt (KMP) algorithm, the Enhanced First-Last Pattern Matching (EFLPM), and the Enhanced Processor-Aware Pattern Matching (EPAPM). Notably, the EFLPM and EPAPM algorithms excel at accommodating errors and mutations in DNA sequences, with EPAPM additionally leveraging parallel processing techniques to enhance performance. This comparative study highlights the crucial role of temporal complexity in selecting the most suitable DNA pattern-matching algorithm for genomic analysis.
AB - Sorghum bicolor, a vital cereal crop with significant roles in agriculture and biofuel production, presents a complex genome that poses substantial challenges for genetic analysis and improvement. This study provides a comprehensive comparison of DNA pattern-matching algorithms applied to the Sorghum bicolor genome, focusing on the accuracy, efficiency, and effectiveness of each technique. The algorithms evaluated include the simple Brute Force method, the efficient BoyerMoore algorithm, the linear-time Knuth-Morris-Pratt (KMP) algorithm, the Enhanced First-Last Pattern Matching (EFLPM), and the Enhanced Processor-Aware Pattern Matching (EPAPM). Notably, the EFLPM and EPAPM algorithms excel at accommodating errors and mutations in DNA sequences, with EPAPM additionally leveraging parallel processing techniques to enhance performance. This comparative study highlights the crucial role of temporal complexity in selecting the most suitable DNA pattern-matching algorithm for genomic analysis.
KW - Sorghum bicolor genome
KW - agricultural technology
KW - bioinformatics
KW - pattern matching
UR - http://www.scopus.com/inward/record.url?scp=85202795523&partnerID=8YFLogxK
U2 - 10.1109/ICICoS62600.2024.10636821
DO - 10.1109/ICICoS62600.2024.10636821
M3 - Conference contribution
AN - SCOPUS:85202795523
T3 - Proceedings - International Conference on Informatics and Computational Sciences
SP - 36
EP - 41
BT - 2024 7th International Conference on Informatics and Computational Sciences, ICICoS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 July 2024 through 18 July 2024
ER -