TY - GEN
T1 - A Hybrid of Bees Algorithm and Regulatory On/Off Minimization for Optimizing Lactate Production
AU - Yong, Mohd Izzat
AU - Mohamad, Mohd Saberi
AU - Choon, Yee Wen
AU - Chan, Weng Howe
AU - Adli, Hasyiya Karimah
AU - Wsw, Khairul Nizar Syazwan
AU - Yusoff, Nooraini
AU - Remli, Muhammad Akmal
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Metabolic engineering has grown dramatically and is now widely used, particularly in the production of biomass utilising microorganisms. The metabolic network model has been extensively used in computational procedures developed to optimise metabolic production and suggest modifications in organisms. The problem has been the unrealistic flux distribution suggestion demonstrated by previous work on a rational modelling framework employing Optknock and OptGene. To address the issue, a hybrid of the Bees Algorithm and Regulatory On/Off Minimization (BAROOM) is introduced. By using Eschericia coli (E. coli) as the model organism, BAROOM is able to determine the optimal set of gene that can be knocked out and improve lactate production. The results show that BAROOM performs better than other methods in increasing lactate production in model organism by identifying optimal set of genes to be knocked out.
AB - Metabolic engineering has grown dramatically and is now widely used, particularly in the production of biomass utilising microorganisms. The metabolic network model has been extensively used in computational procedures developed to optimise metabolic production and suggest modifications in organisms. The problem has been the unrealistic flux distribution suggestion demonstrated by previous work on a rational modelling framework employing Optknock and OptGene. To address the issue, a hybrid of the Bees Algorithm and Regulatory On/Off Minimization (BAROOM) is introduced. By using Eschericia coli (E. coli) as the model organism, BAROOM is able to determine the optimal set of gene that can be knocked out and improve lactate production. The results show that BAROOM performs better than other methods in increasing lactate production in model organism by identifying optimal set of genes to be knocked out.
KW - Artificial Intelligence
KW - Bioinformatics
KW - Gene knockout
KW - Metabolic engineering
KW - Modelling
KW - OptKnock
KW - Optgene
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=85115215720&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85115215720&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-86258-9_10
DO - 10.1007/978-3-030-86258-9_10
M3 - Conference contribution
AN - SCOPUS:85115215720
SN - 9783030862572
T3 - Lecture Notes in Networks and Systems
SP - 95
EP - 104
BT - Practical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021
A2 - Rocha, Miguel
A2 - Fdez-Riverola, Florentino
A2 - Mohamad, Mohd Saberi
A2 - Casado-Vara, Roberto
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021
Y2 - 6 October 2021 through 8 October 2021
ER -