1) Artificial Intelligence and Machine Learning:

i. Evolutionary Computation (Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Artificial Bee Colony Algorithm, Bees Algorithm, Scatter Search Algorithm, etc.).

ii. Learning Systems (Support Vector Machines, Neural Networks, Kernel Methods, Random Forests).

iii. Modelling (Flux Balance Analysis, Minimization of Metabolic Adjustment, Flux Variability Analysis).

iv. Reasoning (Bayesian Networks, Dynamics Bayesian Networks, Decision Networks, Boolean Networks).

2) Bioinformatics and Computational Biology:

i. Cancer Bioinformatics (Gene Expression, Pathways Analysis, Gene Networks, Biomarkers).

ii. In Silico Metabolic Engineering (Parameter Estimation, Metabolic Pathways, Regulatory Process, Biotechnology Production, Kinetic Model).

iii. Computational Genomics & Proteomics (Gene Regulatory Networks, Protein Structures).

3) Industrial Revolution 4.0:

i. Policy and Framework (Teaching & Learning, Research and Services)

ii. Big Data Analytics (Predictive Analytics).

iii. Data Science (Cleansing, Preparation and Analysis).