Systems Biology
Academic (University) preparation with worked examples, written practice and independent learning assessments.
Independent university-level study of Systems Biology. This original curriculum draws on public academic subject descriptions; it is not an official faculty syllabus, university credit, accreditation or an Ivy League qualification. Topics covered: Network representations; Model abstraction; Data integration; Identifiability. Biochemical kinetics; Mass-action models; Steady states; Parameter estimation. Feedback motifs; Feedforward loops; Ultrasensitivity; Adaptation. Gene circuits; Oscillations; Bistability; Stochastic expression. Metabolic networks; Stoichiometric matrices; Flux balance; Constraint-based inference. Signaling networks; Crosstalk; Robustness; Sensitivity analysis. Single-cell variation; Population models; Experimental perturbations; Model discrimination. Optimal experiment design; Uncertainty quantification; Prediction validation; Systems modeling project. Projects use safe simulations, public datasets or textual analysis; specialist subject review is required. Includes lessons, supplementary YouTube tutorials, practical exercises, quizzes and free/paid practice tests. Erudex is independent, not affiliated with the source institution or awarding body. Its 80% learning checks are not official grades or university credit. Content requires qualified subject review before use as a complete teaching programme.
Curriculum
One complete track with its own final exam and certificate.
Independent university-level study of Systems Biology. This original curriculum draws on public academic subject descriptions; it is not an official faculty syllabus, university credit, accreditation or an Ivy League qualification. Topics covered: Network representations; Model abstraction; Data integration; Identifiability. Biochemical kinetics; Mass-action models; Steady states; Parameter estimation. Feedback motifs; Feedforward loops; Ultrasensitivity; Adaptation. Gene circuits; Oscillations; Bistability; Stochastic expression. Metabolic networks; Stoichiometric matrices; Flux balance; Constraint-based inference. Signaling networks; Crosstalk; Robustness; Sensitivity analysis. Single-cell variation; Population models; Experimental perturbations; Model discrimination. Optimal experiment design; Uncertainty quantification; Prediction validation; Systems modeling project. Projects use safe simulations, public datasets or textual analysis; specialist subject review is required.
Network representations; Model abstraction; Data integration; Identifiability
- Biochemical Kinetics, Network Topology, and System Identifiability Lab60 min
- Dynamic Motifs, Nonlinear Gene Circuits, and Stochasticity Lab60 min
- Constraint-Based Metabolic Reconstruction and Signal Transduction Sensitivity Lab60 min
- Single-Cell Heterogeneity, Experimental Design, and Model Discrimination Lab60 min