Module #1 Introduction to Systems Biology Overview of systems biology, its importance, and applications
Module #2 Systems Thinking in Biology Understanding complex biological systems, thinking systemically, and the role of computational approaches
Module #3 Case Studies in Systems Biology Real-world examples of systems biology in action, including gene regulation, metabolism, and signal transduction
Module #4 Biological Data Types and Sources Types of biological data, including omics data, and sources for retrieving and integrating data
Module #5 Computational Tools for Systems Biology Overview of computational tools and platforms for systems biology, including programming languages and software
Module #6 Bioinformatics and Genomics Analysis Methods for analyzing genomic data, including sequence alignment, gene finding, and functional annotation
Module #7 Protein Structure and Function Prediction Methods for predicting protein structure and function from sequence data
Module #8 Network Analysis for Systems Biology Methods for analyzing and modeling biological networks, including graph theory and network metrics
Module #9 Machine Learning for Systems Biology Methods for applying machine learning to systems biology, including supervised and unsupervised learning
Module #10 Dynamical Modeling of Biological Systems Methods for modeling the dynamics of biological systems, including ordinary differential equations (ODEs) and stochastic modeling
Module #11 Systems Biology of Gene Regulation Understanding gene regulation using systems biology approaches, including transcriptional regulation and gene expression
Module #12 Systems Biology of Metabolic Networks Understanding metabolic networks using systems biology approaches, including flux balance analysis and metabolic pathway analysis
Module #13 Systems Biology of Signal Transduction Understanding signal transduction pathways using systems biology approaches, including protein-protein interactions and signaling cascades
Module #14 Systems Biology of Diseases Understanding diseases using systems biology approaches, including cancer, diabetes, and infectious diseases
Module #15 Systems Biology for Synthetic Biology Designing and constructing new biological systems using systems biology approaches
Module #16 Single-Cell Analysis and Systems Biology Analyzing single-cell data using systems biology approaches
Module #17 Multi-Omics Data Integration Integrating multiple types of omics data using systems biology approaches
Module #18 Machine Learning for Systems Biology Imaging Applying machine learning to imaging data in systems biology
Module #19 Systems Biology for Personalized Medicine Applying systems biology approaches to personalized medicine and precision health
Module #20 Ethical and Societal Implications of Systems Biology Considering the ethical and societal implications of systems biology research and applications
Module #21 Project Development 1:Problem Definition Defining a systems biology problem and developing a research question
Module #22 Project Development 2:Data Retrieval and Integration Retrieving and integrating data for systems biology analysis
Module #23 Project Development 3:Computational Modeling and Analysis Applying computational methods to systems biology data
Module #24 Project Development 4:Model Validation and Interpretation Validating and interpreting systems biology models
Module #25 Project Development 5:Presentation and Communication Presenting and communicating systems biology research results
Module #26 Final Project Presentations Student presentations of final projects
Module #27 Course Review and Wrap-Up Reviewing key concepts and wrapping up the course
Module #28 Course Wrap-Up & Conclusion Planning next steps in Systems Biology and Computational Approaches career
