Digital Physics I: Week 2

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Related lectures (31)

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Metabolic Modeling: TFA and Kinetic Models

Explores metabolic modeling using TFA and kinetic models, covering growth simulation, nutrient trade-offs, phenotypic analysis, and metabolomics integration.

Algorithmic Composition: Semester Project Milestones

Covers semester project milestones in Algorithmic Composition, exploring musical concepts, technical tools, and final deliverables.

Parametric Signal Models: Matlab Practice

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Neurophysiological Data Analysis

Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.

Rhythmic Generation Techniques

Covers rhythm generation techniques, including Markov models and hierarchical rhythm generation, with a focus on Nancarrow's Study 14.

Logistic Regression: Vegetation Prediction

Explores logistic regression for predicting vegetation proportions in the Amazon region through remote sensing data analysis.

Python Programming: File Handling and Exceptions

Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.

Harmonic Oscillator: Numerical Stability Analysis

Explores the numerical stability of the harmonic oscillator and the importance of improving digital diagrams.

Gitlab Agent for Kubernetes (`agentk`)

Covers the setup of a Gitlab agent for Kubernetes, focusing on installation, version control, and troubleshooting.

Metabolic Modeling Exercises

Covers exercises on genome-scale metabolic models, including FBA and TFA analysis, as well as modeling kinetics.