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Biological Systems

Biology as information processing

Chemistry → cells → genetics → evolution → systems biology → neuroscience → information → synthetic biology → health → frontier bio-computation.

10
Modules
50
Lessons
1

Chemistry of Life

Atoms, Bonds, and Thermodynamics

Atoms, bonds and water, the biomolecular classes, the thermodynamics of life, enzymatic catalysis, and reaction networks.

5 lessons
2

Cellular Systems

Structure, Transport, and Signaling

The cell as a computational unit, membrane and transport, compartmentalization, signal transduction, and the cell cycle.

5 lessons
3

Genetic Information

Storage, Code, and Expression

DNA as digital storage, the genetic code, replication and fidelity, transcription and translation, and gene regulation networks.

5 lessons
4

Evolution

Selection, Drift, and Dynamics

Populations as distributions, natural selection, genetic drift, mutation and recombination, and evolutionary dynamics.

5 lessons
5

Systems Biology

Networks, Oscillation, and Robustness

Biological networks, metabolic networks, gene regulatory networks, feedback and oscillation, and robustness and adaptation.

5 lessons
6

Minimal Neuroscience

Neurons, Potentials, and Plasticity

Neurons as computational elements, membrane potential, action potentials, synaptic plasticity, and neural coding.

5 lessons
7

Information & Entropy in Life

Entropy, Mutual Information, and Error Correction

Shannon entropy in biology, mutual information in signaling, the thermodynamic cost of information, error correction in biology, and maximum-entropy principles.

5 lessons
8

Synthetic Biology

Parts, Circuits, and Programmable Editing

Parts abstraction, genetic circuits, logic and computation in cells, CRISPR and programmable editing, and the design-verify-iterate loop.

5 lessons
9

Health as System Stability

Homeostasis, Allostasis, and Failure Modes

Homeostasis, allostasis, disease as dynamical failure, the immune system as a classifier, and aging as information loss.

5 lessons
10

Frontier Bio-Computational Systems

Neural Networks, DNA Computing, and Morphogenesis

Biological neural networks and AI, DNA computing, cellular automata and morphogenesis, bio-inspired optimization, and the open problems.

5 lessons

Guided instruction and research mentorship are offered separately → hbar.work