Molecular + cell biology¶
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Prerequisites
Module 2; Module 4; Wave 1 dynamics/probability -
Exit capability
Model cells as chemical, energetic, informational and mechanical systems; understand membranes, metabolism, signaling, division and gene expression. -
Unlocks / transfers to
Gene editing; cultured tissue; artificial organs; bioreactors; longevity; biosensors; engineered microbes; synthetic food.
Weeks¶
Week 32¶
Spine: OpenStax Biology 2e
Reading: Ch. 4 cell structure + Ch. 5 membranes and transport
Know: Understand compartments, membranes, transport, electrochemical gradients and organelle functions.
Reconstruct: Reconstruct diffusion/osmosis/active-transport driving forces and membrane area/volume scaling.
Do: Model nutrient/oxygen diffusion into a cell/tissue sphere and identify size limits without vasculature.
Defend: Why does surface-area-to-volume scaling constrain artificial tissue?
Gate: Pass: transport limitation predicted before simulation and tied to geometry.
Source: source
Week 33¶
Spine: OpenStax Biology 2e
Reading: Ch. 6 metabolism + Ch. 7 cellular respiration + Ch. 8 photosynthesis
Know: Track biological energy, redox carriers, ATP and metabolic pathways as controlled reaction networks.
Reconstruct: Derive ATP/free-energy coupling and proton-gradient/chemiosmosis logic.
Do: Create stoichiometric energy/redox balance for a simplified microbial bioreactor or photosynthetic system.
Defend: How is metabolism simultaneously chemistry, thermodynamics and control?
Gate: Pass: carbon/electron/energy balances close.
Source: source
Week 34¶
Spine: OpenStax Biology 2e
Reading: Ch. 9 cell communication + Ch. 10 cell cycle/division
Know: Understand receptors, signaling cascades, feedback, proliferation checkpoints and cell-state transitions.
Reconstruct: Draw a signaling feedback loop and derive simple Hill-function response; reconstruct cell-cycle checkpoint logic.
Do: Simulate a bistable cell-fate switch and test sensitivity to signaling noise.
Defend: Why can the same signal cause different outcomes in different cells?
Gate: Pass: mechanism includes receptor/state/context, not signal name alone.
Source: source
Week 35¶
Spine: OpenStax Biology 2e
Reading: Ch. 14 DNA replication/repair + Ch. 15 transcription/translation
Know: Understand information storage, replication fidelity, transcription, translation and mutation sources.
Reconstruct: Reconstruct central dogma with directionality/enzymes and simple error-rate compounding.
Do: Model information fidelity across replication and protein expression; calculate mutation/error burden across many generations.
Defend: Where does biological 'error correction' occur and where is error intentionally retained?
Gate: Pass: distinguish DNA mutation, transcription error and translation error consequences.
Source: source
Week 36¶
Spine: OpenStax Biology 2e
Reading: Ch. 16 gene regulation + Ch. 17 biotechnology/genomics
Know: Understand gene regulation, PCR/sequencing/editing concepts, biotechnology workflows and measurement limitations.
Reconstruct: Reconstruct lac-style regulatory logic and PCR amplification scaling.
Do: Design a non-clinical synthetic gene-circuit experiment in simulation: sensor -> regulator -> reporter with controls and failure modes.
Defend: Why is successful editing not equivalent to safe/functional phenotype?
Gate: Module defense: biological intervention -> mechanism -> measurement -> controls -> off-target/selection risks.
Source: source
Exit gate¶
Closed-book: 120 min: membrane transport, energy/redox, signaling, cell cycle, DNA replication/expression/regulation.
Novel problem: Model a cell/tissue/bioreactor intervention and specify what measurements establish function rather than mere presence.
Artifact: Transport/metabolic/gene-circuit simulation with controls.
Defend: Defend mechanism, cell-state context, measurement, off-target/selection and scaling limits.
Pass criterion: Pass if mass/energy/information balances and control logic are mutually consistent.
Transfer problems¶
Try these before consulting solutions or asking for the complete answer.
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Membrane: Predict direction of water/solute movement across a selective membrane.
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Transport: Estimate maximum viable tissue thickness from diffusion/consumption.
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Metabolism: Balance carbon/electrons/ATP in a simplified pathway.
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Chemiosmosis: Explain how a proton gradient couples transport to ATP synthesis.
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Signaling: Model receptor-response saturation and feedback.
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Cell cycle: Map a checkpoint failure to uncontrolled proliferation risk.
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Replication: Estimate mutation burden after many replications given error/repair rates.
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Expression: Translate a DNA sequence toy example into RNA/protein and identify possible regulation points.
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Gene regulation: Model inducible expression with Hill function and leakiness.
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Biotech assay: Design positive/negative/process controls for a gene-editing measurement without performing real editing.
Textbooks¶
See the five-book resource page.