Lecture notes. Written from the material of MIT 8.591J 2004, licensed CC BY-NC-SA 4.0. These are notes, not a transcript: the material has been reorganised and rewritten. This adaptation carries the same licence, and the original is linked above.
4. Molecular vs Systems Biology¶
What this covers¶
What does it mean to study a biological system, rather than a biological molecule? This is an orientation lecture, not a technical one: it assumes only ordinary molecular biology — genes, proteins, the idea that a protein has a function — and sets up the questions the rest of the course exists to answer.
Systems biology as network biology¶
The working definition: systems biology is, to a first approximation, network biology. The goal is a quantitative understanding of the biological function of genetic and biochemical networks, not of their individual parts.
Take a network of input genes — the lecture's example has six, A through F — feeding into some output. Knowing the molecular function of each gene product in detail does not reveal what the whole network's input-output relation does. That needs a systems approach: looking past any one gene or protein to ask what the interactions between them — feedbacks, feedforwards — are for, in the context of the entire network.
Equivalently: systems biology is systems engineering combined with molecular biology, each contributing its own concepts rather than one absorbing the other — the application of systems-engineering ideas to biological systems.
Two questions about the same system¶
The contrast is drawn through one running example, a repressor protein cI. A molecular biologist asks about the molecule: the structure of the cI dimer, the DNA sequence it recognizes, the residues responsible for dimerization, its binding constants, whether the sequence is conserved across evolution.
A systems biologist asks about the same protein differently: what is the functional role of the feedback loop cI sits in, how does that feedback produce a hysteretic switch, what role does noise play in the switch's stability, is the switch's performance robust to small parameter changes or finely tuned, and how do those parameters shift when the module cross-talks with others? These are questions about network architecture, not about the molecule.
Where the course is headed¶
Two stated goals: build the mathematical tools to model network modules — switches, oscillators, filters, amplifiers — and work through recent papers' biological problems that a systems approach can solve, starting with well-stirred systems and moving to diffusion-dominated ones.
Sources¶
- Slides only:
lectures/06-notes.md(MIT OCW 8.591J, Fall 2004, lecture 6) — the network-biology framing, the molecular- vs systems-biology question lists (cI example), and the course goals. - No transcript, written notes, or exercises were supplied for this lecture; nothing beyond the slide content above is recorded. The slide file itself is a model's reconstruction of a PDF with no text layer, so treat exact wording as approximate.
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