Fall 2026

Mathematical Methods for Systems Biology

Covers mathematical modeling of biological systems using dynamical systems and differential equations to analyze pathways and bistability.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=19 letter grades); Fall 2023: 4.00 GPA, 100.0% A/AB (n=20 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=16 letter grades).

Grade history

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average GPA
letter grades
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Prerequisites

Course map

MATH 415 and (MATH 320, 340, 341, or 375) or graduate/professional standing or member of the Pre-Masters Mathematics (Visiting International) Program

BIOCHEM/BMI/BMOLCHEM/MATH 609

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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Student experience

the class

Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=19 letter grades); Fall 2023: 4.00 GPA, 100.0% A/AB (n=20 letter grades); Fall 2025: 4.00 GPA, 100.0% A/AB (n=16 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Dynamical systems
  • Differential equations
  • Biological pathways and bistability

Skills

  • Mathematical modeling of biological systems
  • Applying dynamical systems and differential equations
  • Analyzing biological pathways and bistability

Grades

Latest available · Fall 2025— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2025

More grade details Grade mix, volume & source data

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Sources & history

UW–Madison

Catalog & offerings

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Grade history

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Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "b4e91dc21833ca092b08ecb4913c759b1d4cff8d8a84f7adb82cfa436dab2e11",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}