Spring 2027

Bioinformatic Inquiry

Bioinformatic Inquiry advances competencies for analyzing biological data by balancing existing software with de novo development using advanced Python, R, algorithmics, machine learning, and simulations.

offering recorded3 credits
Recorded instructors · Spring 2027 Natalie Betz

Summary

1 / 2

Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=1 letter grades).

What you’ll be able to do

  • Implement successful solutions to tasks in bioinformatics using existing software and newly developed code.

  • Write R scripts and packages, including formulation of new R classes.

  • Create helpful, user-defined classes in Python.

  • Implement knowledge of algorithmics to write elegant solutions to bioinformatics tasks.

  • Interface with a MySQL database in Python.

  • Simulate biological data to use as a null distribution for novel test statistics.

  • Decide when machine learning methods are appropriate to a task in bioinformatics.

  • Use GitHub to effectively share new software and manage version control.

  • Communicate complicated methodology and results to a variety of stakeholders.

Source: UW Guide

Grade history

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average GPA
letter grades
A
AB
B
BC
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All recorded terms · compare terms & instructors

Prerequisites

Course map

ABT 720 and 730

ABT 780

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

Prerequisite text tree

Professors

Spring 2027

Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=1 letter grades).

Historical instructors & teaching patterns

NATALIE BETZ is recorded teaching in Spring 2022, Spring 2023, Spring 2024, Spring 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Online Only0 / 1000

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

No records available.

Student experience

the class

Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=1 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Analysis of biological data
  • Advanced Python, R, algorithmics, machine learning, and simulations
  • Communication of results
  • MySQL database interfacing
  • Version control and software sharing via GitHub

Skills

  • Advanced Python and R programming, algorithmics, machine learning, simulations, and communicating results.
  • Writing R scripts and packages, including formulating new R classes.
  • Creating user-defined classes in Python.
  • Interfacing with MySQL databases in Python.
  • Using GitHub for software sharing and version control.

Grades

Latest available · Spring 2022— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F
More grade details Grade mix, volume & source data

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records
ABT 780 · Spring 2027

Bioinformatic Inquiry

Recorded 2026-10-14
Raw records 
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:160:025975",
    "course_id": "ABT 780",
    "course_uid": "course_f8fc8b01310ae7bdc82031ba",
    "term_id": "1274",
    "source_course_id": "025975",
    "source_subject_id": "160",
    "title": "Bioinformatic Inquiry",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
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Student reviews

Original comments behind the course and instructor summaries.

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "345ef2557c5217ede2646ed8f76930db6762ca51759c0a07df47307162f1ae49",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}