Introduction to Bioinformatics

Introduction to bioinformatics focusing on algorithms for molecular biology problems.

offering recorded3 credits
Recorded instructors · Fall 2026 Daifeng Wang

Summary

1 / 6

Historical reviews of Colin Dewey: The course features weekly Jupyter notebooks and homework that require significant time investment. Reviews indicate the work is hard but prepares students well for exams, with many assignments providing substantial code scaffolding.

Grade history

average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

(COMP SCI 320 or 400) and MATH 222, graduate/professional standing, or declared in the Capstone Certificate in Computer Sciences for Professionals

    • take all
    • graduate/professional standing
    • declared in the Capstone Certificate in Computer Sciences for Professionals
    take one
BMI/COMPSCI 576

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

Prerequisite text tree
  • Any of

Professors

Fall 2026
Historical instructors & teaching patterns

Daifeng Wang is the current instructor for BMI/COMPSCI 576. Historical reviews for Colin Dewey praise his organization, effort, and clear explanations, though some students find his monotone delivery and tedious homework challenging. Sushmita Roy received criticism for unclear explanations and a difficult midterm.

COLIN DEWEY is recorded teaching in Fall 2008, Fall 2009, Fall 2010, Fall 2015, Fall 2016, Fall 2018, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

SUSHMITA ROY is recorded teaching in Fall 2012, Fall 2013, Fall 2014. 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction17 / 800
LEC 001Classroom Instruction45 / 780

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

Meeting source records

Student experience

the class

Daifeng Wang is the current instructor, but historical reviews for Colin Dewey dominate the course profile. Students describe Dewey's course as well-organized and effort-rewarding, though some find the content difficult or the delivery monotone.

Recent recorded grades — Fall 2023: 3.33 GPA, 65.9% A/AB (n=41 letter grades); Fall 2024: 3.37 GPA, 72.1% A/AB (n=68 letter grades); Fall 2025: 3.18 GPA, 52.6% A/AB (n=57 letter grades).

difficulty & workload

Historical reviews of Colin Dewey: The course features weekly Jupyter notebooks and homework that require significant time investment. Reviews indicate the work is hard but prepares students well for exams, with many assignments providing substantial code scaffolding.

Historical reviews of Colin Dewey: Students appreciate the clear organization and available resources, including office hours and Piazza support. However, some find the pre-recorded lectures monotone and the homework tedious, creating a mixed experience.

Topics

  • Genome sequencing, sequence alignment, phylogenetic trees, and gene-expression analysis.

Skills

  • Algorithms for computational problems in molecular biology.

Grades

Historical instructor

Fall 2026 · Projected

Before grades are released

average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.10 GPA average error.

Grades over time

Through Fall 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Fall 2025 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1320 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

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.

Selected offering source records
BMI/COMPSCI 576 · Fall 2026

Introduction to Bioinformatics

Recorded 2026-09-07
BMI/COMPSCI 576 · Fall 2026

Introduction to Bioinformatics

Recorded 2026-09-07
Raw records
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    "title": "Introduction to Bioinformatics",
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    "title": "Introduction to Bioinformatics",
    "credits_min": 3,
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    "typically_offered": "Fall"
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]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
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  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "1ebad540a1b62caa5f4148cc5698a81d5e6178a561154763c6e8fed4fad74e9d",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}