# ABT 780: Bioinformatic Inquiry | UW–Madison

[View on UW Courses](https://uwcourses.com/courses/ABT_780)

## Dataset

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

### repository

twangodev/uwcourses

### schema version

6

### importer version

7

### projection id

52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07

### observed at

2026-09-07T15:55:43.033547+00:00

### built at

2026-09-10T19:50:42.743001+00:00

### courses

8951

### current instructors

5754

### limited

false

### terms

* 1272
* 1264
* 1262
* 1254
* 1252
* 1244
* 1242
* 1234
* 1232
* 1224
* 1222
* 1212
* 1204
* 1202
* 1194
* 1192
* 1184
* 1182
* 1174
* 1172
* 1164
* 1162
* 1154
* 1152
* 1144
* 1142
* 1134
* 1132
* 1124
* 1122
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* 1102
* 1094
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* 1074
* 1072

### term

1272

### departments

| subject   | count |
| --------- | ----- |
| AAE       | 90    |
| ABT       | 20    |
| ACCTIS    | 36    |
| ACTSCI    | 14    |
| AFAERO    | 10    |
| AFRICAN   | 87    |
| AFROAMER  | 71    |
| AGROECOL  | 21    |
| AMERIND   | 53    |
| ANAT\&PHY | 7     |
| ANATOMY   | 2     |
| ANESTHES  | 8     |
| ANSCI     | 57    |
| ANTHRO    | 95    |
| ART       | 125   |
| ARTED     | 10    |
| ARTHIST   | 121   |
| ASIALANG  | 129   |
| ASIAN     | 109   |
| ASIANAM   | 28    |
| ASTRON    | 38    |
| ATMOCN    | 69    |
| BIOCHEM   | 51    |
| BIOCORE   | 10    |
| BIOLOGY   | 14    |
| BIOMDSCI  | 18    |
| BME       | 66    |
| BMI       | 41    |
| BMOLCHEM  | 10    |
| BOTANY    | 69    |
| BSE       | 44    |
| C\&ESOC   | 73    |
| CBE       | 48    |
| CHEM      | 101   |
| CHICLA    | 52    |
| CIVENGR   | 133   |
| CLASSICS  | 47    |
| CNP       | 10    |
| CNSRSCI   | 50    |
| COMARTS   | 137   |
| COMPBIO   | 15    |
| COMPLIT   | 11    |
| COMPSCI   | 138   |
| COUNPSY   | 78    |
| CRB       | 19    |
| CS\&D     | 71    |
| CSCS      | 40    |
| CURRIC    | 193   |
| DANCE     | 93    |
| DERM      | 8     |
| DS        | 88    |
| DYSCI     | 35    |
| ECE       | 155   |
| ECON      | 145   |
| EDPOL     | 114   |
| EDPSYCH   | 97    |
| ELPA      | 70    |
| EMA       | 53    |
| EMERMED   | 17    |
| ENGL      | 206   |
| ENTOM     | 40    |
| ENVIRST   | 148   |
| EP        | 15    |
| EPD       | 67    |
| ESL       | 16    |
| F\&WECOL  | 60    |
| FAMMED    | 22    |
| FINANCE   | 50    |
| FOLKLORE  | 40    |
| FOODSCI   | 43    |
| FRENCH    | 63    |
| GEN\&WS   | 145   |
| GENBUS    | 72    |
| GENECSLR  | 17    |
| GENETICS  | 60    |
| GEOG      | 113   |
| GEOSCI    | 83    |
| GERMAN    | 82    |
| GLE       | 48    |
| GNS       | 38    |
| GREEK     | 27    |
| HDFS      | 41    |
| HEBR-BIB  | 13    |
| HEBR-MOD  | 10    |
| HISTORY   | 233   |
| HISTSCI   | 56    |
| HONCOL    | 13    |
| ILS       | 43    |
| INFOSYS   | 9     |
| INTEGART  | 7     |
| INTEGSCI  | 22    |
| INTER-AG  | 18    |
| INTER-HE  | 11    |
| INTER-LS  | 22    |
| INTEREGR  | 16    |
| INTLBUS   | 21    |
| INTLST    | 50    |
| ISYE      | 83    |
| ITALIAN   | 53    |
| JEWISH    | 56    |
| JOURN     | 88    |
| KINES     | 128   |
| LACIS     | 26    |
| LANDARC   | 61    |
| LATIN     | 24    |
| LAW       | 120   |
| LEGALST   | 48    |
| LINGUIS   | 35    |
| LIS       | 89    |
| LITTRANS  | 78    |
| LSC       | 52    |
| M\&ENVTOX | 7     |
| MARKETNG  | 62    |
| MATH      | 153   |
| MDGENET   | 8     |
| ME        | 130   |
| MEDHIST   | 43    |
| MEDICINE  | 60    |
| MEDIEVAL  | 32    |
| MEDPHYS   | 39    |
| MEDSC-M   | 29    |
| MEDSC-V   | 41    |
| MHR       | 68    |
| MICROBIO  | 45    |
| MILSCI    | 16    |
| MM\&I     | 22    |
| MOLBIOL   | 6     |
| MS\&E     | 59    |
| MUSIC     | 165   |
| MUSPERF   | 126   |
| NAVSCI    | 20    |
| NE        | 44    |
| NEURODPT  | 11    |
| NEUROL    | 7     |
| NEURSURG  | 4     |
| NTP       | 11    |
| NURSING   | 111   |
| NUTRSCI   | 65    |
| OBS\&GYN  | 18    |
| OCCTHER   | 39    |
| ONCOLOGY  | 14    |
| OPHTHALM  | 5     |
| OTM       | 43    |
| PATH      | 34    |
| PATH-BIO  | 29    |
| PEDIAT    | 26    |
| PHARMACY  | 31    |
| PHILOS    | 77    |
| PHMCOL-M  | 11    |
| PHMPRAC   | 45    |
| PHMSCI    | 60    |
| PHYASST   | 37    |
| PHYSICS   | 88    |
| PHYSIOL   | 3     |
| PHYTHER   | 37    |
| PLANTSCI  | 52    |
| PLPATH    | 35    |
| POLISCI   | 192   |
| POPHLTH   | 58    |
| PORTUG    | 33    |
| PSYCH     | 101   |
| PSYCHIAT  | 22    |
| PUBAFFR   | 54    |
| PUBLHLTH  | 23    |
| RADIOL    | 11    |
| REALEST   | 41    |
| RELIGST   | 90    |
| RHABMED   | 9     |
| RMI       | 24    |
| RP\&SE    | 102   |
| S\&APHM   | 17    |
| SCANDST   | 73    |
| SLAVIC    | 89    |
| SOC       | 149   |
| SOCWORK   | 87    |
| SOILSCI   | 46    |
| SPANISH   | 83    |
| SRMED     | 21    |
| STAT      | 94    |
| STDYABRD  | 52    |
| STS       | 8     |
| SURGERY   | 25    |
| SURGSCI   | 33    |
| THEATRE   | 91    |
| URBRPL    | 60    |
| UROLOGY   | 5     |
| ZOOLOGY   | 89    |

## course

### run id

20260907T155543-ce3781c4

### semester

1272

### observed at

2026-09-07 15:55:43.033547+00:00

### record version id

5b065a832e56eee971b62028cf20327d2d90c5439f4d5c009938e5cf7f2508e3

### course id

ABT 780

### course uid

course\_f8fc8b01310ae7bdc82031ba

### catalog version id

19c386aff2c0ba4ec778d4fc8cbd9986df6b6c1559b85ffc12f660f48915efae

### course number

780

### subjects

* ABT

### title

BIOINFORMATIC INQUIRY

### description

Advances the development of competencies promoting efficient analysis of biological data. Emphasizes matching a research problem with the most effective tools for its completion, balancing use of existing software and de novo software development. Advanced aspects of Python and R, algorithmics, machine learning, simulations, and effective communication of results are emphasized.

### requirements text

ABT 720and730

### credit offering ids

None recorded.

### llm job id

enrich-8b774950c2b6adfdc46d1b82

### llm output id

79e17fc1c441862c2eda9b2cce859a68f7c93a8474bbcd4dbcabd89666c9f7a7

### llm model

nvidia/Qwen3.6-35B-A3B-NVFP4

### llm model revision

1355db6a052410cfd62085d94b58866fd0f2c3c5

### llm task version

14

### llm search status

valid

### llm summary

ABT 780 Bioinformatic Inquiry advances competencies for efficient biological data analysis using Python, R, and machine learning.

### llm topics

* Python and R, algorithmics, machine learning, simulations, and communication of results.

### llm skills

* Tool selection, software development, algorithmics, machine learning, and result communication.

### llm assumed background

* Foundational knowledge in biostatistics, experimental design, and Python-based bioinformatics.

### llm search phrases

* bioinformatics analysis tools
* biological data Python R
* algorithmics machine learning biology
* bioinformatic inquiry advanced

### llm requirements status

valid

### llm student summary status

valid

### llm experience status

insufficient\_evidence

### catalog variants

None recorded.

### student summary

#### context hash

895dc37a8bc6a204edaa02c360643edd06e115817183572019c68ac23027bfbb

#### course id

ABT 780

#### current instructors

None recorded.

#### difficulty workload

None recorded.

#### errors

None recorded.

#### historical context

None recorded.

#### message

No course-specific reviews available

#### offered

false

#### profile hash

672f506f2fc2f46a071b9777f4a92cc197b2ccdeef25590e9285146d8c7e7f90

#### quick take

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

```json
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        "source": "madgrades"
      },
      "table": "grades_latest",
      "term_id": "1224",
      "type": "grade"
    }
  ]
}
```

#### student experience

None recorded.

#### task hash

74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68

#### teaching history

None recorded.

#### term id

1272

#### term name

2026 Fall

#### version

2

### requirements

#### nodes

```json
[
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    "evidence": "ABT 720and730",
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    "kind": "all"
  },
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      "minimum_grade": null,
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      "timing": "prior"
    },
    "evidence": "730",
    "id": "n2",
    "kind": "course"
  }
]
```

#### notes

* The requirements text 'ABT 720and730' appears to be a concatenation of two course codes. Parsed as a conjunction (AND) of ABT 720 and ABT 730 based on the linked\_courses list.

#### root

n0

#### status

parsed

### instructors

None recorded.

### offerings

None recorded.

### sections

None recorded.

### grade instructors

```json
[
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    "source": "madgrades",
    "source_instructor_id": "948165",
    "identity_basis": "source_id",
    "identity_status": "source_identified",
    "name": "NATALIE BETZ",
    "email": null,
    "first_observed_at": "2026-09-06 23:14:58.172943+00:00",
    "last_observed_at": "2026-09-07 15:55:43.033547+00:00",
    "grade_statistics": {
      "gpa": 3.745,
      "graded": 1840,
      "counts": [
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      "sections": 184
    },
    "instructor_url": "/instructors/NATALIE_BETZ--instructor_6d21bc07da00876f9cee3356"
  }
]
```

### grades

```json
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    "term_id": "1224",
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      "Natalie Betz"
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  {
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    "course_id": "ABT 780",
    "course_uid": "course_f8fc8b01310ae7bdc82031ba",
    "term_id": "1264",
    "term_name": "Spring 2026",
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      "Natalie Betz"
    ],
    "a": 0,
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    "source_aliases": [
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]
```

### statistics

#### gpa

4

#### graded

1

#### counts

* 1
* 0
* 0
* 0
* 0
* 0
* 0

### grade conflicts

None recorded.

### evidence

#### history

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_f8fc8b01310ae7bdc82031ba-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_f8fc8b01310ae7bdc82031ba-0.json)

#### traces

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_f8fc8b01310ae7bdc82031ba-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_f8fc8b01310ae7bdc82031ba-0.json)

#### results

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_f8fc8b01310ae7bdc82031ba-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_f8fc8b01310ae7bdc82031ba-0.json)

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

## instructor Trends

```json
[
  {
    "uid": "instructor_6d21bc07da00876f9cee3356",
    "name": "NATALIE BETZ",
    "count": 1,
    "terms": [
      {
        "term": "1224",
        "count": 1,
        "sections": 1,
        "gpa": 4
      }
    ]
  }
]
```

## following

None recorded.