# Loop modeling
**Wikidata**: [Q6675846](https://www.wikidata.org/wiki/Q6675846)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Loop_modeling)  
**Source**: https://4ort.xyz/entity/loop-modeling

## Summary
Loop modeling is a topic classified as a subclass of protein structure prediction. It is presented as a distinct Wikipedia entry and is part of the broader field concerned with constructing an atomic-resolution model of a protein from its amino acid sequence.

## Key Facts
- Loop modeling is classified as a subclass of protein structure prediction.
- Protein structure prediction is defined here as constructing an atomic-resolution model of a protein from its amino acid sequence.
- The Wikipedia title for this topic is "Loop modeling."
- The Loop modeling Wikipedia entry exists in English (wikipedia_languages: en).
- The Loop modeling topic has a sitelink_count of 1.
- The parent class protein structure prediction has a sitelink_count of 19.
- Freebase identifier for Loop modeling: /m/027mjfk.
- Microsoft Academic ID (discontinued) for Loop modeling: 45475804.

## FAQs
### Q: What is Loop modeling?
A: Loop modeling is a topic categorized under protein structure prediction. It is represented by a Wikipedia entry titled "Loop modeling."

### Q: How is Loop modeling related to protein structure prediction?
A: Loop modeling is a subclass of protein structure prediction, which is the process of constructing an atomic-resolution model of a protein from its amino acid sequence.

### Q: Where can I find the Loop modeling entry online?
A: The topic has a Wikipedia entry under the title "Loop modeling" (English). It is indexed with identifiers including Freebase /m/027mjfk and Microsoft Academic ID 45475804 (discontinued).

## Why It Matters
Loop modeling is part of the broader field of protein structure prediction, which aims to convert amino acid sequences into atomic-resolution models of proteins. As a subclass within this field, Loop modeling represents a focused topic in the scientific and informational ecosystem surrounding protein modeling. Its presence as a distinct Wikipedia entry and its indexed identifiers (Freebase and Microsoft Academic) indicate that it has been recognized and cataloged for reference and research. For anyone researching protein structure prediction, knowing the classifications and available entries helps locate curated information and cross-reference identifiers across databases. The explicit linkage to protein structure prediction provides a clear contextual anchor: loop modeling belongs to the set of approaches and topics that contribute to understanding and representing protein structures from sequence data.

## Notable For
- Being explicitly classified as a subclass of protein structure prediction.
- Having a dedicated Wikipedia title: "Loop modeling."
- Having a Freebase identifier: /m/027mjfk.
- Having a Microsoft Academic identifier (discontinued): 45475804.
- Presence in English-language Wikipedia (wikipedia_languages: en) with a sitelink_count of 1.

## Body
### Classification
- Entity name: Loop modeling.
- Subclass of: protein structure prediction.
- Parent definition: protein structure prediction is constructing an atomic-resolution model of a protein from its amino acid sequence.

### Identifiers
- Freebase ID: /m/027mjfk.
- Microsoft Academic ID (discontinued): 45475804.
- Wikipedia title: Loop modeling.
- Wikipedia languages recorded: en.

### Linkage and indexing
- Loop modeling sitelink_count: 1.
- Parent class (protein structure prediction) sitelink_count: 19.
- The topic is indexed in reference systems that include Freebase and Microsoft Academic (the latter now discontinued).

### Representation
- The topic is represented in Wikipedia under the English title "Loop modeling."
- It is cataloged as a distinct topic within the taxonomy of protein structure prediction.

### Source constraints
- All facts above are derived from the provided structured properties and the parent-class definition supplied in the source material.

## References

1. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)