# chemometrics

> science of extracting information from chemical systems by data-driven means

**Wikidata**: [Q910067](https://www.wikidata.org/wiki/Q910067)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Chemometrics)  
**Source**: https://4ort.xyz/entity/chemometrics

## Summary
Chemometrics is the science of extracting information from chemical systems using data-driven means. It is closely related to machine learning and involves the use of statistical models and algorithms to analyze chemical data without explicit instructions. The field is integral to quantitative predictions in pharmaceutical and biological contexts.

## Key Facts
- **Definition:** Chemometrics is the science of extracting information from chemical systems by data-driven means.
- **Parent Classification:** It is categorized under **machine learning**, specifically the scientific study of algorithms and statistical models used to perform tasks without explicit instructions.
- **Related Fields:** It encompasses **quantitative structure-activity relationship** (QSAR), which focuses on the quantitative prediction of biological, ecotoxicological, or pharmaceutical activity of a molecule.
- **Associated Field:** It includes **proteochemometrics**, a related field of research.
- **Notable Researcher:** **Steven D. Brown** (born 1950) is recognized as an American chemistry professor and chemometrics researcher.
- **Identifiers:** The field is indexed under the Dewey Decimal Classification **543.015195** and the Library of Congress Subject Headings **sh2005000482**.
- **MeSH Code:** It is assigned the MeSH Tree Number **E05.196.168** among others.

## FAQs
### Q: What is the primary definition of chemometrics?
A: Chemometrics is defined as the science of extracting information from chemical systems by data-driven means. It bridges the gap between chemical data analysis and statistical modeling.

### Q: How does chemometrics relate to machine learning?
A: Chemometrics is considered a part or application of machine learning. It utilizes the algorithms and statistical models central to machine learning to interpret chemical system data.

### Q: What kind of predictions can chemometrics be used for?
A: Through related methodologies like Quantitative Structure-Activity Relationship (QSAR), chemometrics is used for the quantitative prediction of the biological, ecotoxicological, or pharmaceutical activity of molecules.

## Why It Matters
Chemometrics plays a critical role in modern chemistry by transforming raw chemical data into actionable insights. By applying data-driven means—specifically algorithms and statistical models associated with machine learning—it allows researchers to decipher complex chemical systems that would otherwise be intractable.

Its significance is particularly notable in the pharmaceutical and toxicological sectors. Through sub-disciplines like Quantitative Structure-Activity Relationship (QSAR), chemometrics enables the prediction of how molecules will behave biologically or ecotoxicologically. This predictive power is essential for drug discovery and safety assessment, reducing the need for extensive physical testing. Furthermore, the field's evolution into specialized areas like proteochemometrics highlights its ongoing relevance in expanding the understanding of chemical and biological interactions.

## Notable For
- **Data-Driven Approach:** Distinguishes itself by specifically targeting the extraction of information from chemical systems using statistical and computational methods rather than traditional theoretical chemistry alone.
- **Machine Learning Integration:** It is explicitly classified as a part of machine learning, applying algorithms to chemical problems.
- **Predictive Capabilities:** It is the foundation for predicting pharmaceutical and biological activities (via QSAR).
- **Standardization:** It is a recognized scientific discipline with established identifiers in major library and medical classification systems (e.g., MeSH, LoC, Dewey Decimal).

## Body
### Scientific Definition and Scope
Chemometrics is formally defined as the science of extracting information from chemical systems by data-driven means. It is an interdisciplinary field that overlaps significantly with statistical analysis and computer science.

### Relationship to Machine Learning and QSAR
The field is structurally linked to **machine learning**, defined as the scientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions. Within its scope, it includes **quantitative structure-activity relationship** (QSAR), a method used for the quantitative prediction of the biological, ecotoxicological, or pharmaceutical activity of a molecule. Additionally, **proteochemometrics** is identified as a related field of research.

### Key Researchers
- **Steven D. Brown:** An American chemistry professor and chemometrics researcher, born in 1950.
- **Vishal Sharma:** A researcher and physicist (ORCID 0000-0002-5130-1626) associated with the field.

### Classification and Identifiers
Chemometrics is recognized globally across various knowledge bases and classification systems:
- **Library of Congress (LCCN):** sh2005000482
- **Dewey Decimal:** 543.015195
- **MeSH (Medical Subject Headings):** D000090022 (Tree numbers: E05.196.168, E05.318.740.244, N06.850.505.300)
- **GND (German National Library):** 4299578-4
- **BnF (Bibliothèque nationale de France):** 12327087z
- **Aliases:** Also known as *Chemometrie*, *Хемометрия*, and *Херометрия*.

## Schema Markup
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{
  "@context": "https://schema.org",
  "@type": "Thing",
  "name": "Chemometrics",
  "description": "Science of extracting information from chemical systems by data-driven means.",
  "sameAs": [
    "https://en.wikipedia.org/wiki/Chemometrics"
  ],
  "additionalType": "Scientific Discipline"
}

## References

1. Integrated Authority File
2. [Nuovo soggettario](https://thes.bncf.firenze.sbn.it/termine.php?id=69834)
3. Freebase Data Dumps. 2013
4. [Registros de autoridad de "Materia" de la Biblioteca Nacional de España. Spain open data portal](https://www.bne.es/media/datosgob/catalogo-autoridades/materia/materia-UTF8.zip)
5. BabelNet
6. UMLS 2023
7. Quora
8. National Library of Israel Names and Subjects Authority File
9. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)