# Machine Learning in Bioinformatics

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-learning-in-bioinformatics-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 721,969 |
| Description | This cluster of papers focuses on the prediction of protein subcellular localization using various computational methods such as amino acid composition, machine learning algorithms like support vector machines, and the analysis of signal peptides and transmembrane topology. The research aims to improve the accuracy and reliability of predicting the subcellular location of proteins, which has significant implications for understanding protein function and cellular processes. |
| Domain | Life Sciences |
| Field | Biochemistry, Genetics and Molecular Biology |
| OpenAlex ID | https://openalex.org/T12254 |
| Works | 278,514 |

## Topic researchers

Showing 12 of 20.

- [Eric S. Lander](https://scholariq.org/researchers/eric-s-lander/)
- [Yoshua Bengio](https://scholariq.org/researchers/yoshua-bengio/)
- [Rob Knight](https://scholariq.org/researchers/rob-knight/)
- [Richard Durbin](https://scholariq.org/researchers/richard-durbin/)
- [Peer Bork](https://scholariq.org/researchers/peer-bork/)
- [Steven L. Salzberg](https://scholariq.org/researchers/steven-l-salzberg/)
- [Bert Vogelstein](https://scholariq.org/researchers/bert-vogelstein/)
- [Gad Getz](https://scholariq.org/researchers/gad-getz/)
- [Elaine R. Mardis](https://scholariq.org/researchers/elaine-r-mardis/)
- [Jun Wang](https://scholariq.org/researchers/jun-wang-11/)
- [Matthias Mann](https://scholariq.org/researchers/matthias-mann/)
- [Gonçalo R. Abecasis](https://scholariq.org/researchers/goncalo-r-abecasis/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.