Work

Machine learning and complex biological data

Year: 2019

Type: editorial

Abstract: Machine learning has demonstrated potential in analyzing large, complex biological data. In practice, however, biological information is required in addition to machine learning for successful application.

Source: Genome biology

DOI: 10.1186/s13059-019-1689-0

Authors: Chunming Xu, Scott A. Jackson

Institutions: University of Georgia, Northeast Normal University

Language: English

Topic: Gene expression and cancer classification

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,490

Funders: National Science Foundation, Natural Science Foundation of Jilin Province, National Natural Science Foundation of China

Awards: 新形成异源多倍体小麦减数分裂染色体稳定性快速适应性进化的遗传基础和分子机制, G4210062171, Comparative-, Functional-, and Epi-Genomics of Legumes and Nodule Formation, BREAD ABRDC: Genomic approaches to capture Novel Alleles in cultivated peanut to increase smallholder production.

OpenAlex ID: W2945103729

Cites: 10

Cited by: 381

Related to: 10