A statistical framework for genomic data fusion | Zendy

Gert Lanckriet | Zendy; Tijl De Bie | Zendy; Nello Cristianini | Zendy; Michael I. Jordan | Zendy; William Stafford Noble | Zendy

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A statistical framework for genomic data fusion

Author(s) -

Gert Lanckriet,

Tijl De Bie,

Nello Cristianini,

Michael I. Jordan,

William Stafford Noble

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bth294

Subject(s) - computer science , kernel (algebra) , kernel method , data type , structural genomics , genome , multiple kernel learning , data mining , artificial intelligence , computational biology , support vector machine , machine learning , biology , mathematics , protein structure , gene , genetics , biochemistry , combinatorics , programming language

During the past decade, the new focus on genomics has highlighted a particular challenge: to integrate the different views of the genome that are provided by various types of experimental data.

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