Spectral consensus strategy for accurate reconstruction of large biological networks.

ABSTRACT:

Background

The last decades witnessed an explosion of large-scale biological datasets whose analyses require the continuous development of innovative algorithms. Many of these high-dimensional datasets are related to large biological networks with few or no experimentally proven interactions. A striking example lies in the recent gut bacterial studies that provided researchers with a plethora of information sources. Despite a deeper knowledge of microbiome composition, inferring bacterial interactions remains a critical step that encounters significant issues, due in particular to high-dimensional settings, unknown gut bacterial taxa and unavoidable noise in sparse datasets. Such data type make any a priori choice of a learning method particularly difficult and urge the need for th

SUBMITTER: Affeldt S 

PROVIDER: S-EPMC5249011 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature