LAGE: A Java Framework to reconstruct Gene Regulatory Networks from Large-Scale Continues Expression Data

Yang Lu; Mengying Wang; Kenny Q. Zhu; Bo Yuan

LAGE: A Java Framework to reconstruct Gene Regulatory Networks from Large-Scale Continues Expression Data

Machine Learning 2012-11-12 v1 Computational Engineering, Finance, and Science Quantitative Methods Machine Learning

Authors: Yang Lu , Mengying Wang , Kenny Q. Zhu , Bo Yuan

Abstract

LAGE is a systematic framework developed in Java. The motivation of LAGE is to provide a scalable and parallel solution to reconstruct Gene Regulatory Networks (GRNs) from continuous gene expression data for very large amount of genes. The basic idea of our framework is motivated by the philosophy of divideand-conquer. Specifically, LAGE recursively partitions genes into multiple overlapping communities with much smaller sizes, learns intra-community GRNs respectively before merge them altogether. Besides, the complete information of overlapping communities serves as the byproduct, which could be used to mine meaningful functional modules in biological networks.

Cite

@article{arxiv.1211.2073,
  title  = {LAGE: A Java Framework to reconstruct Gene Regulatory Networks from Large-Scale Continues Expression Data},
  author = {Yang Lu and Mengying Wang and Kenny Q. Zhu and Bo Yuan},
  journal= {arXiv preprint arXiv:1211.2073},
  year   = {2012}
}

Comments

2 pages

LAGE: A Java Framework to reconstruct Gene Regulatory Networks from Large-Scale Continues Expression Data

Abstract

Cite

Comments

Related papers