MPINet: Metabolite Pathway Identification via Coupling of Global Metabolite Network Structure and Metabolomic Profile
High-throughput metabolomics technology, such as gas chromatography mass spectrometry, allows the analysis of hundreds of metabolites. Understanding that these metabolites dominate the study condition from biological pathway perspective is still a significant challenge. Pathway identification is an...
Main Authors: | Li, Feng, Xu, Yanjun, Shang, Desi, Yang, Haixiu, Liu, Wei, Han, Junwei, Sun, Zeguo, Yao, Qianlan, Zhang, Chunlong, Ma, Jiquan, Su, Fei, Feng, Li, Shi, Xinrui, Zhang, Yunpeng, Li, Jing, Gu, Qi, Li, Xia, Li, Chunquan |
---|---|
Format: | Online |
Language: | English |
Published: |
Hindawi Publishing Corporation
2014
|
Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4095715/ |
Similar Items
-
Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network
by: Yao, Qianlan, et al.
Published: (2015) -
Prioritizing Candidate Disease Metabolites Based on Global Functional Relationships between Metabolites in the Context of Metabolic Pathways
by: Shang, Desi, et al.
Published: (2014) -
Subpathway-GMir: identifying miRNA-mediated metabolic subpathways by integrating condition-specific genes, microRNAs, and pathway topologies
by: Feng, Li, et al.
Published: (2015) -
ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis
by: Han, Junwei, et al.
Published: (2015) -
Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways
by: Li, Chunquan, et al.
Published: (2013)