Identification of cancer fusion drivers using network fusion centrality.
about
Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical researchDiscovering and understanding oncogenic gene fusions through data intensive computational approachesChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer.Gene expression in rat models for inter-generational transmission of islet dysfunction and obesity.RWCFusion: identifying phenotype-specific cancer driver gene fusions based on fusion pair random walk scoring method.RNA-seq Based Transcription Characterization of Fusion Breakpoints as a Potential Estimator for Its Oncogenic Potential.TumorFusions: an integrative resource for cancer-associated transcript fusions.Kinase impact assessment in the landscape of fusion genes that retain kinase domains: a pan-cancer study.Synstable Fusion: A Network-Based Algorithm for Estimating Driver Genes in Fusion Structures
P2860
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P2860
Identification of cancer fusion drivers using network fusion centrality.
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
Identification of cancer fusion drivers using network fusion centrality.
@en
type
label
Identification of cancer fusion drivers using network fusion centrality.
@en
prefLabel
Identification of cancer fusion drivers using network fusion centrality.
@en
P2093
P2860
P356
P1433
P1476
Identification of cancer fusion drivers using network fusion centrality
@en
P2093
Aleksandar Milosavljevic
Kalpana Kannan
Laising Yen
Steven Lin
P2860
P304
P356
10.1093/BIOINFORMATICS/BTT131
P407
P50
P577
2013-03-16T00:00:00Z