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Full-Text Articles in Life Sciences
A New Essential Protein Discovery Method Based On The Integration Of Protein-Protein Interaction And Gene Expression Data, Min Li, Hanhui Zhang, Jian-Xin Wang, Yi Pan
A New Essential Protein Discovery Method Based On The Integration Of Protein-Protein Interaction And Gene Expression Data, Min Li, Hanhui Zhang, Jian-Xin Wang, Yi Pan
Computer Science Faculty Publications
The article offers information on a study conducted on the essential protein discovery method, PeC, which is based on the integration of protein-protein interaction and gene expression data. It states that PeC was developed on the basis of the definitions of edge clustering coefficient (ECC) and Pearson's correlation coefficient (PCC). It mentions that a list of essential proteins of Saccharomyces cerevisiae were collected.
Background: Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have …
Integration Of Breast Cancer Gene Signatures Based On Graph Centrality, Jianxin Wang, Gang Chen, Min Li, Yi Pan
Integration Of Breast Cancer Gene Signatures Based On Graph Centrality, Jianxin Wang, Gang Chen, Min Li, Yi Pan
Computer Science Faculty Publications
Background: Various gene-expression signatures for breast cancer are available for the prediction of clinical outcome. However due to small overlap between different signatures, it is challenging to integrate existing disjoint signatures to provide a unified insight on the association between gene expression and clinical outcome.
Results: In this paper, we propose a method to integrate different breast cancer gene signatures by using graph centrality in a context-constrained protein interaction network (PIN). The context-constrained PIN for breast cancer is built by integrating complete PIN and various gene signatures reported in literatures. Then, we use graph centralities to quantify the importance of …