Prediction of human protein-protein interaction by a mixed Bayesian model and its application to exploring underlying cancer-related pathway crosstalk.
about
A novel feature extraction scheme with ensemble coding for protein-protein interaction predictionIntegration strategy is a key step in network-based analysis and dramatically affects network topological properties and inferring outcomes.Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasitesAn ensemble approach for large-scale identification of protein- protein interactions using the alignments of multiple sequences.Network-based identification of key proteins involved in apoptosis and cell cycle regulation.Toward Personalized Network Biomarkers in Alzheimer's Disease: Computing Individualized Genomic and Protein Crosstalk Maps.Network-based analysis of genotype-phenotype correlations between different inheritance modes.Naïve Bayes QSDR classification based on spiral-graph Shannon entropies for protein biomarkers in human colon cancer.Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach
P2860
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P2860
Prediction of human protein-protein interaction by a mixed Bayesian model and its application to exploring underlying cancer-related pathway crosstalk.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
2010年论文
@zh
2010年论文
@zh-cn
name
Prediction of human protein-pr ...... cer-related pathway crosstalk.
@en
type
label
Prediction of human protein-pr ...... cer-related pathway crosstalk.
@en
prefLabel
Prediction of human protein-pr ...... cer-related pathway crosstalk.
@en
P2093
P2860
P356
P1476
Prediction of human protein-pr ...... cer-related pathway crosstalk.
@en
P2093
Huizi Duanmu
Shanzhen Zhang
Zhiqiang Chang
P2860
P304
P356
10.1098/RSIF.2010.0384
P577
2010-10-13T00:00:00Z