Year |
Citation |
Score |
2019 |
Liang Y, Kelemen A, Kelemen A. Reproducibility of biomarker identifications from mass spectrometry proteomic data in cancer studies. Statistical Applications in Genetics and Molecular Biology. 18. PMID 31077580 DOI: 10.1515/Sagmb-2018-0039 |
0.3 |
|
2017 |
Liang Y, Kelemen A. Computational dynamic approaches for temporal omics data with applications to systems medicine. Biodata Mining. 10: 20. PMID 28638442 DOI: 10.1186/S13040-017-0140-X |
0.332 |
|
2017 |
Liang Y, Kelemen A. Dynamic modeling and network approaches for omics time course data: overview of computational approaches and applications. Briefings in Bioinformatics. PMID 28430854 DOI: 10.1093/Bib/Bbx036 |
0.359 |
|
2016 |
Liang Y, Kelemen A. Bayesian state space models for dynamic genetic network construction across multiple tissues. Statistical Applications in Genetics and Molecular Biology. PMID 27343475 DOI: 10.1515/Sagmb-2014-0055 |
0.357 |
|
2011 |
Liang Y, Kelemen A. Sequential Support Vector Regression with Embedded Entropy for SNP Selection and Disease Classification. Statistical Analysis and Data Mining. 4: 301-312. PMID 21666834 DOI: 10.1002/Sam.10110 |
0.319 |
|
2009 |
Liang Y, Kelemen A. Bayesian finite Markov mixture model for temporal multi-tissue polygenic patterns. Biometrical Journal. Biometrische Zeitschrift. 51: 56-69. PMID 19197952 DOI: 10.1002/Bimj.200710489 |
0.358 |
|
2008 |
Liang Y, Kelemen A. Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration. Bmc Bioinformatics. 9: 354. PMID 18755028 DOI: 10.1186/1471-2105-9-354 |
0.315 |
|
2008 |
Liang Y, Kelemen A. Statistical advances and challenges for analyzing correlated high dimensional SNP data in genomic study for complex diseases Statistics Surveys. 2: 43-60. DOI: 10.1214/07-Ss026 |
0.337 |
|
2007 |
Liang Y, Kelemen A. Bayesian state space models for inferring and predicting temporal gene expression profiles. Biometrical Journal. Biometrische Zeitschrift. 49: 801-14. PMID 17638289 DOI: 10.1002/Bimj.200610335 |
0.334 |
|
2007 |
Liang Y, Kelemen A, Tayo B. Model-based or algorithm-based? Statistical evidence for diabetes and treatments using gene expression. Statistical Methods in Medical Research. 16: 139-53. PMID 17484297 DOI: 10.1177/0962280206071927 |
0.327 |
|
2006 |
Liang Y, Kelemen A. Associating phenotypes with molecular events: recent statistical advances and challenges underpinning microarray experiments. Functional & Integrative Genomics. 6: 1-13. PMID 16292543 DOI: 10.1007/S10142-005-0006-Z |
0.368 |
|
2005 |
Liang Y, Kelemen A. Temporal gene expression classification with regularised neural network. International Journal of Bioinformatics Research and Applications. 1: 399-413. PMID 18048144 DOI: 10.1504/Ijbra.2005.008443 |
0.352 |
|
2005 |
Liang Y, Tayo B, Cai X, Kelemen A. Differential and trajectory methods for time course gene expression data. Bioinformatics (Oxford, England). 21: 3009-16. PMID 15886280 DOI: 10.1093/Bioinformatics/Bti465 |
0.345 |
|
2004 |
Liang Y, Kelemen AG. Hierarchical Bayesian neural network for gene expression temporal patterns. Statistical Applications in Genetics and Molecular Biology. 3: Article20. PMID 16646799 DOI: 10.2202/1544-6115.1038 |
0.349 |
|
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