Park M - Search Results

1

Multi-block Analysis of Genomic Data Using Generalized Canonical Correlation Analysis.

Jun I, Choi W, Park M. Jun I, et al. Among authors: park m. Genomics Inform. 2018 Dec;16(4):e33. doi: 10.5808/GI.2018.16.4.e33. Epub 2018 Dec 28. Genomics Inform. 2018. PMID: 30602094 Free PMC article.

2

Genetic Association Analysis of Fasting and 1- and 2-Hour Glucose Tolerance Test Data Using a Generalized Index of Dissimilarity Measure for the Korean Population.

Yee J, Kim Y, Park T, Park M. Yee J, et al. Among authors: park t, park m. Genomics Inform. 2016 Dec;14(4):181-186. doi: 10.5808/GI.2016.14.4.181. Epub 2016 Dec 30. Genomics Inform. 2016. PMID: 28154509 Free PMC article.

3

Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation.

Yee J, Park T, Park M. Yee J, et al. Among authors: park t, park m. Genomics Inform. 2022 Jun;20(2):e17. doi: 10.5808/gi.22033. Epub 2022 Jun 30. Genomics Inform. 2022. PMID: 35794697 Free PMC article.

4

MP-LASSO chart: a multi-level polar chart for visualizing group LASSO analysis of genomic data.

Song M, Lee M, Park T, Park M. Song M, et al. Among authors: park t, park m. Genomics Inform. 2022 Dec;20(4):e48. doi: 10.5808/gi.22075. Epub 2022 Dec 30. Genomics Inform. 2022. PMID: 36617655 Free PMC article.

5

Using the Generalized Index of Dissimilarity to Detect Gene-Gene Interactions in Multi-Class Phenotypes.

Yee J, Kim Y, Park T, Park M. Yee J, et al. Among authors: park t, park m. PLoS One. 2016 Aug 24;11(8):e0158668. doi: 10.1371/journal.pone.0158668. eCollection 2016. PLoS One. 2016. PMID: 27556585 Free PMC article.

6

Multivariate Cluster-Based Multifactor Dimensionality Reduction to Identify Genetic Interactions for Multiple Quantitative Phenotypes.

Kim H, Jeong HB, Jung HY, Park T, Park M. Kim H, et al. Among authors: park t, park m. Biomed Res Int. 2019 Jul 11;2019:4578983. doi: 10.1155/2019/4578983. eCollection 2019. Biomed Res Int. 2019. PMID: 31380425 Free PMC article.

7

Integrative Analysis of Multi-Omics Data Based on Blockwise Sparse Principal Components.

Park M, Kim D, Moon K, Park T. Park M, et al. Among authors: park t. Int J Mol Sci. 2020 Nov 2;21(21):8202. doi: 10.3390/ijms21218202. Int J Mol Sci. 2020. PMID: 33147797 Free PMC article.

8

Investigation of gene-gene interactions of clock genes for chronotype in a healthy Korean population.

Park M, Kim SA, Shin J, Joo EJ. Park M, et al. Genomics Inform. 2020 Dec;18(4):e38. doi: 10.5808/GI.2020.18.4.e38. Epub 2020 Dec 9. Genomics Inform. 2020. PMID: 33412754 Free PMC article.

9

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Lee M, Park T, Shin JY, Park M. Lee M, et al. Among authors: park t, park m. Sci Rep. 2024 Aug 1;14(1):17851. doi: 10.1038/s41598-024-68541-1. Sci Rep. 2024. PMID: 39090161 Free PMC article.

10

Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population.

Shin JE, Shin N, Park T, Park M. Shin JE, et al. Among authors: park t, park m. Sci Rep. 2024 Aug 31;14(1):20283. doi: 10.1038/s41598-024-71217-5. Sci Rep. 2024. PMID: 39217223 Free PMC article.

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