Kim S - Search Results

1

Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection.

Tamada Y, Kim S, Bannai H, Imoto S, Tashiro K, Kuhara S, Miyano S. Tamada Y, et al. Among authors: kim s. Bioinformatics. 2003 Oct;19 Suppl 2:ii227-36. doi: 10.1093/bioinformatics/btg1082. Bioinformatics. 2003. PMID: 14534194

2

Inferring gene networks from time series microarray data using dynamic Bayesian networks.

Kim SY, Imoto S, Miyano S. Kim SY, et al. Brief Bioinform. 2003 Sep;4(3):228-35. doi: 10.1093/bib/4.3.228. Brief Bioinform. 2003. PMID: 14582517

3

Dynamic Bayesian network and nonparametric regression for nonlinear modeling of gene networks from time series gene expression data.

Kim S, Imoto S, Miyano S. Kim S, et al. Biosystems. 2004 Jul;75(1-3):57-65. doi: 10.1016/j.biosystems.2004.03.004. Biosystems. 2004. PMID: 15245804

4

Use of gene networks for identifying and validating drug targets.

Imoto S, Savoie CJ, Aburatani S, Kim S, Tashiro K, Kuhara S, Miyano S. Imoto S, et al. Among authors: kim s. J Bioinform Comput Biol. 2003 Oct;1(3):459-74. doi: 10.1142/s0219720003000290. J Bioinform Comput Biol. 2003. PMID: 15290765

5

Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network.

Imoto S, Kim S, Goto T, Miyano S, Aburatani S, Tashiro K, Kuhara S. Imoto S, et al. Among authors: kim s. J Bioinform Comput Biol. 2003 Jul;1(2):231-52. doi: 10.1142/s0219720003000071. J Bioinform Comput Biol. 2003. PMID: 15290771

6

Comparison of clinical characteristics and outcomes in candidaemia patients with and without COVID-19: a multicentre retrospective study.

Shin SU, Bae S, Cho D, Lee A, Jeong HS, Hwang S, Kim S, Kim M, Kim SE, Kim UJ, Kang SJ, Park KH, Chang HH, Jung SI. Shin SU, et al. Among authors: kim se, kim s. BMC Infect Dis. 2024 Dec 28;24(1):1473. doi: 10.1186/s12879-024-10373-5. BMC Infect Dis. 2024. PMID: 39732640

7

Cognitive and neurodegenerative trajectories of subjective cognitive decline according to baseline biomarkers: Results of the CoSCo study.

Hong YJ, Choi SH, Kim S, Jeong JH, Park KH, Wang MJ, Kang S, Yang DW; CoSCo study group. Hong YJ, et al. Among authors: kim s. Alzheimers Dement. 2024 Dec 28. doi: 10.1002/alz.14473. Online ahead of print. Alzheimers Dement. 2024. PMID: 39732514

8

Enhancing predictive accuracy for antidepressant response in depressive disorders: The additive value of interleukin-1β and interleukin-6 alongside hsCRP.

Kim JM, Kang HJ, Kim JW, Jhon M, Lee JY, Kim SW, Shin IS. Kim JM, et al. Among authors: kim sw. J Affect Disord. 2024 Dec 26:S0165-0327(24)02078-0. doi: 10.1016/j.jad.2024.12.091. Online ahead of print. J Affect Disord. 2024. PMID: 39732400

9

Enhancing toxicity prediction for natural products in herbal medicine and dietary supplements: Integrating (Q)STR models and in vitro assays.

Shin HK, Park SM, Choi MS, Oh JH, Kim SK, Yoon S, Park HR, Han HY. Shin HK, et al. Among authors: kim sk. Toxicol Appl Pharmacol. 2024 Dec 26:117220. doi: 10.1016/j.taap.2024.117220. Online ahead of print. Toxicol Appl Pharmacol. 2024. PMID: 39732204

10

Characterization of fusidic acid-resistant Staphylococcus aureus isolated from food animals during 2010-2021 in South Korea.

Kim SJ, Ali MS, Kang HS, Moon BY, Hwang YJ, Yoon SS, Park SC, Lim SK. Kim SJ, et al. Int J Food Microbiol. 2024 Dec 19;430:111026. doi: 10.1016/j.ijfoodmicro.2024.111026. Online ahead of print. Int J Food Microbiol. 2024. PMID: 39731987

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