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Kim, Donghyuk (김동혁)

Department
School of Energy and Chemical Engineering(에너지화학공학과)
Website
https://sites.google.com/view/systemskimlab
Lab
Systems Biology and Machine Learning Lab. (시스템생물학 머신러닝 실험실)
Research Keywords
시스템생물학, 머신러닝, 대사공학, 차세대염기서열분석법, Systems Biology, Machine Learning, Metabolic engineering, NGS
Research Interests
The research areas of Systems Biology and Machine Learning Lab are primarily based on the systems biology and machine learning approaches and their applications to study - Transcriptional regulation of bacterial pathogens including Salmonella and E. coli- Characterization of high-value bacterial strains- Anti-microbial resistance- Machine learning approaches for biological information
We have been applying the systems biology approaches to study bacteria, but there are also collaborators who expect us to apply those approaches to other types of organisms including yeast, fungi, and human cells.
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Issue DateTitleAuthor(s)TypeViewAltmetrics
2023-11A deep learning-based framework for battery reusability verification: one-step state-of-health estimation of pack and constituent modules using a generative algorithm and graphical representationPark, Seojoung; Lim, Dongjun; Lee, Hyunjun, et alARTICLE85 A deep learning-based framework for battery reusability verification: one-step state-of-health estimation of pack and constituent modules using a generative algorithm and graphical representation
2023-07Comparative Genomic Analysis and BTEX Degradation Pathways of a Thermotolerant Cupriavidus cauae PHS1Sathesh-Prabu, Chandran; Woo, Jihoon; Kim, Yuchan, et alARTICLE101 Comparative Genomic Analysis and BTEX Degradation Pathways of a Thermotolerant Cupriavidus cauae PHS1
2023-05Design of synthetic promoters for cyanobacteria with generative deep-learning modelSeo, Euijin; Choi, Yun-Nam; Shin, Ye Rim, et alARTICLE210 Design of synthetic promoters for cyanobacteria with generative deep-learning model
2023-04Deep-learning based spatio-temporal generative model on assessing state-of-health for Li-ion batteries with partially-cycled profilesPark, Seojoung; Lee, Hyunjun; Scott-Nevros, Zoe K. K., et alARTICLE631 Deep-learning based spatio-temporal generative model on assessing state-of-health for Li-ion batteries with partially-cycled profiles
2023-03Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak callingBang, Ina; Lee, Sang-Mok; Park, Seojoung, et alARTICLE290 Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling
2023-02Revealing Causes for False-Positive and False-Negative Calling of Gene Essentiality in Escherichia coli Using Transposon Insertion SequencingChoe, Donghui; Kim, Uigi; Hwang, Soonkyu, et alARTICLE353 Revealing Causes for False-Positive and False-Negative Calling of Gene Essentiality in Escherichia coli Using Transposon Insertion Sequencing
2023-01A Machine Learning Approach Reveals a Microbiota Signature for Infection with Mycobacterium avium subsp. paratuberculosis in CattleLee, Sang-Mok; Park, Hong-Tae; Park, Seojoung, et alARTICLE159 A Machine Learning Approach Reveals a Microbiota Signature for Infection with Mycobacterium avium subsp. paratuberculosis in Cattle
2023-01ChEAP: ChIP-exo analysis pipeline and the investigation of Escherichia coli RpoN protein-DNA interactionsBang, Ina; Nong, Linh Khanh; Park, Joon Young, et alARTICLE229 ChEAP: ChIP-exo analysis pipeline and the investigation of Escherichia coli RpoN protein-DNA interactions
2023-01Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichia coliPark, Joon Young; Lee, Sang-Mok; Ebrahim, Ali, et alARTICLE159 Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichia coli
2023-01Characterization of Klebsiella pneumoniae bacteriophages, KP1 and KP12, with deep learning-based structure predictionKim, Youngju; Lee, Sang-Mok; Nong, Linh Khanh, et alARTICLE199 Characterization of Klebsiella pneumoniae bacteriophages, KP1 and KP12, with deep learning-based structure prediction
2022-11Characterization of an Entner-Doudoroff pathway-activated Escherichia coliKim, Ye Eun; Cho, Kyung Hyun; Bang, Ina, et alARTICLE93 Characterization of an Entner-Doudoroff pathway-activated Escherichia coli
2022-09Delineating transcriptional crosstalk between Mycobacterium avium subsp. paratuberculosis and human THP-1 cells at the early stage of infection via dual RNA-seq analysisPark, Hong-Tae; Lee, Sang-Mok; Ko, Seyoung, et alARTICLE224 Delineating transcriptional crosstalk between Mycobacterium avium subsp. paratuberculosis and human THP-1 cells at the early stage of infection via dual RNA-seq analysis
2022-09Pan-genome Analysis Reveals Comparative Genomic Features of Central Metabolic Pathways in Methylorubrum extorquensLee, Gyu Min; Scott-, NevrosZoe K.; Lee, Sang-Mok, et alARTICLE263 Pan-genome Analysis Reveals Comparative Genomic Features of Central Metabolic Pathways in Methylorubrum extorquens
2022-03Enhanced production of nonanedioic acid from nonanoic acid by engineered Escherichia coliLee, Yongjoo; Sathesh-Prabu, Chandran; Kwak, Geun Hwa, et alARTICLE508 Enhanced production of nonanedioic acid from nonanoic acid by engineered Escherichia coli
2022-01proChIPdb: a chromatin immunoprecipitation database for prokaryotic organismsDecker, Katherine T.; Gao, Ye; Rychel, Kevin, et alARTICLE451 proChIPdb: a chromatin immunoprecipitation database for prokaryotic organisms
2022-01Comparative genomic analysis of plasmids encoding metallo-beta-lactamase NDM-5 in Enterobacterales Korean isolates from companion dogsKyung, Su Min; Choi, Sung-Woon; Lim, Jaewon, et alARTICLE545 Comparative genomic analysis of plasmids encoding metallo-beta-lactamase NDM-5 in Enterobacterales Korean isolates from companion dogs
2021-09Rapid Real-Time Polymerase Chain Reaction for Salmonella Serotyping Based on Novel Unique Gene Markers by Pangenome AnalysisYang, Seung-Min; Kim, Eiseul; Kim, Dayoung, et alARTICLE396 Rapid Real-Time Polymerase Chain Reaction for Salmonella Serotyping Based on Novel Unique Gene Markers by Pangenome Analysis
2021-03Genomic diversity of Mycobacterium avium subsp. paratuberculosis: pangenomic approach for highlighting unique genomic features with newly constructed complete genomesLim, Jaewon; Park, Hong-Tae; Ko, Seyoung, et alARTICLE412 Genomic diversity of Mycobacterium avium subsp. paratuberculosis: pangenomic approach for highlighting unique genomic features with newly constructed complete genomes
2021-03Alpha-2-Macroglobulin as a New Promising Biomarker Improving the Diagnostic Sensitivity of Bovine ParatuberculosisPark, Hyun-Eui; Park, Jin-Sik; Park, Hong-Tae, et alARTICLE563 Alpha-2-Macroglobulin as a New Promising Biomarker Improving the Diagnostic Sensitivity of Bovine Paratuberculosis
2021-01Development of a Genoserotyping Method for Salmonella Infantis Detection on the Basis of Pangenome AnalysisYang, Seung-Min; Baek, Jiwon; Kim, Eiseul, et alARTICLE400 Development of a Genoserotyping Method for Salmonella Infantis Detection on the Basis of Pangenome Analysis

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