Systems Biology and Machine Learning Lab

시스템생물학 머신러닝 실험실

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시스템생물학 머신러닝 실험실

시스템 생물학 및 머신러닝 실험실은 시스템 생물학과 머신러닝 기법을 이용해 산업용 균주와 병원성 미생물을 포함한 다양한 박테리아에 대해 연구합니다. 차세대염기서열분석법(NGS)를 이용한 실험과 컴퓨터 계산을 이용한 in silico 시뮬레이션을 이용해 박테리아의 유전체와 전사체를 연구하고, 대량의 데이터의 복잡도를 낮추기 위해 머신러닝 기법을 적용하고 있습니다. 최근에는, 박테리아에 서 영역을 확대해 더 복잡한 생명체와 무기화학물질에 머신러닝 기법을 적용하는 시도를 하고 있습니다.
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.

Major research field

시스템생물학, 머신러닝, 대사공학

Desired field of research

시스템생물학, 머신러닝, 대사공학

Research Keywords and Topics

• Transcriptional regulation of industrial and pathogenic bacteria
• Characterization of high-value bacterial strains
• Anti-microbial resistance
• Machine learning approaches for bio/chemical information

Research Publications
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• Proceedings of the National Academy of Sciences of the United States of America / Functional cooperation of the glycine synthase-reductase and Wood-Ljungdahl pathways for autotrophic growth of Clostridium drakei / Song, Yoseb; Lee, Jin Soo; Shin, Jongoh; Lee, Gyu Min; Jin, Sangrak; Kang, Seulgi; Lee, Jung-Kul; Kim, Dong Rip; Lee, Eun Yeol; Kim, Sun Chang; Cho, Suhyung; Kim, Donghyuk; Cho, Byung￾Kwan / 2020-03
• METABOLIC ENGINEERING / Genome-scale evaluation of core one-carbon metabolism in gammaproteobacterial methanotrophs grown on methane and methanol / Nguyen, Anh Duc; Park, Joon Young; Hwang, In Yeub; Hamilton, Richard; Kalyuzhnaya, Marina G.; Kim, Donghyuk; Lee, Eun Yeol / 2020-01
• NUCLEIC ACIDS RESEARCH / Systematic discovery of uncharacterized transcription factors in Escherichia coli K-12 MG1655 / Gao, Ye; Yurkovich, James T.; Seo, Sang Woo; Kabimoldayev, Ilyas; Draeger, Andreas; Cho, Byung-Kwan; Kim, Donghyuk; Palsson, Bernhard O. / 2018-11

국가과학기술표준분류

  • EC. 화공
  • EC04. 생물화학공정기술
  • EC0402. 대사공학기술

국가기술지도분류

  • 건강한 생명사회 지향
  • 021900. 생체정보분석/활용 기술

녹색기술분류

  • 녹색기술관련 과제 아님
  • 녹색기술관련 과제 아님
  • 999. 녹색기술 관련과제 아님

6T분류

  • BT 분야
  • 기초/기반기술
  • 020111. 유전체기반 기술