Genome Lab

게놈랩

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게놈램은 게놈과 생정보학 연구를 주로 합니다. 게놈랩은 코직(KOGIC)에 속한 랩입니다. 주요 연구 분야는 한국인 특이적 게놈 분석과 생정보학 기술(다중오믹스 분석, 표준게놈구축 등)의 활용을 통한 모든 종류의 질병과 노화 극복입니다. 2021년 현재 인간표준게놈의 구축과 질병·노화 관련 바이오마커를 연구하여, 정밀의료 구현을 하는데 기여하려 합니다. 그 외에도 각종 동식물게놈(고래상어, 호랑이, 고래) 등 다양한 종들의 표준게놈을 구축합니다. 생명현상을 이해하고, 조절하고, 상용화하는 모든 영역에 걸친 연구를 합니다. 실험실에서 데이터도 생산하고, 컴퓨터를 통해, 정보분석을 합니다.
Genome lab performs research on genomes using bioinformatics. Genome Lab is a part of KOGIC. KOGIC is focused on the research and development on all kinds of diseases and aging (Geromics). Wet lab experiments and data production accompanied by bioinformatics technologies are also included. Broadly, we perform multi-omics analysis. We build various reference and standard in genomics. Our lab’s final goal is curing aging using omics technologies.

Major research field

Bioinformatics, Genomics, Geromics (Aging), Reference Genomes, Korean Genome Project, Genomics, Multi-Oomics, Diseaseomics, Variomics, Sequencer, Bio

Desired field of research

Anyone who has any bioscience background is welcome to join our lab. Computer science, Medicine, Psychology, and Engineering school graduates are also very welcome. We are interested in solvoing problems in the field of Biological Aging, Precision Medicine, Diseaseomics, Population genomics, Humonomics (Omics + Human behaviour), Sequencing life.

Research Keywords and Topics

한국표준게놈, 생정보학, 게놈, 유전체학, 체학, 변이체, 게놈프로젝트, 바이오 빅데이터, 바이러스, 감염체, 바이오마커
Korean Standard Genome, Bioinformatics, Genomics, Omics, Variomics, Genome Project, Bio Big data, Infectomics, Biomarker

Research Publications
MORE

· Korean Genome Project: 1094 Korean personal genomes with clinical information. Science Advances. 2020
· The Origin and Composition of Korean Ethnicity Analyzed by Ancient and Present-Day Genome Sequences. Genome Biology and Evolution. 2020
· Depression and Suicide Risk Prediction Models Using Blood-Derived Multi-Omics Data. Transl Psychiatry. 2019

Patents

· Method for screening makers for predicting depressive disorder or suicide risk using machine learning, markers for predicting depressive disorder or suicide risk, method for predicting depressive disorder or suicide risk, Semin Lee, Jong Bhak, Youngjune bhak, et al. 2020.06.11
· Method for disease and phenotype risk score calculation, Yoonsung Cho, Jaehoon Jeon, Jong Bhak, et al. 2020.03.31.

국가과학기술표준분류

  • LA. 생명과학
  • LA02. 유전학·유전공학
  • LA0204. 유전체학

국가기술지도분류

  • 건강한 생명사회 지향
  • 021900. 생체정보분석/활용 기술

녹색기술분류

  • 예측기술

6T분류

  • BT 분야
  • 기초/기반기술
  • 020113. 생물정보학 기술