Dae-hyun Baek
Seoul National University · Biochemistry, Genetics and Molecular Biology
About the Lab
Professor Dae-hyun Baek's research lab specializes in molecular and systems biology, focusing on post-transcriptional gene regulation in mammalian cells. Key research directions include the identification and functional characterization of microRNAs and their regulatory networks, alternative splicing and promoter usage in gene expression regulation, and the role of RNA-binding proteins in modulating miRNA targeting efficiency. The lab also investigates viral-host interactions, particularly the translational dynamics of SARS-CoV-2, to uncover host-virus molecular interplay. These studies integrate high-throughput sequencing, bioinformatics, and functional genomics to decode complex regulatory mechanisms in development, disease, and infection.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15MicroRNAs (miRNAs) are small regulatory RNAs that derive from distinctive hairpin transcripts. To learn more about the miRNAs of mammals, we sequenced 60 million small RNAs from mouse brain, ovary, testes, embryonic stem cells, three embryonic stages, and whole newborns. Analysis of these sequences confirmed 398 annotated miRNA genes and identified 108 novel miRNA genes. More than 150 previously annotated miRNAs and hundreds of candidates failed to yield sequenced RNAs with miRNA-like features.
RB1 mutations can be used as a prognostic molecular biomarker for resectable hepatocellular carcinoma. Further study is required to investigate the potential role of FGF19 amplification in driving hepatocarcinogenesis in patients with liver cirrhosis and to investigate the potential of anti-FGF19 treatment in these patients.
Studies of expressed sequence tag data sets have revealed large numbers of splicing variants for human genes, but it remains challenging to distinguish functionally important variants from aberrant splicing, clarify the nature of the alternative functions, and understand the signals that regulate splicing choices. To help address these issues, we have constructed and analyzed a large data set of 1,478 exon-skipping alternative splicing (AS) variants evolutionarily conserved in human and mouse. I
Recent studies suggest that surprisingly many mammalian genes have alternative promoters (APs); however, their biological roles, and the characteristics that distinguish them from single promoters (SPs), remain poorly understood. We constructed a large data set of evolutionarily conserved promoters, and used it to identify sequence features, functional associations, and expression patterns that differ by promoter type. The four promoter categories CpG-rich APs, CpG-poor APs, CpG-rich SPs, and Cp
COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which infected >200 million people resulting in >4 million deaths. However, temporal landscape of the SARS-CoV-2 translatome and its impact on the human genome remain unexplored. Here, we report a high-resolution atlas of the translatome and transcriptome of SARS-CoV-2 for various time points after infecting human cells. Intriguingly, substantial amount of SARS-CoV-2 translation initiates at a novel translation i
Argonaute is the primary mediator of metazoan miRNA targeting (MT). Among the currently identified >1,500 human RNA-binding proteins (RBPs), there are only a handful of RBPs known to enhance MT and several others reported to suppress MT, leaving the global impact of RBPs on MT elusive. In this study, we have systematically analyzed transcriptome-wide binding sites for 150 human RBPs and evaluated the quantitative effect of individual RBPs on MT efficacy. In contrast to previous studies, we show
Despite efforts to interrogate human genome variation through large-scale databases, systematic preference toward populations of Caucasian descendants has resulted in unintended reduction of power in studying non-Caucasians. Here we report a compilation of coding variants from 1,055 healthy Korean individuals (KOVA; Korean Variant Archive). The samples were sequenced to a mean depth of 75x, yielding 101 singleton variants per individual. Population genetics analysis demonstrates that the Korean
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In
MicroRNAs (miRNAs) play cardinal roles in regulating biological pathways and processes, resulting in significant physiological effects. To understand the complex regulatory network of miRNAs, previous studies have utilized massivescale datasets of miRNA targeting and attempted to computationally predict the functional targets of miRNAs. Many miRNA target prediction tools have been developed and are widely used by scientists from various fields of biology and medicine. Most of these tools conside
본 연구는 통일편익과 비용 인식이 통일의식에 미치는 영향을 분석하는 것을 목적으로 한다. 이를 위해 문화체육관광부가 조사한 “2013 한국인 의식・가치관 조사” 데이터를 활용하였다. 먼저 통일편익 및 비용 인식과 통일의식 간의 상관성을 분석하기 위해 x²검정을 한 결과, 통일편익 및 비용 인식에 따라 통일의식에 유의미한 차이가 있었다. 다음으로 통일의식에 대한 서열로짓분석의 결과를 보면, 통일편익 인식의 경우 통일의식에 유의미한 긍정적 영향을 미쳤는데, 인도적 문제해결을 기준으로 경제적 부강이 통일의식에 가장 큰 영향을 미쳤으며, 그 다음으로 국제사회에서의 영향력 확대, 전쟁위험의 소멸 순이었다. 반면 통일비용 인식의 경우 통일의식에 부정적인 영향을 미쳤는데, 경제적 부담이 통일의식에 가장 부정적인 영향을 미쳤다.
PURPOSE: To better understand the complete genomic architecture of lung adenocarcinoma. EXPERIMENTAL DESIGN: We used array experiments to determine copy number variations and sequenced the complete exomes of the 247 lung adenocarcinoma tumor samples along with matched normal cells obtained from the same patients. Fully annotated clinical data were also available, providing an unprecedented opportunity to assess the impact of genomic alterations on clinical outcomes. RESULTS: We discovered that g
Research Areas
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