What we do
Our group is interested in developing bioinformatics technologies, and practicing evidence-based precision medicine for diseases like cancer.
We utilize machine learning and AI technologies, together with noncoding RNA (ncRNA) centered multi-omics data,
to understand how genetic information is encoded in the structured DNA and RNA sequences,
and how they interact and regulate each other in a biological system.
Ultimately, this will help us understand and cure human diseases, know and improve ourselves.
We have two major research directions based on noncoding RNA (ncRNA): I. Precision Medicine; II. AI-driven Drug Design.
我们致力于发展生物信息学技术，并探索其在癌症等复杂疾病的精准诊疗上的具体实践。我们利用机器学习等人工智能技术，结合 非编码RNA (ncRNA) 为核心的多组学数据，来研究遗传信息是如何被编码在结构化的DNA和RNA分子之中，以及它们是如何在一个生命体系中相互作用、彼此调控。
“上工治未病”，我们的一个重要使命，是帮助人们更早期的发现癌症。 我们相信，这种使命感以及为此付出的实践和努力，将帮助我们理解和治疗人类疾病，并最终认识和提高我们自己。
实验室围绕着 非编码RNA (ncRNA) 主要有两个研究方向: 1.精准医疗；2.AI驱动的药物设计。
Projects
Who we are
We are group of people dedicated to the research of bioinformatics, genomics and systems biology.
We have been committed to bioinformatics research of noncoding RNA for years. Our lab has provided a set of systematic bioinformatics tools for researchers in the field of noncoding RNA (NAR 2015a*; 2015b*; 2016*; 2017a*; 2017b*; 2017c*+, 2018*, 2019*+, 2022*; Genome Biol 2017*；BIB 2019*+) (*：last corresponding author; *+: co-corresponding author). More than 20 intersecting work using this tool have been jointly published (Nature 2012，2014; Cell Stem Cell 2016; Cell 2019；PNAS 2020*+, etc）. Through collaboration with medical experts, we have discovered a set of novel noncoding RNAs (Nature Commun 2017*) and reprogrammed tissue-specific RNAs related to cancer using aforementioned method (Cell Res. 2020*+). Based on these, we have developed non-invasive biomarkers that could be applied to clinical diagnosis of cancer (Clinical Chem. 2019*, Thranositics 2021*，e-Life 2022*+, 6 related patents).
清华大学鲁志实验室一直致力于和非编码RNA相关的生物信息学研究，从非编码RNA的“序列-结构-功能（靶标）”三个层次研发了一套系统性的生物信息学方法 (Nuc. Acides Res. 2015-2022*, Genome Biology 2017*, Briefings in Bioinformatics 2019*)(*:通讯作者)；这套方法得到了很好的认可，被合作者应用和共同发表在多个动植物物种的RNA研究中（Science1 2010; Nature 2012; Nature Biotech. 2012; Nature 2014; Cell Stem Cell 2016; Cell 2019; PNAS 2020*）(*:通讯作者)。尤其是和医学专家合作，发表了和癌症发生迁移相关的新型非编码RNA和表观遗传调控机制，可以用来做癌症诊断和预后辅助的分子标志物（Nature Commun. 2017*, Clinical Chem. 2019*, Cell Res. 2020*; e-Life 2022*）(*:通讯作者)。鲁志博士一共发表重要期刊文章60余篇，总引用近2万次。
Group Members @ Lu Lab
Contact Us
MOE Key Lab of Bioinformatics教育部”生物信息学“重点实验室
Rm 2-110 Biotech. Building, School of Life Sciences
生命科学学院 生物技术馆
Tsinghua University, Beijing 100084, China
清华大学
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