Computational and Integrative Biology Group

Bioinformatics is an interdisciplinary that combines biology, computer science, and information technology to analyze and interpret biological data. It involves the development and application of computational methods, algorithms, and software tools to understand biological processes, analyze large datasets, and make predictions about biological systems.
Bioinformatics plays a crucial role in many areas of biological research, including genomics, proteomics, structural biology, evolutionary biology, and systems biology. It is used to analyze DNA sequences, protein sequences, gene expression data, protein structures, and biological networks. Bioinformatics tools and techniques enable researchers to identify genes, predict protein functions, study genetic variations, analyze evolutionary relationships, and much more. We aim to explore:

  • Data-driven research in development, ageing and evolution biology;
  • Machine learning methodology and its applications in biomedicine;
  • Developing and maintaining bioinformatics database and software;
  • AI and drug discovery.
  • Learn More

    Ongoing Projects

    Research Summary

    Clustering in single-cell RNA-sequencing

    As one of the core steps of single-cell transcriptome data analysis, clustering plays a crucial role in identifying cell types and interpreting cellular heterogeneity. We summarize applications and challenges of the clustering ensemble method in single-cell transcriptome data analysis, and provide constructive thoughts and references for researchers. (Nie X., et al. Computers in Biology and Medicine, 2023).

    Read more

    Additives and Toxicological Mechanisms

    Additives have the potential to affect the survival and lifespan of insects, but the full molecular mechanisms behind mortality and infertility remain unclear. By integrating molecular biology and multi-omics approaches, we focuses on uncovering the potential adverse effects of different food additives on the growth and developmental pathways of fruit flies. (Li L., et al. Int J Mol Sci, 2024).

    Read more

    Computational Drug Repurposing

    In the field of drug discovery, how to efficiently mine transcriptome data and identify new indications for old drugs remains a critical challenge. discussed the irreplaceable role of transcriptome data in computational drug repurposing and summarized some representative databases, tools and strategies. (He H., Duo H., et al. Computers in Biology and Medicine, 2023)

    Read more

    LAB MEMBERS: Teachers

    Faculty Members

    Youjin HAO 

     Professor, College of Life Sciences, CQNU

    Dr. Hao the Director of the Department of Biology at College of Life Sciences, Chongqing Normal University. He graduated with a Bachelor of Science degree from Ludong University in 1998, followed by Master's and Ph.D. degrees from Nankai University in 2001 and 2005. With experience as a Postdoctoral researcher at the University of the Azores, Portugal, and as an Assistant Researcher at the University of Chicago, USA, he also served as a Senior Visiting Scholar at the University of Colorado, USA from 2017 to 2018. Proficient in teaching courses such as Cell Biology, Cell Engineering, Enzyme Engineering, Professional English, and Advanced Molecular Biology, his current research focuses on biological big data mining and analysis. He has led or participated in over 10 scientific research projects globally, published more than 80 papers in prestigious journals, holds 3 utility model patents, and was awarded one third prize in Natural Science from Chongqing City.

    Bo LI 

     Associate Professor, College of Life Sciences, CQNU

    Dr. Li currently holds the positions of Associate Professor and Master's Supervisor. He obtained his bachelor's degree from Northwest A&F University in 2003, followed by earning a master's degree in Biophysics and a Ph.D. in Bioinformatics from Chongqing University. With expertise in bioinformatics, machine learning, and biological data mining, he actively contributes to teaching and research in these areas. Li has been involved in leading or collaborating on various provincial and ministerial-level projects, including an educational reform initiative. He has also authored a textbook and published over 50 academic papers in prestigious international journals such as Nucleic Acids Research, Trends in Food Science & Technology, Bioinformatics, Briefings in Bioinformatics, and Molecular & Cellular Proteomics.

    Lab members: Students

    Graduate Student

    Hongrui DUO

    Recommended graduate student
    (2022)

    Yujie ZENG

    Graduate student
    (2022)

    Xiaoxi ZHANG

    Graduate student
    (2022)

    Jing SUN

    Graduate student
    (2023)

    Yingxue XIAO

    Graduate student
    (2023)

    Hanyue HU

    Graduate student
    (2023)

    Lingling XIE

    Graduate student
    (2024)

    Fan HE

    Graduate student
    (2024)

    Tong LI

    Graduate student
    (2024)

    Shiqi LIN

    Graduate student
    (2024)

    Yuyan LIU

    Graduate student
    (2024)

    Ziqi MA

    Graduate student
    (2024)

    Xiaojiao TANG

    Graduate student
    (2024)

    Ting WEI

    Graduate student
    (2024)

    Yi WU

    Graduate student
    (2024)

    Undergraduates

    Yue ZOU

    Undergraduate
    (2021)

    Rui GAO

    Undergraduate
    (2022)

    Chen XU

    Undergraduate
    (2022)

    Qiuyue HU

    Undergraduate
    (2023)

    Feifei LI

    Undergraduate
    (2023)

    Dandan LIU

    Undergraduate
    (2023)

    Alumni

    Publications

    Selected Publications

    # Equal contribution; * Corresponding author


    2024

    TMED4 maintains Treg cell suppressive function through modulating ROS homeostasis via balancing BiP-IRE1α-XBP1 signaling axis and NRF2 antioxidant stress response

    Jiang Z.#, Wang H.#, Wang X.#, Duo H.#, Tao Y., Li J., Li X., Liu J., Ni J., Wu J., Xiang H., Guan C., Wang X., Zhang K., Zhang P., Hou Z., Liu Y., Wang Z., Su B., Li B., Hao Y.*, Li B.* & Wu X*.

    Journal of Clinical Investigation, Accepted, 2024  

    Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios

    Duo H.#, Li Y.#, Lan Y.#, Tao J., Yang Q., Xiao Y., Sun J., Li L., Nie X., Zhang X., Liang G., Liu M., Hao Y.* & Li B*.

    Genome Biology, 25: 145, 2024  

    Common Methods for Phylogenetic Tree Construction and Their Implementation in R

    Zou Y.#, Zhang Z.#, Zeng Y., Hu H., Hao Y., Huang S.* & Li B*.

    Bioengineering, 11(5): 480, 2024  

    A Comparative Benchmarking and Evaluation Framework for Heterogeneous Network-Based Drug Repositioning Methods

    Li Y.#,*, Yang Y.#,, Tong Z., Wang Y., Mi Q., Bai M., Liang G., Li B.* & Shu K*.

    Briefings in Bioinformatics, 25(3): bbae172, 2024  

    International Journal of Molecular Sciences, 25(7): 3738, 2024  

    Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma

    Tang J.#, Mou M.#, Zheng X.#, Yan J., Pan Z., Zhang J., Li B., Yang Q., Wang Y., Zhang Y., Gao J., Li S.*, Yang H.* & Zhu F*.

    Analytical Chemistry, 96(12): 4745–4755, 2024  

    Journal of Chongqing Normal University (Natural Science), 41(1): 125-132, 2024  

    2023

    Symbiosis between Dendrobium catenatum protocorms and Serendipita indica involves the plant hypoxia response pathway

    Xu Z.-X.#, Zhu X.-M.#, Yin H., Li B., Chen X.-J., Fan X.-L., Li N.-Q., Selosse M.-A., Gao J.-Y.* & Han J.-J*

    Plant Physiology, 192(3): 2554-2568, 2023  

    Clustering ensemble in scRNA-seq data analysis: methods, applications and challenges

    Nie X., Qin D,, Zhou X., Duo H., Hao Y., Li B.*, Liang G*.

    Computers in Biology and Medicine, 159: 106939, 2023  

    Long F.#, Ma H.#, Hao Y.#, Tian L., Li Y., Li B., Chen J., Tang Y., Li J., Deng L., Xie G.*, Liu M*.

    Computational and Structural Biotechnology Journal, 21: 3010-3023, 2023  

    Computers in Biology and Medicine, 155: 106671, 2023  

    Popular Resources

    Classes for Students

    Bioinformatics-B2023

    for Undergraduates
    Undergraduate students majoring in Biology, autumn semester, CQNU

    Bioinformatics-M2023

    for Graduate students
    Graduate students majoring in Biochem. & Mol. Biology, autumn semester, CQNU

    Bioinformatics-D2023

    for Ph.D candidates
    Ph.D students majoring in Biology, autumn semester, CQNU

    Software and Tools

    NOREVA
    MMEASE
    DEGMiner
    simshiny

    Under construction

    Downloading Zone

    CibLab

    Toolkits

      EditPlus 3.0 
      Sublime Text 
      Endnote X8 

    CibLab

    Datasets





    CibLab

    Document





     

    News

    2024 May: Hongrui's paper has been accepted by Genome Biology! Congrats Hongrui!

    2024 May: Yue's paper has been published online by Bioengineering! Congrats Yue!

    2024 Apr: Qian's site in Bilibili was public, showing many movies for teaching biology at high school Click here! !

    2024 Mar: Bo's collaboration paper (with Li Y. & Shu K.) is accepted in Briefings in Bioinformatics! Congrats Bo!

    2024 Mar: Lei Li's paper is accepted in Int. J. Mol. Sci.! Congrats Li!

    2023 Sep: Welcome our new graduate students, Yingxue Xiao, Jing Sun & Hanyue Hu!

    2023 Jun: Yin's collaboration paper (with Xu Z. & Han J.) is accepted in Plant Physiology! Congrats Yin!

    2023 May: We started hiring!

    2023 Mar: Welcome our new intern students!

    Contact

    Join us!

    We are looking for passionate (graduate students and undergraduates to develop together. Please do not hesitate to contact us ( libcell@cqnu.edu.cn) or ( haoyoujin@hotmail.com) if you are interested in bioinformatics or computational biology.

    © 2024 Hao & Li Laboratory. All Rights Reserved. Designed by HTML Codex
    Visit our CP: RStuio CibLab ||| Seminar portal