zhixu.ni [at] tu-dresden.de
Tel: +49 351 796-5631
Fax: +49 351 796-36699
Twitter: @Zhixu_Ni
GitHub: @ZhixuNi

Zhixu Ni

PostDoctoral researcher

Zhixu Ni (commonly known as “Ni”😊) obtained his BSc in Pharmacy at Wuhan University, China. He did his bachelor thesis as an exchange student at Jena University, Germany. Then he moved to Leipzig for Master study in analytical chemistry, where he met Maria first time for a lab rotation. He continued his PhD with Maria in the field of lipidomics. During the PhD time, Ni faced a critical shortage in automated solutions for identification lipids from LC-MS/MS datasets. To overcome it, Ni successfully developed several software to assist the high-throughput identification and visualization of (epi)lipids. With his broad background and several years of hands-on experience in wet lab, during his postdoc time Ni switched to the software development aiming to provide fine-tuned data analysis solutions for (epi)lipidomics research.

Research interests

Zhixu’s work primarily revolves around creating innovative solutions to assist in comprehensive analysis of lipidomics data. From lipid identification, epilipids prediction, towards complex pathway/network integration and analysis, Ni assembles different bioinformatics methods and tune them specifically for lipidomics data to discover lipidome regulation and plasticity under various conditions. In the past few years, he developed several successful analytical pipelines with built-in user-friendly graphical interface including LipidHunter2, LPPtiger2, LipidLynxX and others ( Read more about our published bioinformatics tools). Currently, Ni research is mainly focused on data integration and advanced analysis of quantitative lipidomics datasets to explain plasticity and dynamics of lipidomes by assembling and optimizing lipid specific algorithms using supervised and unsupervised machine learning methods. Ni key research interests include understanding of (epi)lipdiome regulation under chronic inflammation and metabolic disorders by developing novel bioinformatics tools towards systems biology and medicine integration of multi-omics data.