微小RNA（microRNA）及其调控网络. MiRNAs are a class of endogenous regulatory small noncoding RNAs. At least 30% protein-coding genes are regulated by these tiny molecules. Using deep sequencing technology, we aim at developing the computational pipeline to analyze the miRNA expressions. Then, we try to develop network-based multi-layer association analysis methods (funded by NSFC) to identify the miRNA sub-networks regulating the cell phenotypes or diseases.
复杂生物网络的信息理论与计算分析. We are very interested in developing new theories and methods to establish the association (may be casual) between network states and cell/disease phenotypes. It is expected that we can use network states to explain or predict the disease occurrence and progression. We are also interested in developing new tools integrating gene expressions, biological networks and literature information, such as network clustering-based gene set analysis, gene function prediction and the simplified equivalent model of biological networks.
计算平台与数据库开发. Develop computational platform and databases for angiogenesis, inflammation, etc. Lab-mates have developed dozens of software and databases in network analysis, pathway analysis, literature mining, association analysis, etc. For better maintenance and broader use of these resources, we are developing flexible computational and storage platform to achieve the integration. We welcome the students with good software engineering/programming background to join our team.
 ClustEx: responsive gene module identification package (v0.3)
 PCS: de novo k-mer analysis package (v1.5)
 Mamm miR-EST: the ESTs mapped to the flanking sequences of miRNAs
 Jin Gu, Yang Chen, Shao Li, Yanda Li. Identification of responsive gene modules by network-based gene clustering and extending: application to inflammation and angiogenesis. BMC Systems Biology 2010, 4:47.
 Jin Gu. Brief review: frontiers in the computational studies of gene regulations. Frontier of Electrical Electronic Engineering in China 2008, 3(3):251-259.
 Xiaowo Wang, Jin Gu, Michael Zhang, Yanda Li. Identification of phylogenetically conserved microRNA cis-regulatory elements across 12 Drosophila species. Bioinformatics 2008, 24(2):165-171.
 Tao He, Fei Li, Jin Gu, Ruiqiang Li, Fei Li. Computational Identification of 99 Invertebrate MicroRNAs with Comparative Genomics. Tsinghua Science and Technology 2008, 13(4):425-432.
 Jin Gu, Hu Fu, Xuegong Zhang, Yanda Li. Identifications of conserved 7-mers in 3'-UTRs and microRNAs in Drosophila. BMC Bioinformatics 2007, 8:32.
 Jin Gu, Tao He, Yunfei Pei, Fei Li, Jing Zhang, Xiaowo Wang, Xuegong Zhang, Yanda Li. Primary Transcripts and Expressions of Mammal Intergenic MicroRNAs Detected by Mapping ESTs to Their Flanking Sequences. Mammalian Genome 2006, 17(10):1033-1041.
 Xiaowo Wang, Jing Zhang, Fei Li, Jin Gu, Tao He, Xuegong Zhang, Yanda Li. MicroRNA Identification Based on Sequence and Structure Alignment. Bioinformatics 2005, 21(18):3610-3614.
 Dingming Wu, Michael Q Zhang, Jin Gu. A new gene network clustering algorithm based on minimum spanning tree. The 4th Chinese National Bioinformatics and Systems Biology Conference, 2010, Hangzhou. (Poster)
 Ting Wang, Jin Gu, Rui Li, Shiwen Zhao, Yanda Li. Defining gene expression adaptive responses regulated by microRNAs and transcription factors in human umbilical vein endothelial cells. Computational Biology 2010, Suzhou Dushu Lake Conference Center. (Abstract & Oral Presentation)
 Jin Gu. A multiple-instance scoring method to predict tissue-specific cis-regulatory motifs and regions. The International MultiConference of Engineers and Computer Scientists (IMECS'10) 2010, Vol I:186-190. (Oral Presentation)
 Jin Gu, Shao Li, Yang Chen, Yanda Li. Integrative computational identifications of the signaling pathway network related to TNF-alpha stimulus in vascular endothelial cells. International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing (IJCBS'09) 2009, 422-427. (Oral Presentation)