• PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition.

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  • DNA4mC-LIP: a linear integration method to identify N4-methylcytosine site in multiple species.

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  • iRNA-3typeA: identifying 3-types of modification at RNA’s adenosine sites.

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  • iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition.

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  • iRSpot-PseDNC: Identify recombination spots with pseudo dinucleotide composition.

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  • im6A-TS-CNN: identifying N6-methyladenine site in multiple tissues by using convolutional neural network.

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Research

Recent development of high-throughput technologies generate and continue to generate an overwhelmingly large amount of biological and medical data, which provides both opportunities and challenges. Bioinformatics analysis, as excellent complements to experimental techniques, provide a fast, efficient and cost effective solution to modeling excellent data, and revealing the underlying biological mechanisms.


The main focus of our group is on the following fields:

      1. Designing computational tools for biological data representation and visualization.
      2. Developing bioinformatics methods for genomics and proteomics annotation.
      3. Mining the potential biomarkers for disease diagnosis and therapy.
      4. Constructing databases for biological and medical data.