二、阅读科研论文：
1. Solving 3-Coloring Problem with Timed Tissue P Systems，亚洲膜计算国际会议，2013；
2. The PageRank Citation Ranking : Bringing Order to the Web，http://www-db.stanford.edu/-backrub/pageranksub.ps，1998，9（1）；
3. Time-Free Solution to Hamilton Path Problems Using P Systems with d-Division，《Journal of Applied Mathematics》，2013，（4）；
4. 基于生物网络的疾病 microRNA挖掘技术研究，博士学位论文；
5. Matrix Factorization Techniques for Recommender Systems，《Computer》，2009，42（8）；
6. The Link-Prediction Problem for Social Networks，《Journal of the Association for Information Science and Technology》，2007，58（7）；
7. Network-based global inference of human disease genes，《Molecular Systems Biology》，2008,4（1）；
8. Genome-wide inferring gene–phenotype relationship by walking on the heterogeneous network，《Bioinformatics》，2010，26（9）；
9. Prediction and Validation of Gene-Disease Associations Using Methods Inspired by Social Network Analyses，PloS one，2013，8（5）；
10. Walking the Interactome for Prioritization of Candidate Disease Genes，《American Journal of Human Genetics》，2008，82（4）；
11. Ranking-based clustering of heterogeneous information networks with star network schema， ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28 – July，2009；
12. PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks，《Proceedings of the Vldb Endowment》 ， 2011,4（11）；
13. Co-author Relationship Prediction in Heterogeneous Bibliographic Networks，International Conference on Advances in Social Networks Analysis and Mining，2011；
14. A Survey of Link Prediction in Social Networks，《Social Network Data Analytics》，2011；
15. Inductive matrix completion for predicting gene–disease associations，《Bioinformatics》，2014，30（12）；
16. Cross Social Media Recommendation，The International AAAI Conference on Web and Social Media，2016；
17. Unsupervised Feature Selection on Networks: A Generative View，National Conference of the American Association for Artificial Intelligence，2016；
18. Integrative approaches for predicting protein function and prioritizing genes for complex phenotypes using protein interaction networks，《Briefings in Bioinformatics》，2014，15（5）；
19. Jumping across biomedical contexts using compressive data fusion，《Bioinformatics》，2016，32（12）；
20. PU Learning for Matrix Completion，《Computer Science》，2014。