2018年度单位署名论文

1. Bai, X., Jia, J.a., Fang, M., Chen, S., Liang, X., Zhu, S., Zhang, S., Feng, J., Sun, F., & Gao, C. (2018). Deep sequencing of HBV pre-S region reveals high heterogeneity of HBV genotypes and associations of word pattern frequencies with HCC. Plos Genetics, 14(2).

2. Cheng, W., Rolls, E., Qiu, J., Xie, X., Lyu, W., Li, Y., Huang, C.C., Yang, A., Tsai, S.J., Lyu, F., Zhuang, K., Lin, C.P., Xie, P., & Feng, J. (2018). Functional connectivity of the human amygdala in health and in depression. Social Cognitive and Affective Neuroscience, 13(6), 557-568. Functional connectivity of the human amygdala in health and in depression.pdf

3. Cheng, W., Rolls, E., Qiu, J., Xie, X., Wei, D., Huang, C.C., Yang, A., Tsai, S.J., Li, Q., Meng, J., Lin, C.P., Xie, P., & Feng, J. (2018). Increased functional connectivity of the posterior cingulate cortex with the lateral orbitofrontal cortex in depression. Translational Psychiatry, 8. Increased functional connectivity of the posterior cingulate cortex with the lateral orbitofrontal cortex in depression.pdf

4. Cheng, W., Rolls, E., Qiu, J., Yang, D., Ruan, H., Wei, D., Zhao, L., Meng, J., Xie, P., & Feng, J. (2018). Functional Connectivity of the Precuneus in Unmedicated Patients With Depression. Biological Psychiatry-Cognitive Neuroscience and Neuroimaging, 3(12), 1040-1049. Functional connectivity of the precuneus in unmedicated patients with depression.pdf

5. Cheng, W., Rolls, E., Ruan, H., & Feng, J. (2018). Functional Connectivities in the Brain That Mediate the Association Between Depressive Problems and Sleep Quality. Jama Psychiatry, 75(10), 1052-1061. Functional Connectivities in the Brain That Mediate the Association Between Depressive Problems and Sleep Quality.pdf

6. Dai, F., Zhou, S., Peron, T., Lin, W., & Ji, P. (2018). Interplay among inertia, time delay, and frustration on synchronization dynamics. Physical Review E, 98(5).

7. Du, M., Li, J., Chen, L., Yu, Y., & Wu, Y. (2018). Astrocytic Kir4.1 channels and gap junctions account for spontaneous epileptic seizure. Plos Computational Biology, 14(3).

8. Fang, L.H., Lin, W., & Luo, Q. (2018). Brain-Inspired Constructive Learning Algorithms with Evolutionally Additive Nonlinear Neurons. International Journal of Bifurcation and Chaos, 28(5). Brain-Inspired Constr Statistical testing and power analysis for brain-wide association study.pdfuctive Learning Algorithms with Evolutionally Additive Nonlinear Neurons(Article).pdf

9. Gao, N., Zhang, C., Zhang, Z., Hu, S., Lercher, M., Zhao, X.M., Bork, P., Liu, Z., & Chen, W.H. (2018). MVP: a microbe-phage interaction database. Nucleic Acids Research, 46(D1), D700-D707. MVP a microbe-phage interaction database.pdf

10. Ge, S., Geng, X., Wang, X., Li, N., Chen, L., Zhang, X., Huang, Y., Li, Y., Chen, Y., Wang, S., & Gao, G. (2018). Oscillatory local field potentials of the nucleus accumbens and the anterior limb of the internal capsule in heroin addicts. Clinical Neurophysiology, 129(6), 1242-1253. Oscillatory local field potentials of the nucleus accumbens and the anterior limb of the internal capsule in heroin addicts.pdf

11. Geng, X., Xu, X., Horn, A., Li, N., Ling, Z., Brown, P., & Wang, S. (2018). Intra-operative characterisation of subthalamic oscillations in Parkinson's disease. Clinical Neurophysiology, 129(5), 1001-1010.

12. Gong, W., Wan, L., Lu, W., Ma, L., Cheng, F., Cheng, W., Grunewald, S., & Feng, J. (2018). Statistical testing and power analysis for brain-wide association study. Medical Image Analysis, 47, 15-30. Statistical testing and power analysis for brain-wide association study.pdf

13. Huang, S., & Zhao, X.M. (2018). Prediction of Drug Response with a Topology Based Dual-Layer Network Model. Bioinformatics Research and Applications, Isbra 2018, 10847, 3-12. Prediction of Drug Response with a Topology Based Dual-Layer Network Model.pdf

14. Huang, Y., Wu, D., Bahuri, N., Wang, S., Hyam, J., Yarrow, S., FitzGerald, J., Aziz, T., & Green, A. (2018). Spectral and phase-amplitude coupling signatures in human deep brain oscillations during propofol-induced anaesthesia. British Journal of Anaesthesia, 121(1), 303-313. Spectral and phase-amplitude coupling signatures in human deep brain oscillations during propofol-induced anaesthesia.pdf 

15. Huang, Y., Green, A., Hyam, J., Fitzgerald, J., Aziz, T., & Wang, S. (2018). Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation. Neurobiology of Disease, 109, 117-126. Oscillatory neural representations in the sensory thalamus predict.pdf

16. Ji, P., Lu, W., & Kurths, J. (2018). Stochastic basin stability in complex networks. Epl, 122(4). Stochastic basin stability in complex networks.pdf

17. Jia, F., Shan, L., Wang, B., Li, H., Miao, C., Xu, Z., Lin, C.P., & Saad, K. (2018). Bench to bedside review: Possible role of vitamin D in autism spectrum disorder. Psychiatry Research, 260, 360-365.

18. Li, C. (2018). Landscape of gene networks for random parameter perturbation. Integrative Biology, 10(2), 92-99. Landscape of gene networks for random parameter perturbation.pdf

19. Li, C., & Balazsi, G. (2018). A landscape view on the interplay between EMT and cancer metastasis. Npj Systems Biology and Applications, 4. A landscape view on the interplay between EMT and cancer metastasis.pdf

20. Li, C., Zhang, L., & Nie, Q. (2018). Landscape reveals critical network structures for sharpening gene expression boundaries. Bmc Systems Biology, 12. Landscape reveals critical network structures for sharpening gene expression boundaries.pdf