Publications

Google Scholar (link to this website: https://scholar.google.com/citations?hl=en&user=1sdUrZMAAAAJ )

44. Sihua Peng. HIV-1 M group subtype classification using deep learning approach. Comput Biol Med. 2024 Oct 5;183:109218. doi: 10.1016/j.compbiomed.2024.109218

43. Shihang Wang, Zhehan Shen, Taigang Liu, Sihua Peng. DeepmRNALoc: A novel predictor of eukaryotic mRNA subcellular localization based on deep learning. Molecules 2023, 28, 2284, (corresponding author) pdf

42.Cai Wei, Dan Sun, Wenliang Yuan, Lei Li, Chaoxu Dai, Zuozhou Chen, Xiaomin Zeng, Shihang Wang, Yuyang Zhang, Shouwen Jiang, Zhichao Wu, Dong Liu, Linhua Jiang, and Sihua Peng. Metagenomics revealing molecular profiling of microbial community structure and metabolic capacity in Bamucuo, Tibet . Environmental Research. 217 (2023) 11484 (corresponding author) pdf .

41. Xiaoyu Liu, Jingying Zhao, Sicong Li, Cai Wei, Shihang Wang, Xuanyu Xu, Yin Zheng, Xiangyu Deng, Wenliang Yuan, Xiaomin Zeng, and Sihua Peng. Clarifying real receptor binding site between coronavirus hcov-hku1 and 9-o-ac-sia based on molecular docking. J Bioinform Comput Biol. 2022, 20(1):2150034 (corresponding author) pdf

40. Shihang Wang, Xuanyu Xu, Cai Wei, Sicong Li, Jingying Zhao, Yin Zheng, Xiaoyu Liu, Xiaomin Zeng, Wenliang Yuan, Sihua Peng. Molecular evolutionary characteristics of SARS‐CoV‐2 emerging in the United States. J Med Virol. 2022, 1‐8. (corresponding author) pdf

39. Yuan, Wenliang; Cai, Wei; Huang, Xiao; et al. Prognostic value of immune scores in the microenvironment of colorectal cancer.Oncology letters. 2020, 20(5): 256 (corresponding author) pdf

38. Guli Jiang, Jing Mu, Xing Liu, Xiangni Peng, Feiya Zhong, Wenliang Yuan, Fang Deng, Xiaoning Peng, Sihua Peng & Xiaomin Zeng. Prognostic value of miR-21 in gliomas: comprehensive study based on meta-analysis and TCGA dataset validation.Scientific Reports. 2020,10: 4220(corresponding author) pdf

37. Huang, Xiao; Cai, Wei; Yuan, Wenliang; Peng, Sihua. Identification of key lncRNAs as prognostic prediction models for colorectal cancer based on LASSO.International journal of clinical and experimental pathology. 2020, 13:675-684(corresponding author) pdf

36. Yuan W, Jiang S, Sun D, Wu Z, Wei C, Dai C, Jiang L, Peng S.Transcriptome profiling analysis of sex-based differentially expressed mRNAs and lncRNAs in the brains of mature zebrafish (Danio rerio). BMC Genomics. 2019, 20(1):830. (corresponding author) pdf

35. Yuan W, Liu L, Wei C, Li X, Sun D, Dai C, Li S, Peng S, Jiang L.Identification and meta-analysis of copy number variation-driven circadian clock genes for colorectal cancer. Oncol Lett. 2019, 18(5):4816-4824. (corresponding author) pdf

34. Yuan W, Peng S, Wang J, Wei C, Ye Z, Wang Y, Wang M, Xu H, Jiang S, Sun D, Dai C, Jiang L, Li X.Identification and characterization of circRNAs as competing endogenous RNAs for miRNA-mRNA in colorectal cancer. PeerJ. 2019, 7:e7602. pdf

33. Li Y, Li W, Zeng X, Tang X, Zhang S, Zhong F, Peng X, Zhong Y, Rosol TJ, Deng X, Liu Z, Peng S, Peng X.The role of microRNA-148a and downstream DLGAP1 on the molecular regulation and tumor progression on human glioblastoma. Oncogene. 2019, 38(47):7234-7248. (corresponding author) pdf

32. Li L, Jiang L, Peng S.Protein Network Analysis of the Fifth Chromosome of Zebrafish. J Comput Biol. 2019 Aug 28. doi: 10.1089/cmb.2019.0157.

31. Chen L, Lu Y, Li W, Ren Y, Yu M, Jiang S, Fu Y, Wang J, Peng S, Bilyk KT, Murphy KR, Zhuang X, Hune M, Zhai W, Wang W, Xu Q, Cheng CC.The genomic basis for colonizing the freezing Southern Ocean revealed by Antarctic toothfish and Patagonian robalo genomes. Gigascience. 2019, 8(4). pii: giz016.

30. Yuan W, Li X, Liu L, Wei C, Sun D, Peng S, Jiang L.Comprehensive analysis of lncRNA-associated ceRNA network in colorectal cancer. Biochem Biophys Res Commun. 2019, 508(2):374-379. (corresponding author)

29. Sihua Peng, Shouwen Jiang, Dan Sun, Zhichao Wu, Jie Chen. Application of metagenomic technology in the identification of aquatic animal viruses. Jiangsu Agricultural Journal, 2019, 35(1): 229-237. (corresponding author)

28. Sihua Peng, Dan Sun, Wenliang Yuan, Cai Wei. Discovery of Biocatalysts through Metagenomics. Chinese Journal of Applied and Environmental Biology, 2019, 25(2): 463-472. (corresponding author)

27. Sihua Peng, Zhichao Wu, Dan Sun, Shuangpei Tan, Yiming Wang, Dengxin Wen. Application of metagenomics in the identification of antibiotic resistance genes. Genomics and Applied Biology. 2019, 38(9):4102-4109. (corresponding author)

26. Dan Sun, Wenliang Yuan, Sihua Peng. Application of long-read sequencing technology in metagenomics research. Life Science,2018, 30(8):896-905. (corresponding author)

25. Zhang D, Yu M, Hu P, Peng S, Liu Y, Li W, Wang C, He S, Zhai W, Xu Q, Chen L.Genetic Adaptation of Schizothoracine Fish to the Phased Uplifting of the Qinghai-Tibetan Plateau. G3 (Bethesda). 2017, 7(4):1267-1276.

24. Xu Q, Zhang C, Zhang D, Jiang H, Peng S, Liu Y, Zhao K, Wang C, Chen L.Analysis of the erythropoietin of a Tibetan Plateau schizothoracine fish (Gymnocypris dobula) reveals enhanced cytoprotection function in hypoxic environments. BMC Evol Biol. 2016 Jan 15;16:11. doi: 10.1186/s12862-015-0581-0.

23. Xu Q, Cai C, Hu X, Liu Y, Guo Y, Hu P, Chen Z, Peng S, Zhang D, Jiang S, Wu Z, Chan J, Chen L.Evolutionary suppression of erythropoiesis via the modulation of TGF-β signalling in an Antarctic icefish. Mol Ecol. 2015, 24(18):4664-78.

22. Sylvester KG, Ling XB, Liu GY, Kastenberg ZJ, Ji J, Hu Z, Wu S, Peng S, Abdullah F, Brandt ML, Ehrenkranz RA, Harris MC, Lee TC, Simpson BJ, Bowers C, Moss RL.Urine protein biomarkers for the diagnosis and prognosis of necrotizing enterocolitis in infants. J Pediatr. 2014, 164(3):607-12.e1-7.

21. Xiaobi Li, Sihua peng. Research on Feature Gene Selection Method for Multi-Class Tumor Classification. Journal of Fudan University (Natural Science Edition). 2014, 53(3):305-312.

20. Li X, Peng S.Identification of metastasis-associated genes in colorectal cancer through an integrated genomic and transcriptomic analysis. Chin J Cancer Res. 2013 Dec;25(6):623-36.

19. Sylvester KG, Ling XB, Liu GY, Kastenberg ZJ, Ji J, Hu Z, Peng S, Lau K, Abdullah F, Brandt ML, Ehrenkranz RA, Harris MC, Lee TC, Simpson J, Bowers C, Moss RL.A novel urine peptide biomarker-based algorithm for the prognosis of necrotising enterocolitis in human infants. Gut. 2014, 63(8):1284-92.

18. Peng S, Zhu Y, Lü B, Xu F, Li X, Lai M.TCF7L2 gene polymorphisms and type 2 diabetes risk: a comprehensive and updated meta-analysis involving 121,174 subjects. Mutagenesis. 2013, 28(1):25-37.

17. Ling XB, Macaubas C, Alexander HC, Wen Q, Chen E, Peng S, Sun Y, Deshpande C, Pan KH, Lin R, Lih CJ, Chang SY, Lee T, Sandborg C, Begovich AB, Cohen SN, Mellins ED.Correlation analyses of clinical and molecular findings identify candidate biological pathways in systemic juvenile idiopathic arthritis. BMC Med. 2012, 10:125.

16. Ling XB, Kanegaye JT, Ji J, Peng S, Sato Y, Tremoulet A, Burns JC, Cohen HJ.Point-of-care differentiation of Kawasaki disease from other febrile illnesses. J Pediatr. 2013, 162(1):183-188.e3.

15. Li X, Peng S, Chen J, Lü B, Zhang H, Lai M.SVM-T-RFE: a novel gene selection algorithm for identifying metastasis-related genes in colorectal cancer using gene expression profiles. Biochem Biophys Res Commun. 2012, 419(2):148-53.

14. Ling XB, Lau K, Kanegaye JT, Pan Z, Peng S, Ji J, Liu G, Sato Y, Yu TT, Whitin JC, Schilling J, Burns JC, Cohen HJ.A diagnostic algorithm combining clinical and molecular data distinguishes Kawasaki disease from other febrile illnesses. BMC Med. 2011, 9:130.

13. Ganping Yang, Sihua Peng, Shuangyan Zuo, Yiren Wang, Xiaoning Peng, Xiaomin Zeng. Meta-analysis of the association between leptin receptor Gln223Arg and Pr01019Pro gene polymorphisms and obesity in Chinese population. Chinese Journal of Epidemiology.1211, 32(10):1037-1042.

12. Peng S, Zhu Y, Xu F, Ren X, Li X, Lai M.FTO gene polymorphisms and obesity risk: a meta-analysis. BMC Med. 2011, 9:71.

11. Peng S, Lü B, Ruan W, Zhu Y, Sheng H, Lai M.Genetic polymorphisms and breast cancer risk: evidence from meta-analyses, pooled analyses, and genome-wide association studies. Breast Cancer Res Treat. 2011, 127(2):309-24.

10. Li X, Chen J, Lü B, Peng S, Desper R, Lai M.-8p12-23 and +20q are predictors of subtypes and metastatic pathways in colorectal cancer: construction of tree models using comparative genomic hybridization data. OMICS. 2011, 15(1-2):37-47.

9. Peng S, Zeng X, Li X, Peng X, Chen L.Multi-class cancer classification through gene expression profiles: microRNA versus mRNA. J Genet Genomics. 2009 Jul;36(7):409-16.

8. Peng X, Zeng X, Peng S, Deng D, Zhang J.The association risk of male subfertility and testicular cancer: a systematic review. PLoS One. 2009, 4(5):e5591.

7. Dai Z, Chen Z, Ye H, Zhou L, Cao L, Wang Y, Peng S, Chen L.Characterization of microRNAs in cephalochordates reveals a correlation between microRNA repertoire homology and morphological similarity in chordate evolution. Evol Dev. 2009 , 11(1):41-9.

6. Xiaoning Peng, Sihua Peng, Xiaomin Zeng. Research progress in early diagnosis of ovarian cancer. International Journal of Pathological Science and Clinical.2007, 27(6):489-492.

5. Dong H, Deng Y, Chen J, Wang S, Peng S, Dai C, Fang Y, Shao J, Lou Y, Li D.An exploration of 3'-end processing signals and their tissue distribution in Oryza sativa. Gene. 2007, 389(2):107-13.

4. Multiclass cancer classification and biomarker discovery using GA-based algorithms.Liu JJ, Cutler G, Li W, Pan Z, Peng S, Hoey T, Chen L, Ling XB. Bioinformatics. 2005, 21(11):2691-7.

3. Sihua Peng, Hongliang Zhou, Xiaoning Peng, Wei Du. Analysis and Modeling of Systems Biology. Information and Control.2004, 33(4):457-462.

2. Peng S, Xu Q, Ling XB, Peng X, Du W, Chen L.Molecular classification of cancer types from microarray data using the combination of genetic algorithms and support vector machines. FEBS Lett. 2003, 555(2):358-62.

1. Sihua Peng, Longjiang Fan, Xiaoning Peng, Shulin Zhuang, Wei Du, Liangbiao Chen. Splicing-site recognition of rice (Oryza sativa L.)DNA sequences by support vector machines. Journal of Zhejiang University (English version).2003, 4(5):573-577.

 

Our vision


With the dream of exploring nature, we try to find the laws of nature in the palace of science. We firmly believe that artificial intelligence will reconstruct all fields of natural science. This is because the world we live in is nonlinear, and we can address the problem of nonlinear system modeling through deep learning. Therefore, it is our most lofty mission to promote artificial intelligence in various disciplines of scientific research.