张胜利
- 副教授
- 性别：男
- 毕业院校：大连理工大学
- 学历：博士研究生毕业
- 学位：博士学位
- 在职信息：在岗
- 所在单位：数学与统计学院
- 入职时间： 2011-07-01
- 学科：应用数学 统计学
- 办公地点：行政辅楼326室
- 电子邮箱：27b93f8b4e0f500da82c205ab81cb4852b22d8bd496e2da5d911f887c6696f95af36f537a356ad3a8a5eb0053a593b08dc0a6fc8cd729a3eb6785c78241afbe7865c748c27fa730033542490ab726f276dbed7ced580cd5d470fe942fbf52523355e322e99c5d1dbd66dd99004adecd784a5cdc2a50757205bb1fe8444bf71eb
访问量：
- [1] iPro-GAN: A novel model based on generative adversarial learning for identifying promoters and their strength.Computer Methods and Programs in Biomedicine.2022
- [2] Pep-CNN: An improved convolutional neural network for predicting therapeutic peptides.Chemometrics and Intelligent Laboratory Systems.2022
- [3] iR5hmcSC: Identifying RNA 5-hydroxymethylcytosine with multiple features based on stacking learning.Computational Biology and Chemistry.2021
- [4] PA-PseU: An incremental passive-aggressive based method for identifying RNA pseudouridine sites via Chou's 5-steps rule.Chemometrics and Intelligent Laboratory Systems.2021
- [5] i6mA‑VC: A Multi‑Classifier Voting Method for the Computational Identification of DNA N6‑methyladenine Sites.Interdisciplinary Sciences: Computational Life Sciences.2021
- [6] Zhang Shengli(#)(*); Yu Qianhao; He Haoran; Zhu Fu; Wu Panjing; Gu Lingzhi; Jiang Sijie. iDHS-DSAMS: Identifying DNase I hypersensitive sites based on the dinucleotide property matrix and ensemble bagged tree..Genomics.2020,112 :1282-1289
- [7] Zhang, Shengli(#)(*); Yang, Kaiwen; Lei, Yuqing; Song, Kang. iRSpot-DTS: Predict recombination spots by incorporating the dinucleotide-based spare-cross covariance information into Chou's pseudo components..Genomics.2019,111 (6):1760-1770
- [8] Zhou Cong; Liu Sanyang; Zhang Shengli(*). Identification of amyloidogenic peptides via optimized integrated features space based on physicochemical properties and PSSM..Analytical Biochemistry.2019,583 :113362
- [9] Shengli Zhang, Tongtong Zhang, Chang Liu. Prediction of Apoptosis Protein Subcellular Localization via Heterogenous Features and Hierarchical Extreme Learning Machine.SAR and QSAR in Environmental Research.2019
- [10] Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC.Journal of Theoretical Biology.2018,437 (1):239-250
- [11] Prediction of Protein Subcellular Localization by Using λ-order Factor and Principal Component Analysis.Letters in Organic Chemistry.2017,14 (3):717-724
- [12] Accurate prediction of protein structural classes by incorporating PSSS and PSSM into Chou's general PseAAC.CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS.2015,142 :28-35
- [13] A Novel Reduced Triplet Composition Based Method to Predict Apoptosis Protein Subcellular Localization.MATCH-COMMUNICATIONS IN MATHEMATICAL AND IN COMPUTER CHEMISTRY.2015,73 (2):559-571
- [14] Novel method to numerically characterize protein sequences and its application.Journal of Computational and Theoretical Nanoscience.2015,12 (10):3487-3491
