default search action
Xiaojun Yao
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j77]Pengyong Li, Zhengxiang Jiang, Tianxiao Liu, Xinyu Liu
, Hui Qiao, Xiaojun Yao:
Improving drug response prediction via integrating gene relationships with deep learning. Briefings Bioinform. 25(3) (2024) - [j76]Qianqian Wang
Unraveling the allosteric inhibition mechanism of PARP-1 CAT and the D766/770A mutation effects via Gaussian accelerated molecular dynamics and Markov state model. Comput. Biol. Medicine 168: 107682 (2024) - [j75]Huiying Liu, Xiangzheng Fu, Haiting Chen, Jun Shang, Haoyu Zhou, Wang Zhe, Xiaojun Yao:
Developing explainable models for lncRNA-Targeted drug discovery using graph autoencoders. Future Gener. Comput. Syst. 160: 29-39 (2024) - [j74]Yanan Tian, Chenbin Wang, Ruiqiang Lu, Henry H. Y. Tong, Xiaoqing Gong, Jiayue Qiu, Shaoliang Peng, Xiaojun Yao, Huanxiang Liu
3DSGIMD: An accurate and interpretable molecular property prediction method using 3D spatial graph focusing network and structure-based feature fusion. Future Gener. Comput. Syst. 161: 189-200 (2024) - [j73]Mingyang Wang, Zhengjian Wu, Jike Wang, Gaoqi Weng, Yu Kang
Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space. J. Chem. Inf. Model. 64(4): 1213-1228 (2024) - [j72]Rui Wang
An Effective Plant Small Secretory Peptide Recognition Model Based on Feature Correction Strategy. J. Chem. Inf. Model. 64(7): 2798-2806 (2024) - [j71]Tao Wang, Wentao Wang, Xin Jiang, Jiaxing Mao, Linlin Zhuo
ML-NPI: Predicting Interactions between Noncoding RNA and Protein Based on Meta-Learning in a Large-Scale Dynamic Graph. J. Chem. Inf. Model. 64(7): 2912-2920 (2024) - [j70]Shuo Liu, Jialiang Yu, Ningxi Ni, Zidong Wang, Mengyun Chen, Yuquan Li, Chen Xu, Yahao Ding, Jun Zhang
Versatile Framework for Drug-Target Interaction Prediction by Considering Domain-Specific Features. J. Chem. Inf. Model. 64(14): 5646-5656 (2024) - [j69]Huian Jin, Xiaojun Yao
Ice Thickness Assessment of Non-Freshwater Lakes in the Qinghai-Tibetan Plateau Based on Unmanned Aerial Vehicle-Borne Ice-Penetrating Radar: A Case Study of Qinghai Lake and Gahai Lake. Remote. Sens. 16(6): 959 (2024) - [j68]Juan Zhang, Xiaojun Yao, Hongyu Duan, Xinde Chu, Chen Yang, Jiayu Hu:
Extraction of Cladophora Blooms in Qinghai Lake Through the Integration of Sentinel-2 MSI Imagery and Deep Learning Techniques. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 19115-19129 (2024) - [c2]Quansong He, Xiaojun Yao, Jun Wu, Zhang Yi, Tao He:
A Lightweight U-like Network Utilizing Neural Memory Ordinary Differential Equations for Slimming the Decoder. IJCAI 2024: 821-829 - 2023
- [j67]Yanan Tian, Xiaorui Wang
Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism. Briefings Bioinform. 24(1) (2023) - [j66]Ruiqiang Lu, Jun Wang, Pengyong Li, Yuquan Li, Shuoyan Tan, Yiting Pan, Huanxiang Liu, Peng Gao, Guotong Xie, Xiaojun Yao:
Improving drug-target affinity prediction via feature fusion and knowledge distillation. Briefings Bioinform. 24(3) (2023) - [j65]Jinhang Wei, Linlin Zhuo
GCFMCL: predicting miRNA-drug sensitivity using graph collaborative filtering and multi-view contrastive learning. Briefings Bioinform. 24(4) (2023) - [j64]Qingqing Du, Gao Tu, Yan Qian, Jingyi Yang, Xiaojun Yao, Weiwei Xue:
Unbiased molecular dynamics simulation of a first-in-class small molecule inhibitor binds to oncostatin M. Comput. Biol. Medicine 155: 106709 (2023) - [j63]Jinhang Wei, Linlin Zhuo, Shiyao Pan, Xinze Lian, Xiaojun Yao, Xiangzheng Fu
HeadTailTransfer: An efficient sampling method to improve the performance of graph neural network method in predicting sparse ncRNA-protein interactions. Comput. Biol. Medicine 157: 106783 (2023) - [j62]An Huang
HF-DDI: Predicting Drug-Drug Interaction Events Based on Multimodal Hybrid Fusion. J. Comput. Biol. 30(9): 961-971 (2023) - [j61]Yuwei Yang
Deep Generation Model Guided by the Docking Score for Active Molecular Design. J. Chem. Inf. Model. 63(10): 2983-2991 (2023) - [j60]Xiaodan Yin
CODD-Pred: A Web Server for Efficient Target Identification and Bioactivity Prediction of Small Molecules. J. Chem. Inf. Model. 63(20): 6169-6176 (2023) - [j59]Zhe Wang, Haiyang Zhong
Small-Molecule Conformer Generators: Evaluation of Traditional Methods and AI Models on High-Quality Data Sets. J. Chem. Inf. Model. 63(21): 6525-6536 (2023) - [j58]Yaguo Gong, Wei Ding, Panpan Wang, Qibiao Wu
Evaluating Machine Learning Methods of Analyzing Multiclass Metabolomics. J. Chem. Inf. Model. 63(24): 7628-7641 (2023) - [j57]Guoyu Wang, Xiaohua Hao
Simulations of Snowmelt Runoff in a High-Altitude Mountainous Area Based on Big Data and Machine Learning Models: Taking the Xiying River Basin as an Example. Remote. Sens. 15(4): 1118 (2023) - [j56]Shuting Niu, Meiping Sun, Guoyu Wang, Weisheng Wang, Xiaojun Yao
Glacier Change and Its Influencing Factors in the Northern Part of the Kunlun Mountains. Remote. Sens. 15(16): 3986 (2023) - [j55]Cong Zhang
Glacier Change in the West Kunlun Main Peak Area from 2000 to 2020. Remote. Sens. 15(17): 4236 (2023) - [j54]Xiaojun Yao
Surging Glaciers in High Mountain Asia between 1986 and 2021. Remote. Sens. 15(18): 4595 (2023) - [j53]Yuan Zhang
Inventory of Glacial Lake in the Southeastern Qinghai-Tibet Plateau Derived from Sentinel-1 SAR Image and Sentinel-2 MSI Image. Remote. Sens. 15(21): 5142 (2023) - 2022
- [j52]Weitong Zhang, Wangqi Tian, Yifan Wang, Xiaojie Jin, Hui Guo, Yuwei Wang
Explore the mechanism and substance basis of Mahuang FuziXixin Decoction for the treatment of lung cancer based on network pharmacology and molecular docking. Comput. Biol. Medicine 151(Part): 106293 (2022) - [j51]Yuwei Yang
Exploring Low-Toxicity Chemical Space with Deep Learning for Molecular Generation. J. Chem. Inf. Model. 62(13): 3191-3199 (2022) - [j50]Xiaojun Yao
Do cloud-based enterprise resource planning systems affect the productivity of human resources in the COVID-19 era? Kybernetes 51(6): 1967-1990 (2022) - [j49]Yuquan Li
An adaptive graph learning method for automated molecular interactions and properties predictions. Nat. Mach. Intell. 4(7): 645-651 (2022) - [j48]Yongpeng Gao
The Evolution of the Glacier Surges in the Tuanjie Peak, the Qilian Mountains. Remote. Sens. 14(4): 852 (2022) - [j47]Hongyu Duan, Xiaojun Yao
Long-Term Temporal and Spatial Monitoring of Cladophora Blooms in Qinghai Lake Based on Multi-Source Remote Sensing Images. Remote. Sens. 14(4): 853 (2022) - [j46]Qixin Wei, Xiaojun Yao
Analysis of the Variability and Influencing Factors of Ice Thickness during the Ablation Period in Qinghai Lake Using the GPR Ice Monitoring System. Remote. Sens. 14(10): 2437 (2022) - [j45]Hongfang Zhang, Xiaojun Yao
Comparison of Lake Ice Extraction Methods Based on MODIS Images. Remote. Sens. 14(19): 4740 (2022) - [j44]Jiayu Hu
Temporal and Spatial Changes and GLOF Susceptibility Assessment of Glacial Lakes in Nepal from 2000 to 2020. Remote. Sens. 14(19): 5034 (2022) - 2021
- [j43]Chao Shen, Ye Hu, Zhe Wang
Can machine learning consistently improve the scoring power of classical scoring functions? Insights into the role of machine learning in scoring functions. Briefings Bioinform. 22(1): 497-514 (2021) - [j42]Qifeng Bai
MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm. Briefings Bioinform. 22(3) (2021) - [j41]Pengyong Li, Yuquan Li
TrimNet: learning molecular representation from triplet messages for biomedicine. Briefings Bioinform. 22(4) (2021) - [j40]Chao Shen, Gaoqi Weng, Xujun Zhang, Elaine Lai-Han Leung, Xiaojun Yao, Jinping Pang, Xin Chai, Dan Li, Ercheng Wang
Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening? Briefings Bioinform. 22(5) (2021) - [j39]Pengyong Li, Jun Wang, Yixuan Qiao, Hao Chen, Yihuan Yu, Xiaojun Yao, Peng Gao, Guotong Xie, Sen Song:
An effective self-supervised framework for learning expressive molecular global representations to drug discovery. Briefings Bioinform. 22(6) (2021) - [j38]Huizhen Ge, Longfei Mao, Jie Zhao, Yuwei Wang
Discovery of novel IDO1 inhibitors via structure-based virtual screening and biological assays. J. Comput. Aided Mol. Des. 35(5): 679-694 (2021) - [j37]Lina Xiu
Effect of Ecological Construction Engineering on Vegetation Restoration: A Case Study of the Loess Plateau. Remote. Sens. 13(8): 1407 (2021) - [j36]Sugang Zhou
Remote Sensing Monitoring of Advancing and Surging Glaciers in the Tien Shan, 1990-2019. Remote. Sens. 13(10): 1973 (2021) - 2020
- [j35]Chao Shen, Zhe Wang
Comprehensive assessment of nine docking programs on type II kinase inhibitors: prediction accuracy of sampling power, scoring power and screening power. Briefings Bioinform. 21(1): 282-297 (2020) - [j34]Miaomiao Qi, Shiyin Liu
Monitoring the Ice Phenology of Qinghai Lake from 1980 to 2018 Using Multisource Remote Sensing Data and Google Earth Engine. Remote. Sens. 12(14): 2217 (2020) - [i1]Pengyong Li, Jun Wang, Yixuan Qiao, Hao Chen, Yihuan Yu, Xiaojun Yao, Peng Gao, Guotong Xie, Sen Song:
Learn molecular representations from large-scale unlabeled molecules for drug discovery. CoRR abs/2012.11175 (2020)
2010 – 2019
- 2019
- [j33]Xiaoli An, Shaoyong Lu, Kun Song, Qiancheng Shen, Meilan Huang
Are the Apo Proteins Suitable for the Rational Discovery of Allosteric Drugs? J. Chem. Inf. Model. 59(1): 597-604 (2019) - [j32]Shuangyan Zhou, Yongchang Zhu, Xiaojun Yao
Carbon Nanoparticles Inhibit the Aggregation of Prion Protein as Revealed by Experiments and Atomistic Simulations. J. Chem. Inf. Model. 59(5): 1909-1918 (2019) - [c1]Zhirui Liao, Ronghui You, Xiaodi Huang
DeepDock: Enhancing Ligand-protein Interaction Prediction by a Combination of Ligand and Structure Information. BIBM 2019: 311-317 - 2017
- [j31]Juan Du
Molecular basis of P450 OleTJE: an investigation of substrate binding mechanism and major pathways. J. Comput. Aided Mol. Des. 31(5): 483-495 (2017) - [j30]Lanlan Li
Discovery of small molecules binding to the normal conformation of prion by combining virtual screening and multiple biological activity evaluation methods. J. Comput. Aided Mol. Des. 31(12): 1053-1062 (2017) - 2015
- [j29]Shuyan Li, Jiazhong Li, Lulu Ning, Shaopeng Wang, Yuzhen Niu, Nengzhi Jin, Xiaojun Yao, Huanxiang Liu
In Silico Identification of Protein S-Palmitoylation Sites and Their Involvement in Human Inherited Disease. J. Chem. Inf. Model. 55(9): 2015-2025 (2015) - 2014
- [j28]Weiwei Xue
Computational Study on the Drug Resistance Mechanism against HCV NS3/4A Protease Inhibitors Vaniprevir and MK-5172 by the Combination Use of Molecular Dynamics Simulation, Residue Interaction Network, and Substrate Envelope Analysis. J. Chem. Inf. Model. 54(2): 621-633 (2014) - 2013
- [j27]Weiwei Xue
Exploring the Molecular Mechanism of Cross-Resistance to HIV-1 Integrase Strand Transfer Inhibitors by Molecular Dynamics Simulation and Residue Interaction Network Analysis. J. Chem. Inf. Model. 53(1): 210-222 (2013) - 2012
- [j26]Chengqi Wang, Lili Xi, Shuyan Li, Huanxiang Liu
A sequence-based computational model for the prediction of the solvent accessible surface area for α-helix and β-barrel transmembrane residues. J. Comput. Chem. 33(1): 11-17 (2012) - [j25]Weiwei Xue
Molecular mechanism of HIV-1 integrase-vDNA interactions and strand transfer inhibitor action: A molecular modeling perspective. J. Comput. Chem. 33(5): 527-536 (2012) - 2011
- [j24]Shuyan Li, Lili Xi, Jiazhong Li, Chengqi Wang, Beilei Lei, Yulin Shen, Huanxiang Liu
In silico prediction of deleterious single amino acid polymorphisms from amino acid sequence. J. Comput. Chem. 32(7): 1211-1216 (2011) - [j23]Juan Du, Huijun Sun, Lili Xi, Jiazhong Li, Ying Yang, Huanxiang Liu
Molecular modeling study of checkpoint kinase 1 inhibitors by multiple docking strategies and prime/MM-GBSA calculation. J. Comput. Chem. 32(13): 2800-2809 (2011) - [j22]Ying Yang, Jin Qin, Huanxiang Liu
Molecular Dynamics Simulation, Free Energy Calculation and Structure-Based 3D-QSAR Studies of B-RAF Kinase Inhibitors. J. Chem. Inf. Model. 51(3): 680-692 (2011) - [j21]Ying Yang, Yulin Shen, Huanxiang Liu
Molecular Dynamics Simulation and Free Energy Calculation Studies of the Binding Mechanism of Allosteric Inhibitors with p38α MAP Kinase. J. Chem. Inf. Model. 51(12): 3235-3246 (2011) - 2010
- [j20]Lili Xi, Juan Du, Shuyan Li, Jiazhong Li, Huanxiang Liu
A combined molecular modeling study on gelatinases and their potent inhibitors. J. Comput. Chem. 31(1): 24-42 (2010) - [j19]Jiazhong Li, Shuyan Li, Beilei Lei, Huanxiang Liu
A new strategy to improve the predictive ability of the local lazy regression and its application to the QSAR study of melanin-concentrating hormone receptor 1 antagonists. J. Comput. Chem. 31(5): 973-985 (2010) - [j18]Juan Du, Lili Xi, Beilei Lei, Jing Lu, Jiazhong Li, Huanxiang Liu
Structure-based quantitative structure-activity relationship studies of checkpoint kinase 1 inhibitors. J. Comput. Chem. 31(15): 2783-2793 (2010) - [j17]Iurii Sushko, Sergii Novotarskyi, Robert Körner, Anil Kumar Pandey, Artem Cherkasov, Jiazhong Li, Paola Gramatica
Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set. J. Chem. Inf. Model. 50(12): 2094-2111 (2010)
2000 – 2009
- 2009
- [j16]Shuyan Li, Lili Xi, Chengqi Wang, Jiazhong Li, Beilei Lei, Huanxiang Liu
A novel method for protein-ligand binding affinity prediction and the related descriptors exploration. J. Comput. Chem. 30(6): 900-909 (2009) - 2008
- [j15]Beilei Lei, Juan Du, Shuyan Li, Huanxiang Liu
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of thiazolone derivatives as hepatitis C virus NS5B polymerase allosteric inhibitors. J. Comput. Aided Mol. Des. 22(10): 711-725 (2008) - [j14]Jiazhong Li, Beilei Lei, Huanxiang Liu
QSAR study of malonyl-CoA decarboxylase inhibitors using GA-MLR and a new strategy of consensus modeling. J. Comput. Chem. 29(16): 2636-2647 (2008) - 2006
- [j13]Igor V. Tetko
Benchmarking of Linear and Nonlinear Approaches for Quantitative Structure-Property Relationship Studies of Metal Complexation with Ionophores. J. Chem. Inf. Model. 46(2): 808-819 (2006) - 2005
- [j12]Huanxiang Liu
The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machine. J. Comput. Aided Mol. Des. 19(1): 33-46 (2005) - [j11]Huanxiang Liu
Prediction of the tissue/blood partition coefficients of organic compounds based on the molecular structure using least-squares support vector machines. J. Comput. Aided Mol. Des. 19(7): 499-508 (2005) - 2004
- [j10]Huanxiang Liu
QSAR and classification models of a novel series of COX-2 selective inhibitors: 1, 5-diarylimidazoles based on support vector machines. J. Comput. Aided Mol. Des. 18(6): 389-399 (2004) - [j9]Huanxiang Liu
Prediction of the Isoelectric Point of an Amino Acid Based on GA-PLS and SVMs. J. Chem. Inf. Model. 44(1): 161-167 (2004) - [j8]C. X. Xue, Ruisheng Zhang
An Accurate QSPR Study of O-H Bond Dissociation Energy in Substituted Phenols Based on Support Vector Machines. J. Chem. Inf. Model. 44(2): 669-677 (2004) - [j7]Xiaojun Yao, Annick Panaye, Jean-Pierre Doucet, Ruisheng Zhang
Comparative Study of QSAR/QSPR Correlations Using Support Vector Machines, Radial Basis Function Neural Networks, and Multiple Linear Regression. J. Chem. Inf. Model. 44(4): 1257-1266 (2004) - [j6]C. X. Xue, Ruisheng Zhang
QSAR Models for the Prediction of Binding Affinities to Human Serum Albumin Using the Heuristic Method and a Support Vector Machine. J. Chem. Inf. Model. 44(5): 1693-1700 (2004) - [j5]Huanxiang Liu
Quantitative Prediction of logk of Peptides in High-Performance Liquid Chromatography Based on Molecular Descriptors by Using the Heuristic Method and Support Vector Machine. J. Chem. Inf. Model. 44(6): 1979-1986 (2004) - 2003
- [j4]Huanxiang Liu
Diagnosing Breast Cancer Based on Support Vector Machines. J. Chem. Inf. Comput. Sci. 43(3): 900-907 (2003) - [j3]Huanxiang Liu
QSAR Study of Ethyl 2-[(3-Methyl-2, 5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl) pyrimidine-5-carboxylate: An Inhibitor of AP-1 and NF-B Mediated Gene Expression Based on Support Vector Machines. J. Chem. Inf. Comput. Sci. 43(4): 1288-1296 (2003) - 2002
- [j2]Xiaojun Yao, Xiaoyun Zhang, Ruisheng Zhang
Radial Basis Function Neural Network Based QSPR for the Prediction of Critical Pressures of Substituted Benzenes. Comput. Chem. 26(2): 159-169 (2002) - 2001
- [j1]Xiaojun Yao, Xiaoyun Zhang, Ruisheng Zhang
Prediction of Enthalpy of Alkanes by the Use of Radial Basis Function Neural Networks. Comput. Chem. 25(5): 475-482 (2001)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-08 20:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: