Search Results - "Fu, Xiangzheng"

StableDNAm: towards a stable and efficient model for predicting DNA methylation based on adaptive feature correction learning by Zhuo, Linlin, Wang, Rui, Fu, Xiangzheng, Yao, Xiaojun

“…DNA methylation, instrumental in numerous life processes, underscores the paramount importance of its accurate prediction. Recent studies suggest that deep…”
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An efficient model for predicting human diseases through miRNA based on multiple-types of contrastive learning by Liao, Qingquan, Fu, Xiangzheng, Zhuo, Linlin, Chen, Hao

“…Multiple studies have demonstrated that microRNA (miRNA) can be deeply involved in the regulatory mechanism of human microbiota, thereby inducing disease…”
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Joint masking and self-supervised strategies for inferring small molecule-miRNA associations by Zhou, Zhecheng, Zhuo, Linlin, Fu, Xiangzheng, Lv, Juan, Zou, Quan, Qi, Ren

“…Inferring small molecule-miRNA associations (MMAs) is crucial for revealing the intricacies of biological processes and disease mechanisms. Deep learning,…”
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DrugReAlign: a multisource prompt framework for drug repurposing based on large language models by Wei, Jinhang, Zhuo, Linlin, Fu, Xiangzheng, Zeng, XiangXiang, Wang, Li, Zou, Quan, Cao, Dongsheng

“…Drug repurposing is a promising approach in the field of drug discovery owing to its efficiency and cost-effectiveness. Most current drug repurposing models…”
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Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations by Du, Zhenya, Tu, Gao, Gong, Yaguo, Fu, Xiangzheng, Wu, Qibiao, Long, Guankui

“…The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRAS ) mutation, a prevalent oncogenic driver in cancer,…”
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Fusion of multi-source relationships and topology to infer lncRNA-protein interactions by Zhang, Xinyu, Liu, Mingzhe, Li, Zhen, Zhuo, Linlin, Fu, Xiangzheng, Zou, Quan

“…Long non-coding RNAs (lncRNAs) are important factors involved in biological regulatory networks. Accurately predicting lncRNA-protein interactions (LPIs) is…”
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DlncRNALoc: A discrete wavelet transform-based model for predicting lncRNA subcellular localization by Fu, Xiangzheng, Chen, Yifan, Tian, Sha

“…The prediction of long non-coding RNA (lncRNA) subcellular localization is essential to the understanding of its function and involvement in cellular…”
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Improved Pre-miRNAs Identification Through Mutual Information of Pre-miRNA Sequences and Structures by Fu, Xiangzheng, Zhu, Wen, Cai, Lijun, Liao, Bo, Peng, Lihong, Chen, Yifan, Yang, Jialiang

“…Playing critical roles as post-transcriptional regulators, microRNAs (miRNAs) are a family of short non-coding RNAs that are derived from longer transcripts…”
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MILNP: Plant lncRNA-miRNA Interaction Prediction Based on Improved Linear Neighborhood Similarity and Label Propagation by Cai, Lijun, Gao, Mingyu, Ren, Xuanbai, Fu, Xiangzheng, Xu, Junlin, Wang, Peng, Chen, Yifan

“…Knowledge of the interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) is the basis of understanding various biological activities and…”
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Active Semisupervised Model for Improving the Identification of Anticancer Peptides by Cai, Lijun, Wang, Li, Fu, Xiangzheng, Zeng, Xiangxiang

“…Cancer is one of the most dangerous threats to human health. Accurate identification of anticancer peptides (ACPs) is valuable for the development and design…”
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Improved DNA-Binding Protein Identification by Incorporating Evolutionary Information Into the Chou's PseAAC by Fu, Xiangzheng, Zhu, Wen, Liao, Bo, Cai, Lijun, Peng, Lihong, Yang, Jialiang

“…DNA-binding proteins play critical roles in various cellular biological processes, such as gene expression and transcription. However, the experimental methods…”
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Prediction of lncRNA-Protein Interactions via the Multiple Information Integration by Chen, Yifan, Fu, Xiangzheng, Li, Zejun, Peng, Li, Zhuo, Linlin

“…The long non-coding RNA (lncRNA)-protein interaction plays an important role in the post-transcriptional gene regulation, such as RNA splicing, translation,…”
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Improved Prediction of Cell-Penetrating Peptides via Effective Orchestrating Amino Acid Composition Feature Representation by Fu, Xiangzheng, Ke, Lixia, Cai, Lijun, Chen, Xiangtao, Ren, Xuanbai, Gao, Mingyu

“…Cell-penetrating peptides (CPPs) promote the transport of pharmacologically active molecules, such as nanoparticles, plasmid DNA and short interfering RNA…”
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Integration of single sample and population analysis for understanding immune evasion mechanisms of lung cancer by Li, Xiong, Meng, Xu, Chen, Haowen, Fu, Xiangzheng, Wang, Peng, Chen, Xia, Gu, Changlong, Zhou, Juan

“…A deep understanding of the complex interaction mechanism between the various cellular components in tumor microenvironment (TME) of lung adenocarcinoma (LUAD)…”
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Identifying protein complexes by reducing noise in interaction networks by Liao, Bo, Fu, Xiangzheng, Cai, Lijun, Chen, Haowen

“…Identifying protein complexes in protein-protein interaction (PPI) networks is a fundamental problem in computational biology. High-throughput experimental…”
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Toward better drug discovery with knowledge graph by Zeng, Xiangxiang, Tu, Xinqi, Liu, Yuansheng, Fu, Xiangzheng, Su, Yansen

“…Drug discovery is the process of new drug identification. This process is driven by the increasing data from existing chemical libraries and data banks. The…”
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StackCPPred: a stacking and pairwise energy content-based prediction of cell-penetrating peptides and their uptake efficiency by Fu, Xiangzheng, Cai, Lijun, Zeng, Xiangxiang, Zou, Quan

“…Abstract Motivation Cell-penetrating peptides (CPPs) are a vehicle for transporting into living cells pharmacologically active molecules, such as short…”
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iEnhancer-XG: interpretable sequence-based enhancers and their strength predictor by Cai, Lijun, Ren, Xuanbai, Fu, Xiangzheng, Peng, Li, Gao, Mingyu, Zeng, Xiangxiang

“…Abstract Motivation Enhancers are non-coding DNA fragments with high position variability and free scattering. They play an important role in controlling gene…”
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Drug repositioning based on the heterogeneous information fusion graph convolutional network by Cai, Lijun, Lu, Changcheng, Xu, Junlin, Meng, Yajie, Wang, Peng, Fu, Xiangzheng, Zeng, Xiangxiang, Su, Yansen

“…In silico reuse of old drugs (also known as drug repositioning) to treat common and rare diseases is increasingly becoming an attractive proposition because it…”
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Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs by Zhou, Zhecheng, Zhuo, Linlin, Fu, Xiangzheng, Zou, Quan

“…Exploring microbial stress responses to drugs is crucial for the advancement of new therapeutic methods. While current artificial intelligence methodologies…”
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