于彬｜青岛科技大学｜学者主页

2026

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug–Drug Interaction Prediction

Zhuo Chen, Xiaofeng Man, Chao Sun, Yuanyuan Ji, Xin Gao, Bin Yu

IEEE Transactions on Neural Networks and Learning Systems

DOI

2026

ConMGIN: Interpretable multilayer GIN-Bayesian framework for spatial domain analysis

Jie Li, Farong Liu, Haoyang Lv, Sheng Ren, Xin Gao, Bin Yu

Neural Networks

DOI

2026

Multi-branch molecular feature fusion for molecular property prediction

Chao Sun, Na Li, Kairui Lyu, Zihe Liu, Junwei Du, Zhuo Chen, Bin Yu

Engineering Applications of Artificial Intelligence

DOI

2026

Multimodal Information-Driven Heterogeneous Graph Neural Networks for Protein–Ligand Binding Affinity Prediction

Bin Yu, Shiyue He, Y Li, Xin Gao, Defu Lian

Journal of Chemical Information and Modeling

DOI

2026

FG-PromptNet: Cross-modal prompt learning for explainable molecular property prediction

Chao Sun, Xiaofeng Man, Na Li, Zihe Liu, Zhuo Chen, Bin Yu

Computational Biology and Chemistry

DOI

2026

LDM-DTI: A multimodal framework integrating pretrained language models and geometric graph networks for interpretable drug-target interaction prediction

Yuanyuan Ji, Zhuo Chen, Zhihan Liu, Xiaofeng Man, Junwei Du, Bin Yu

Expert Systems with Applications

DOI

2026

MTEGDRP: Interpretable Molecular Self-Attention Transformer and Equivariant Graph Neural Network Based on Multi-Omics Fusion for Drug Response Prediction in Cancer Cell Lines

Zhihan Liu, Kairui Lyu, Ya Li, Xinghui Sun, Xin Gao, Bin Yu

Journal of Medicinal Chemistry

DOI

2026

PTET-DDI: Dual-Channel Drug–Drug Interaction Prediction with a Pre-Trained Language Model and Equivariant Graph Transformer

Xiaofeng Man, Chao Sun, Zhuo Chen, Yuanyuan Ji, Junwei Du, Bin Yu

ACS Synthetic Biology

DOI

2025

基于移动倒置瓶颈和迁移学习的乳腺癌组织病理图像二值分类

臧敏，曹源，丰艳，于彬

《青岛科技大学学报(自然科学版)》

DOI

2025

基于多头注意力机制和双向长短时记忆网络的DNA结合蛋白和RNA结合蛋白预测

韦芹芹，于彬，张岩

《青岛科技大学学报(自然科学版)》

DOI

2025

MSN-DTA: A multi-scale node adaptive graph neural network for interpretable drug-target binding affinity prediction

Jianxin Wang, Pengju Ding, Yongxin Zhu, Xin Gao, Xu Yu, Bin Yu

Knowledge-Based Systems

DOI

2025

BiVAE-CPI: An Interpretable Generative Model Using a Bilateral Variational Autoencoder for Compound–Protein Interaction Prediction

Yongxin Zhu, Jianxin Wang, Shiyue He, Xinghui Sun, Jiangning Song, Bin Yu

Journal of Chemical Information and Modeling

DOI

2025

Exploring the Latent Information in Spatial Transcriptomics Data via Multi‐View Graph Convolutional Network Based on Implicit Contrastive Learning

Sheng Ren, Xingyu Liao, Farong Liu, Jie Li, Xin Gao, Bin Yu

Advanced Science

DOI

2025

SGTB: A graph representation learning model combining transformer and BERT for optimizing gene expression analysis in spatial transcriptomics data

Farong Liu, Sheng Ren, Jie Li, Haoyang Lv, Fenghui Jiang, Bin Yu

Computational Biology and Chemistry

DOI

2025

DTF-diffusion: A 3D equivariant diffusion generation model based on ligand-target information fusion

Jianxin Wang, Yongxin Zhu, Yushuang Liu, Bin Yu

Computational Biology and Chemistry

DOI

2025

Enhanced Integration of Single-Cell Multi-Omics Data Using Graph Attention Networks

Xingyu Liao, Yanyan Li, Shuangyi Li, Long Wen, Xingyi Li, Bin Yu

ACS Synthetic Biology

DOI

2024

DeepUTF: Locating transcription factor binding sites via interpretable dual-channel encoder-decoder structure

Pengju Ding, Jianxin Wang, Shiyue He, Xin Gao, Xu Yu, Bin Yu

Pattern Recognition

DOI

2024

Dynamic weighted knowledge distillation for brain tumor segmentation

Dianlong An, Panpan Liu, Yan Feng, Pengju Ding, Weifeng Zhou, Bin Yu

Pattern Recognition

DOI

2024

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders

Yifei Wang, Pengju Ding, Congjing Wang, Shiyue He, Xin Gao, Bin Yu

IEEE Transactions on Neural Networks and Learning Systems

DOI

2024

Res-GCN: Identification of protein phosphorylation sites using graph convolutional network and residual network

Minghui Wang, Jihua Jia, Fei Xu, Hongyan Zhou, Yushuang Liu, Bin Yu

Computational Biology and Chemistry

DOI

2024

A weighted integration method based on graph representation learning for drug repositioning

Haojie Lian, Pengju Ding, Chao Yu, Xinyu Zhang, Guozhu Liu, Bin Yu

Applied Soft Computing

DOI

2024

ECA-PHV: Predicting human-virus protein-protein interactions through an interpretable model of effective channel attention mechanism

Minghui Wang, Jiali Lai, Jihua Jia, Fei Xu, Hongyan Zhou, Bin Yu

Chemometrics and Intelligent Laboratory Systems

DOI

2024

AntiCVP-Deep: Identify anti-coronavirus peptides between different negative datasets based on self-attention and deep learning

Yan Lu, Minghui Wang, Hongyan Zhou, Yushuang Liu, Bin Yu

Biomedical Signal Processing and Control

DOI

2024

ML-FGAT: Identification of multi-label protein subcellular localization by interpretable graph attention networks and feature-generative adversarial networks

Congjing Wang, Yifei Wang, Pengju Ding, Shan Li, Xu Yu, Bin Yu

Computers in Biology and Medicine

DOI

2023

DRBPPred-GAT: Accurate prediction of DNA-binding proteins and RNA-binding proteins based on graph multi-head attention network

Xinyu Zhang, Yifei Wang, Qinqin Wei, Shiyue He, Adil Salhi, Bin Yu

Knowledge-Based Systems

DOI

2023

DAUnet: A U-shaped network combining deep supervision and attention for brain tumor segmentation

Yan Feng, Yuan Cao, Dianlong An, Panpan Liu, Xingyu Liao, Bin Yu

Knowledge-Based Systems

DOI

2023

DeepSTF: predicting transcription factor binding sites by interpretable deep neural networks combining sequence and shape

Pengju Ding, Yifei Wang, Xinyu Zhang, Xin Gao, Guozhu Liu, Bin Yu

Briefings in Bioinformatics

DOI

2023

DBGRU-SE: predicting drug–drug interactions based on double BiGRU and squeeze-and-excitation attention mechanism

Mingxiang Zhang, Hongli Gao, Xin Liao, Baoxing Ning, Haiming Gu, Bin Yu

Briefings in Bioinformatics

DOI

2023

RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network

Yifei Wang, Xue Wang, Cheng Chen, Hongli Gao, Adil Salhi, Xin Gao, Bin Yu

Pattern Recognition

DOI

2023

A universal framework for single-cell multi-omics data integration with graph convolutional networks

Hongli Gao, Bin Zhang, Long Liu, Shan Li, Xin Gao, Bin Yu

Briefings in Bioinformatics

DOI

2023

Cooperation of local features and global representations by a dual-branch network for transcription factor binding sites prediction

Yutong Yu, Pengju Ding, Hongli Gao, Guozhu Liu, Fa Zhang, Bin Yu

Briefings in Bioinformatics

DOI

2023

BiGRUD-SA: Protein S-sulfenylation sites prediction based on BiGRU and self-attention

Tingting Zhang, Tingting Zhang, Jihua Jia, Cheng Chen, Yaqun Zhang, Bin Yu

Computers in Biology and Medicine

DOI

2023

DE-MHAIPs: Identification of SARS-CoV-2 phosphorylation sites based on differential evolution multi-feature learning and multi-head attention mechanism

Minghui Wang, Yan Lu, Jihua Jia, Jiali Lai, Hongyan Zhou, Bin Yu

Computers in Biology and Medicine

DOI

2022

scBKAP: A Clustering Model for Single-Cell RNA-Seq Data Based on Bisecting K-Means

Xiaolin Wang, Hongli Gao, Ren Qi, Ruiqing Zheng, Xin Gao, Bin Yu

IEEE Transactions on Computational Biology and Bioinformatics

DOI

2022

DEEPStack-RBP: Accurate identification of RNA-binding proteins based on autoencoder feature selection and deep stacking ensemble classifier

Qinqin Wei, Qingmei Zhang, Hongli Gao, Tao Song, Adil Salhi, Bin Yu

Knowledge-Based Systems

DOI

2022

Malsite-Deep: Prediction of protein malonylation sites through deep learning and multi-information fusion based on NearMiss-2 strategy

Minghui Wang, Lili Song, Yaqun Zhang, Hongli Gao, Yan Lu, Bin Yu

Knowledge-Based Systems

DOI

2022

Prediction of protein-protein interactions based on ensemble residual convolutional neural network

Hongli Gao, Cheng Chen, Shuangyi Li, Congjing Wang, Weifeng Zhou, Bin Yu

Computers in Biology and Medicine

DOI

2022

MBANet: A 3D convolutional neural network with multi-branch attention for brain tumor segmentation from MRI images

Yuan Jie Cao, Weifeng Zhou, Min Zang, Dianlong An, Yan Feng, Bin Yu

Biomedical Signal Processing and Control

DOI

2022

MTDCNet: A 3D multi-threading dilated convolutional network for brain tumor automatic segmentation

Wankun Chen, Weifeng Zhou, Ling Xi Zhu, Yuan Cao, Haiming Gu, Bin Yu

Journal of Biomedical Informatics

DOI

2022

RPI-MDLStack: Predicting RNA–protein interactions through deep learning with stacking strategy and LASSO

Bin Yu, Xue Wang, Yaqun Zhang, Hongli Gao, Yifei Wang, Yushuang Liu, Xin Gao

Applied Soft Computing

DOI

2022

Identification of DNA modification sites based on elastic net and bidirectional gated recurrent unit with convolutional neural network

Bin Yu, Yaqun Zhang, Xue Wang, Hongli Gao, Jianqiang Sun, Xin Gao

Biomedical Signal Processing and Control

DOI

2022

StackRAM: a cross-species method for identifying RNA N6-methyladenosine sites based on stacked ensemble

Yaqun Zhang, Zhaomin Yu, Bin Yu, Xue Wang, Hongli Gao, Jianqiang Sun, Shuangyi Li

Chemometrics and Intelligent Laboratory Systems

DOI

2021

基于深度学习的DNA N4-甲基胞嘧啶位点预测

张亚群，于彬

《数学建模及其应用》

DOI

2021

Predicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier

Yushuang Liu, Shuping Jin, Hongli Gao, Xue Wang, Congjing Wang, Weifeng Zhou, Bin Yu

Bioinformatics

DOI

2021

DeepStack-DTIs: Predicting Drug–Target Interactions Using LightGBM Feature Selection and Deep-Stacked Ensemble Classifier

Yan Zhang, Zhiwen Jiang, Cheng Chen, Qinqin Wei, Haiming Gu, Bin Yu

Interdisciplinary Sciences Computational Life Sciences

DOI

2021

DNN-DTIs: Improved drug-target interactions prediction using XGBoost feature selection and deep neural network

Cheng Chen, Shi Han, Zhiwen Jiang, Adil Salhi, Ruixin Chen, Xuefeng Cui, Bin Yu

Computers in Biology and Medicine

DOI

2021

MSMANet: A multi-scale mesh aggregation network for brain tumor segmentation

Yan Zhang, Yao Lu, Wankun Chen, Yankang Chang, Haiming Gu, Bin Yu

Applied Soft Computing

DOI

2021

Prediction of protein ubiquitination sites via multi-view features based on eXtreme gradient boosting classifier

Yushuang Liu, Shuping Jin, Lili Song, Han Yu, Bin Yu

Journal of Molecular Graphics and Modelling

DOI

2021

Prediction of protein-protein interaction sites through eXtreme gradient boosting with kernel principal component analysis

Xue Wang, Yaqun Zhang, Bin Yu, Adil Salhi, Ruixin Chen, Lin Wang, Zengfeng Liu

Computers in Biology and Medicine

DOI

2021

Fertility-LightGBM: A fertility-related protein prediction model by multi-information fusion and light gradient boosting machine

Minghui Wang, Lingling Yue, Xinhua Yang, Xiaolin Wang, Han Yu, Bin Yu

Biomedical Signal Processing and Control

DOI

2020

GTB-PPI: Predict Protein–Protein Interactions Based on L1-Regularized Logistic Regression and Gradient Tree Boosting

Bin Yu, Cheng Chen, Hongyan Zhou, Bingqiang Liu, Qin Ma

Genomics Proteomics & Bioinformatics

DOI

2020

MpsLDA-ProSVM: Predicting multi-label protein subcellular localization by wMLDAe dimensionality reduction and ProSVM classifier

Qi Zhang, Shan Li, Qingmei Zhang, Yandan Zhang, Han Yu, Ruixin Chen, Bin Yu

Chemometrics and Intelligent Laboratory Systems

DOI

2020

StackPDB: Predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier

Qingmei Zhang, Peishun Liu, Xue Wang, Yaqun Zhang, Han Yu, Bin Yu

Applied Soft Computing

DOI

2020

DeepMal: Accurate prediction of protein malonylation sites by deep neural networks

Minghui Wang, Xiaowen Cui, Shan Li, Xinhua Yang, Anjun Ma, Yusen Zhang, Bin Yu

Chemometrics and Intelligent Laboratory Systems

DOI

2020

DMLDA-LocLIFT: Identification of multi-label protein subcellular localization using DMLDA dimensionality reduction and LIFT classifier

Qi Zhang, Shan Li, Bin Yu, Qingmei Zhang, Yu Han, Yan Zhang, Qin Ma

Chemometrics and Intelligent Laboratory Systems

DOI

2020

Prediction of protein crotonylation sites through LightGBM classifier based on SMOTE and elastic net

Yaning Liu, Zhaomin Yu, Cheng Chen, Yu Han, Bin Yu

Analytical Biochemistry

DOI

2020

Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier

Cheng Chen, Qingmei Zhang, Bin Yu, Zhaomin Yu, Patrick J. Lawrence, Qin Ma, Yan Zhang

Computers in Biology and Medicine

DOI

2020

DNNAce: Prediction of prokaryote lysine acetylation sites through deep neural networks with multi-information fusion

Bin Yu, Zhaomin Yu, Cheng Chen, Anjun Ma, Bingqiang Liu, Baoguang Tian, Qin Ma

Chemometrics and Intelligent Laboratory Systems

DOI

2020

SulSite-GTB: identification of protein S-sulfenylation sites by fusing multiple feature information and gradient tree boosting

Minghui Wang, Xiaowen Cui, Bin Yu, Cheng Chen, Qin Ma, Hongyan Zhou

Neural Computing and Applications

DOI

2020

Prediction of Extracellular Matrix Proteins by Fusing Multiple Feature Information, Elastic Net, and Random Forest Algorithm

Minghui Wang, Lingling Yue, Xiaowen Cui, Cheng Chen, Hongyan Zhou, Qin Ma, Bin Yu

Mathematics

DOI

2019

SubMito-XGBoost: predicting protein submitochondrial localization by fusing multiple feature information and eXtreme gradient boosting

Bin Yu, Wenying Qiu, Cheng Chen, Anjun Ma, Jing Jiang, Hongyan Zhou, Qin Ma

Bioinformatics

DOI

2019

Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier

Jianying Lin, Hui Chen, Shan Li, Yushuang Liu, Xuan Li, Bin Yu

Artificial Intelligence in Medicine

DOI

2019

RBPro-RF: Use Chou’s 5-steps rule to predict RNA-binding proteins via random forest with elastic net

Xiaomeng Sun, Tingyu Jin, Cheng Chen, Xiaowen Cui, Qin Ma, Bin Yu

Chemometrics and Intelligent Laboratory Systems

DOI

2019

SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso

Yanhao Huo, Lihui Xin, Chuanze Kang, Minghui Wang, Qin Ma, Bin Yu

Journal of Theoretical Biology

DOI

2019

LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion

Cheng Chen, Qingmei Zhang, Qin Ma, Bin Yu

Chemometrics and Intelligent Laboratory Systems

DOI

2018

Protein–protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique

Xiaoying Wang, Bin Yu, Anjun Ma, Cheng Chen, Bingqiang Liu, Qin Ma

Bioinformatics

DOI

2018

Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure

Shi Han, Simin Liu, Junqi Chen, Xuan Li, Qin Ma, Bin Yu

Genomics

DOI

2018

Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine

Chuanze Kang, Yanhao Huo, Lihui Xin, Baoguang Tian, Bin Yu

Journal of Theoretical Biology

DOI

2018

UbiSitePred: A novel method for improving the accuracy of ubiquitination sites prediction by using LASSO to select the optimal Chou's pseudo components

Xiaowen Cui, Zhaomin Yu, Bin Yu, Minghui Wang, Baoguang Tian, Qin Ma

Chemometrics and Intelligent Laboratory Systems

DOI

2018

Predicting protein–protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach

Baoguang Tian, Xue Wu, Cheng Chen, Wenying Qiu, Qin Ma, Bin Yu

Journal of Theoretical Biology

DOI

2018

Prediction of subcellular location of apoptosis proteins by incorporating PsePSSM and DCCA coefficient based on LFDA dimensionality reduction

Bin Yu, Shan Li, Wenying Qiu, Minghui Wang, Junwei Du, Yusen Zhang, Xing Chen

BMC Genomics

DOI

2018

Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition

Wenying Qiu, Shan Li, Xiaowen Cui, Zhaomin Yu, Minghui Wang, Junwei Du, Yanjun Peng, Bin Yu

Journal of Theoretical Biology

DOI

2017

Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

Bin Yu, Shan Li, Wen-Ying Qiu, Cheng Chen, Ruixin Chen, Lei Wang, Minghui Wang, Yan Zhang

Oncotarget

DOI

2017

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method

Bin Yu, Jiameng Xu, Shan Li, Cheng Chen, Ruixin Chen, Lei Wang, Yan Zhang, Minghui Wang

Oncotarget

DOI

2017

Prediction of protein structural class for low-similarity sequences using Chou’s pseudo amino acid composition and wavelet denoising

Bin Yu, Lifeng Lou, Shan Li, Yusen Zhang, Wenying Qiu, Xue Wu, Minghui Wang, Baoguang Tian

Journal of Molecular Graphics and Modelling

DOI

2014

一种改进的蚁群聚类的图像分割

于彬

《电子测试》

2014

基于蚁群算法的图像分割研究

于彬

《兰州交通大学》

2010

A Prediction Approach of Transmembrane Helical Segments in Membrane Proteins Based on Wavelet Transform

Bin Yu, Yan Zhang

DOI

2009

基于支持向量机的肿瘤基因数据挖掘

于彬

《科学技术与工程》

精选作品

期刊论文

A Unified Differential Denoising Learning Framework With a Pre-Trained Model and Fuzzy Graph Networks for Drug–Drug Interaction Prediction

ConMGIN: Interpretable multilayer GIN-Bayesian framework for spatial domain analysis

Multi-branch molecular feature fusion for molecular property prediction

Multimodal Information-Driven Heterogeneous Graph Neural Networks for Protein–Ligand Binding Affinity Prediction

FG-PromptNet: Cross-modal prompt learning for explainable molecular property prediction

LDM-DTI: A multimodal framework integrating pretrained language models and geometric graph networks for interpretable drug-target interaction prediction

MTEGDRP: Interpretable Molecular Self-Attention Transformer and Equivariant Graph Neural Network Based on Multi-Omics Fusion for Drug Response Prediction in Cancer Cell Lines

PTET-DDI: Dual-Channel Drug–Drug Interaction Prediction with a Pre-Trained Language Model and Equivariant Graph Transformer

基于移动倒置瓶颈和迁移学习的乳腺癌组织病理图像二值分类

基于多头注意力机制和双向长短时记忆网络的DNA结合蛋白和RNA结合蛋白预测

MSN-DTA: A multi-scale node adaptive graph neural network for interpretable drug-target binding affinity prediction

BiVAE-CPI: An Interpretable Generative Model Using a Bilateral Variational Autoencoder for Compound–Protein Interaction Prediction

Exploring the Latent Information in Spatial Transcriptomics Data via Multi‐View Graph Convolutional Network Based on Implicit Contrastive Learning

SGTB: A graph representation learning model combining transformer and BERT for optimizing gene expression analysis in spatial transcriptomics data

DTF-diffusion: A 3D equivariant diffusion generation model based on ligand-target information fusion

Enhanced Integration of Single-Cell Multi-Omics Data Using Graph Attention Networks

DeepUTF: Locating transcription factor binding sites via interpretable dual-channel encoder-decoder structure

Dynamic weighted knowledge distillation for brain tumor segmentation

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders

Res-GCN: Identification of protein phosphorylation sites using graph convolutional network and residual network

A weighted integration method based on graph representation learning for drug repositioning

ECA-PHV: Predicting human-virus protein-protein interactions through an interpretable model of effective channel attention mechanism

AntiCVP-Deep: Identify anti-coronavirus peptides between different negative datasets based on self-attention and deep learning

ML-FGAT: Identification of multi-label protein subcellular localization by interpretable graph attention networks and feature-generative adversarial networks

DRBPPred-GAT: Accurate prediction of DNA-binding proteins and RNA-binding proteins based on graph multi-head attention network

DAUnet: A U-shaped network combining deep supervision and attention for brain tumor segmentation

DeepSTF: predicting transcription factor binding sites by interpretable deep neural networks combining sequence and shape

DBGRU-SE: predicting drug–drug interactions based on double BiGRU and squeeze-and-excitation attention mechanism

RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network

A universal framework for single-cell multi-omics data integration with graph convolutional networks

Cooperation of local features and global representations by a dual-branch network for transcription factor binding sites prediction

BiGRUD-SA: Protein S-sulfenylation sites prediction based on BiGRU and self-attention

DE-MHAIPs: Identification of SARS-CoV-2 phosphorylation sites based on differential evolution multi-feature learning and multi-head attention mechanism

scBKAP: A Clustering Model for Single-Cell RNA-Seq Data Based on Bisecting K-Means

DEEPStack-RBP: Accurate identification of RNA-binding proteins based on autoencoder feature selection and deep stacking ensemble classifier

Malsite-Deep: Prediction of protein malonylation sites through deep learning and multi-information fusion based on NearMiss-2 strategy

Prediction of protein-protein interactions based on ensemble residual convolutional neural network

MBANet: A 3D convolutional neural network with multi-branch attention for brain tumor segmentation from MRI images

MTDCNet: A 3D multi-threading dilated convolutional network for brain tumor automatic segmentation

RPI-MDLStack: Predicting RNA–protein interactions through deep learning with stacking strategy and LASSO

Identification of DNA modification sites based on elastic net and bidirectional gated recurrent unit with convolutional neural network

StackRAM: a cross-species method for identifying RNA N6-methyladenosine sites based on stacked ensemble

基于深度学习的DNA N4-甲基胞嘧啶位点预测

Predicting the multi-label protein subcellular localization through multi-information fusion and MLSI dimensionality reduction based on MLFE classifier

DeepStack-DTIs: Predicting Drug–Target Interactions Using LightGBM Feature Selection and Deep-Stacked Ensemble Classifier

DNN-DTIs: Improved drug-target interactions prediction using XGBoost feature selection and deep neural network

MSMANet: A multi-scale mesh aggregation network for brain tumor segmentation

Prediction of protein ubiquitination sites via multi-view features based on eXtreme gradient boosting classifier

Prediction of protein-protein interaction sites through eXtreme gradient boosting with kernel principal component analysis

Fertility-LightGBM: A fertility-related protein prediction model by multi-information fusion and light gradient boosting machine

GTB-PPI: Predict Protein–Protein Interactions Based on L1-Regularized Logistic Regression and Gradient Tree Boosting

MpsLDA-ProSVM: Predicting multi-label protein subcellular localization by wMLDAe dimensionality reduction and ProSVM classifier

StackPDB: Predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier

DeepMal: Accurate prediction of protein malonylation sites by deep neural networks

DMLDA-LocLIFT: Identification of multi-label protein subcellular localization using DMLDA dimensionality reduction and LIFT classifier

Prediction of protein crotonylation sites through LightGBM classifier based on SMOTE and elastic net

Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier

DNNAce: Prediction of prokaryote lysine acetylation sites through deep neural networks with multi-information fusion

SulSite-GTB: identification of protein S-sulfenylation sites by fusing multiple feature information and gradient tree boosting

Prediction of Extracellular Matrix Proteins by Fusing Multiple Feature Information, Elastic Net, and Random Forest Algorithm

SubMito-XGBoost: predicting protein submitochondrial localization by fusing multiple feature information and eXtreme gradient boosting

Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier

RBPro-RF: Use Chou’s 5-steps rule to predict RNA-binding proteins via random forest with elastic net

SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso

LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion

Protein–protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique

Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure

Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine

UbiSitePred: A novel method for improving the accuracy of ubiquitination sites prediction by using LASSO to select the optimal Chou's pseudo components

Predicting protein–protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach

Prediction of subcellular location of apoptosis proteins by incorporating PsePSSM and DCCA coefficient based on LFDA dimensionality reduction

Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition

Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method

Prediction of protein structural class for low-similarity sequences using Chou’s pseudo amino acid composition and wavelet denoising

一种改进的蚁群聚类的图像分割

基于蚁群算法的图像分割研究

A Prediction Approach of Transmembrane Helical Segments in Membrane Proteins Based on Wavelet Transform