QUST-AIBBDRC

DeepMal

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

DNN-DTIs

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

EL-SMURF

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

GA-Bagging-SVM

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

LightGBM-PPI

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

LRF-DTIs

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

rL-GenSVM

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

scGMAI

scGMAI: a Gaussian mixture model for clustering single-cell RNA-seq data based on deep autoencoder

StackPPI

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

SulSite-GTB

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

QUST-AIBBDRC/scGMAI

scGMAI: a Gaussian mixture model for clustering single-cell RNA-seq data based on deep autoencoder

QUST-AIBBDRC/DNN-DTIs

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

QUST-AIBBDRC/StackPPI

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

QUST-AIBBDRC/GA-Bagging-SVM

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

QUST-AIBBDRC/DeepMal

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

QUST-AIBBDRC/PPISP-XGBoost

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

QUST-AIBBDRC/DeepStack-DTIs

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

QUST-AIBBDRC/Mps-mvRBRL

Accurate prediction of multi-label protein subcellular localization through multi-view feature learning with RBRL classifier

QUST-AIBBDRC/4mCi6mA-BGC

Identification of DNA N4-methylcytosine sites and N6-methyladenine sites through elastic net and bidirectional gated recurrent unit with convolutional neural network

QUST-AIBBDRC/RPI-MDLStack

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

QUST-AIBBDRC/ECMP-RF

Prediction of extracellular matrix proteins by fusing multiple feature information, elastic net and Random Forest algorithm

QUST-AIBBDRC/MFF-PAMP

Prediction of antimicrobial peptides based on multi-feature fusion through synthetic minority oversampling technique and random forest

QUST-AIBBDRC/ML-locMLFE

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

QUST-AIBBDRC/MpsLDA-ProSVM

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

QUST-AIBBDRC/StackPDB

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

QUST-AIBBDRC/UbiSite-XGBoost

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

QUST-AIBBDRC/AntiCVP-Deep

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

QUST-AIBBDRC/CITE-sort

QUST-AIBBDRC/DMLDA-LocLIFT

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

QUST-AIBBDRC/DSAC

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

QUST-AIBBDRC/EResCNN

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

QUST-AIBBDRC/Fertility-LightGBM

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

QUST-AIBBDRC/GNN-algorithms

图神经网络相关算法详述及实现

QUST-AIBBDRC/GNN_Review

GNN综述阅读报告

QUST-AIBBDRC/hopper

Diverse sampling for single-cell datasets

QUST-AIBBDRC/LBLS-XGB

LBLS-XGB: a computional method for identification of cancerlectins using XGBoost with multi-information fusion

QUST-AIBBDRC/PMPA_DeepTL

PMPA_DeepTL: a novel deep transfer learning method for predicting multiple protein acylation modified sites based on convolutional neural networks

QUST-AIBBDRC/scIGANs

Generative adversarial networks for single-cell RNA-seq imputation

QUST-AIBBDRC/scirpy

A scanpy extension to analyse single-cell TCR and BCR data.

QUST-AIBBDRC/StackRAM

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