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Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics

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Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network data

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NOREVA: normalization and evaluation of MS-based metabolomics data

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SVM-RFE With MRMR Filter for Gene Selection

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Distance-based Support Vector Machine to Predict DNA N6- methyladenine Modification

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Deep-Resp-Forest: A deep forest model to predict anti-cancer drug response

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Clustering and classification methods for single-cell RNA-sequencing data

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Application of Machine Learning in Microbiology

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ACPred-Fuse: fusing multi-view information improves the prediction of anticancer peptides

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A Review of Approaches for Predicting Drug–Drug Interactions Based on Machine Learning

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Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species

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Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework

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Artificial Intelligence-Based Toxicity Prediction of Environmental Chemicals: Future Directions for Chemical Management Applications

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Anticancer peptides prediction with deep representation learning features

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Artificial Intelligence in Drug Discovery: A Comprehensive Review of Data-driven and Machine Learning Approaches

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StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides

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MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters

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iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree

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An Efficient Classifier for Alzheimer’s Disease Genes Identification

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A Random Forest Sub-Golgi Protein Classifier Optimized via Dipeptide and Amino Acid Composition Features

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Review of machine learning and deep learning models for toxicity prediction

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StackDPPIV: A novel computational approach for accurate prediction of dipeptidyl peptidase IV (DPP-IV) inhibitory peptides

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Gradient boosting decision tree-based method for predicting interactions between target genes and drugs

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Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network

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Fusing convolutional neural network features with hand-crafted features for osteoporosis diagnoses

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Sequence representation approaches for sequence-based protein prediction tasks that use deep learning

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k-Skip-n-Gram-RF: A Random Forest Based Method for Alzheimer's Disease Protein Identification

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Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment

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An effective framework for predicting drug–drug interactions based on molecular substructures and knowledge graph neural network

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Exposing the Causal Effect of Body Mass Index on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study

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Deep Neural Network Models for Predicting Chemically Induced Liver Toxicity Endpoints From Transcriptomic Responses

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DeepFusionDTA: Drug-Target Binding Affinity Prediction With Information Fusion and Hybrid Deep-Learning Ensemble Model

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Advances in the Identification of Circular RNAs and Research Into circRNAs in Human Diseases

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Discrimination of Thermophilic Proteins and Non-thermophilic Proteins Using Feature Dimension Reduction

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iEnhancer-EBLSTM: Identifying Enhancers and Strengths by Ensembles of Bidirectional Long Short-Term Memory

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Exploiting Discriminative Regions of Brain Slices Based on 2D CNNs for Alzheimer’s Disease Classification

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SubLocEP: a novel ensemble predictor of subcellular localization of eukaryotic mRNA based on machine learning

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Research on Bitter Peptides in the Field of Bioinformatics: A Comprehensive Review

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Supervised Brain Tumor Segmentation Based on Gradient and Context-Sensitive Features

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SRDFM: Siamese Response Deep Factorization Machine to improve anti-cancer drug recommendation

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WERFE: A Gene Selection Algorithm Based on Recursive Feature Elimination and Ensemble Strategy

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ACP-GCN: The Identification of Anticancer Peptides Based on Graph Convolution Networks

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Identification of expression signatures for non-small-cell lung carcinoma subtype classification

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iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier

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dPromoter-XGBoost: Detecting promoters and strength by combining multiple descriptors and feature selection using XGBoost

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EP3: an ensemble predictor that accurately identifies type III secreted effectors

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Developing a Multi-Layer Deep Learning Based Predictive Model to Identify DNA N4-Methylcytosine Modifications

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Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity

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StackHCV: a web-based integrative machine-learning framework for large-scale identification of hepatitis C virus NS5B inhibitors

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Construction of Complex Features for Computational Predicting ncRNA-Protein Interaction

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Identification and classification of promoters using the attention mechanism based on long short-term memory

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A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data

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PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron

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Application of Multilayer Network Models in Bioinformatics

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Identification of adaptor proteins using the ANOVA feature selection technique

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Predicting drug-induced hepatotoxicity based on biological feature maps and diverse classification strategies

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Identification of Methicillin-Resistant Staphylococcus Aureus From Methicillin-Sensitive Staphylococcus Aureus and Molecular Characterization in Quanzhou, China

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iAIPs: Identifying Anti-Inflammatory Peptides Using Random Forest

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rBPDL:Predicting RNA-Binding Proteins Using Deep Learning

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DrugHybrid_BS: Using Hybrid Feature Combined With Bagging-SVM to Predict Potentially Druggable Proteins

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Identification of Triple-Negative Breast Cancer Genes and a Novel High-Risk Breast Cancer Prediction Model Development Based on PPI Data and Support Vector Machines

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CWLy-pred: A novel cell wall lytic enzyme identifier based on an improved MRMD feature selection method

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Unlocking the microbial studies through computational approaches: how far have we reached?

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Identification of miR-200c and miR141-Mediated lncRNA-mRNA Crosstalks in Muscle-Invasive Bladder Cancer Subtypes

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FunEffector-Pred: Identification of Fungi Effector by Activate Learning and Genetic Algorithm Sampling of Imbalanced Data

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Identification of glioblastoma molecular subtype and prognosis based on deep MRI features

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Predicting Ion Channels Genes and Their Types With Machine Learning Techniques

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iRNA-m5C_NB: A Novel Predictor to Identify RNA 5-Methylcytosine Sites Based on the Naive Bayes Classifier

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Analysis of Cyclin-Dependent Kinase 1 as an Independent Prognostic Factor for Gastric Cancer Based on Statistical Methods

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6mA-Pred: identifying DNA N6-methyladenine sites based on deep learning

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Identification of hormone-binding proteins using a novel ensemble classifier

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AAPred-CNN: Accurate predictor based on deep convolution neural network for identification of anti-angiogenic peptides

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TMPpred: A support vector machine-based thermophilic protein identifier

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Identification of Phage Viral Proteins With Hybrid Sequence Features

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iDNA-MT: Identification DNA Modification Sites in Multiple Species by Using Multi-Task Learning Based a Neural Network Tool

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Distant metastasis identification based on optimized graph representation of gene interaction patterns

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Prediction of G Protein-Coupled Receptors With CTDC Extraction and MRMD2.0 Dimension-Reduction Methods

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NonClasGP-Pred: robust and efficient prediction of non-classically secreted proteins by integrating subset-specific optimal models of imbalanced data

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Prediction of lncRNA–Protein Interactions via the Multiple Information Integration

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Identification of Secreted Proteins From Malaria Protozoa With Few Features

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Predicting the Disease Risk of Protein Mutation Sequences With Pre-training Model

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Recent Advances in Predicting Protein S‐Nitrosylation Sites

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Toxicogenomic analysis of physiologically important metals: An integrated in silico approach

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Deep reinforcement learning with emergent communication for coalitional negotiation games

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Single-cell transcriptome analysis reveals immune microenvironment changes and insights into the transition from DCIS to IDC with associated prognostic genes

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4mCPred-MTL: Accurate Identification of DNA 4mC Sites in Multiple Species Using Multi-Task Deep Learning Based on Multi-Head Attention Mechanism

Zeng, R., Cheng, S., & Liao, M. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.664669 · Cited by 10

Structure Mapping Generative Adversarial Network for Multi-View Information Mapping Pattern Mining

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White Blood Cell Image Segmentation Based on Color Component Combination and Contour Fitting

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Identifying G-Protein Coupled Receptors Using Mixed-Feature Extraction Methods and Machine Learning Methods

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ORS‐Pred: An optimized reduced scheme‐based identifier for antioxidant proteins

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6mAPred-MSFF: A Deep Learning Model for Predicting DNA N6-Methyladenine Sites across Species Based on a Multi-Scale Feature Fusion Mechanism

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ATGPred-FL: sequence-based prediction of autophagy proteins with feature representation learning

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Computational Approaches for Drug-Induced Liver Injury (DILI) Prediction: State of the Art and Challenges

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Bioluminescent Proteins Prediction with Voting Strategy

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Toxicity prediction and classification of Gunqile-7 with small sample based on transfer learning method

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CWLy-RF: A novel approach for identifying cell wall lyases based on random forest classifier

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Better Performance with Transformer: CPPFormer in the Precise Prediction of Cell-penetrating Peptides

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MFA-DTI: Drug-target interaction prediction based on multi-feature fusion adopted framework

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