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Predicting Drug–Target Interactions Using Probabilistic Matrix Factorization

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What this work says

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Dual-Layer Strengthened Collaborative Topic Regression Modeling for Predicting Drug Sensitivity

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Drug-Target Interaction Prediction: End-to-End Deep Learning Approach

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FMGNN: A Method to Predict Compound-Protein Interaction With Pharmacophore Features and Physicochemical Properties of Amino Acids

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Predicting Drug-Target Interactions Via Dual-Stream Graph Neural Network

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Effective Generalized Low-Rank Tensor Contextual Bandits

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Network‐based precision medicine and systems pharmacology

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Drugs – Protein affinity‐score prediction using deep convolutional neural network

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Realizing private and practical pharmacological collaboration

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Pyrazolidine-3,5-dione Derivatives: Synthesis, Computational, and In Vitro Screening Targeting Breast Cancer

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Hybrid quantum neural networks for efficient protein-ligand binding affinity prediction

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COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

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Investigating Multiview and Multitask Learning Frameworks for Predicting Drug-Disease Associations

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Systems Medicine: The Application of Systems Biology Approaches for Modern Medical Research and Drug Development

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Drug‐Target Interaction Prediction Based on Adversarial Bayesian Personalized Ranking

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Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses

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A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine

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Leveraging Image-Derived Phenotypic Measurements for Drug-Target Interaction Predictions

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VB-MK-LMF: fusion of drugs, targets and interactions using variational Bayesian multiple kernel logistic matrix factorization

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Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server

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Predicting associations among drugs, targets and diseases by tensor decomposition for drug repositioning

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Drug-target interactions prediction using marginalized denoising model on heterogeneous networks

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visGReMLIN: graph mining-based detection and visualization of conserved motifs at 3D protein-ligand interface at the atomic level

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Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets

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NeuRank: learning to rank with neural networks for drug–target interaction prediction

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A comparison of embedding aggregation strategies in drug–target interaction prediction

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DeepMPF: deep learning framework for predicting drug–target interactions based on multi-modal representation with meta-path semantic analysis

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A multi-label approach to target prediction taking ligand promiscuity into account

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Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review

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Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction

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Predicting kinase inhibitors using bioactivity matrix derived informer sets

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Adverse Drug Reaction Prediction Using Scores Produced by Large-Scale Drug-Protein Target Docking on High-Performance Computing Machines

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Drug-target interaction prediction using Multi Graph Regularized Nuclear Norm Minimization

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Drug–target interaction prediction via chemogenomic space: learning-based methods

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Target Fishing: A Single-Label or Multi-Label Problem?

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Autoencoders for Drug-Target Interaction Prediction

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Density Functional Theory and Molecular Modeling Studies of New 4-(Furan-2-yl) Thiazol-2-Amine Derivatives as Cyclooxygenase Inhibitors

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Application of Machine Learning Techniques in Drug-target Interactions Prediction

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Chemogenomic Approaches for Revealing Drug Target Interactions in Drug Discovery

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A Comparative Analytical Review on Machine Learning Methods in Drugtarget Interactions Prediction

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Drug Target Interaction [DTI] and Prediction using Machine Learning

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Small Random Forest Models for Effective Chemogenomic Active Learning

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Personalized and adaptive recommendation

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Challenges and solutions in drug-target interaction prediction

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In-Silico Evaluation of Binding Interaction and ADME Properties of Novel Pyrazoline and Pyrimidine Derivatives Targeting Cyclooxygenase-2 Enzyme

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Predicting the Effects of Drug Combinations Using Probabilistic Matrix Factorization

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Insights into the Modulation of Dopamine Transporter Function by Amphetamine, Orphenadrine, and Cocaine Binding

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A Review of Current In Silico Methods for Repositioning Drugs and Chemical Compounds

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Quantitative Systems Pharmacological Analysis of Drugs of Abuse Reveals the Pleiotropy of Their Targets and the Effector Role of mTORC1

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Simulation and Machine Learning Methods for Ion-Channel Structure Determination, Mechanistic Studies and Drug Design

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EmbedDTI: Enhancing the Molecular Representations via Sequence Embedding and Graph Convolutional Network for the Prediction of Drug-Target Interaction

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Mechanisms of Action of Autophagy Modulators Dissected by Quantitative Systems Pharmacology Analysis

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Is Drug Delivery System a Deterministic or Probabilistic Approach? A Theoretical Model Based on the Sequence: Electrodynamics–Diffusion–Bayes

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Machine Learning for Drug-Target Interaction Prediction

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Revealing Drug-Target Interactions with Computational Models and Algorithms

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Graph Representation Learning and Its Applications: A Survey

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DeepVir - Graphical Deep Matrix Factorization for In Silico Antiviral Repositioning: Application to COVID-19

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DeepVir - Graphical Deep Matrix Factorization for In Silico Antiviral Repositioning: Application to COVID-19

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Machine Learning in Drug Repurposing

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In silico evaluation of binding interaction and ADME study of new 1,3-diazetidin-2-one derivatives with high antiproliferative activity

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Artificial Intelligence in Drug Design: Algorithms, Applications, Challenges and Ethics

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Data Infrastructure and Approaches for Ontology-Based Drug Repurposing

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Drug-Target Interaction Prediction via an Ensemble of Weighted Nearest Neighbors with Interaction Recovery

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A Deep Learning Framework for Prediction of the Mechanism of Action

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Additional file 1 of visGReMLIN: graph mining-based detection and visualization of conserved motifs at 3D protein-ligand interface at the atomic level

inferred← citeshttps://doi.org/10.6084/m9.figshare.12703482openalex-snapshot

Additional file 2 of Drug-target interactions prediction using marginalized denoising model on heterogeneous networks

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Additional file 1 of Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets

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Additional file 1 of DeepMPF: deep learning framework for predicting drug–target interactions based on multi-modal representation with meta-path semantic analysis

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Additional file 2 of DeepMPF: deep learning framework for predicting drug–target interactions based on multi-modal representation with meta-path semantic analysis

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Additional file 1 of A comparison of embedding aggregation strategies in drug–target interaction prediction

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LinkDTI: Drug-Target Interactions prediction through a Link Prediction framework on Biomedical Knowledge Graph

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Machine learning approaches for drug virtual screening

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Peer Review #3 of "Survey on graph embeddings and their applications to machine learning problems on graphs (v0.1)"

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Peer Review #1 of "Survey on graph embeddings and their applications to machine learning problems on graphs (v0.2)"

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Peer Review #3 of "Survey on graph embeddings and their applications to machine learning problems on graphs (v0.2)"

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[Drug-target protein interaction prediction based on AdaBoost algorithm].

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Survey on graph embeddings and their applications to machine learning problems on graphs

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.