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De Novo Drug Design Using Multiobjective Evolutionary Graphs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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The art and practice of structure-based drug design: A molecular modeling perspective
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Chemoinformatics in Drug Discovery
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Introduction to Chemoinformatics in Drug Discovery – A Personal View
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Efficient Strategies for Lead Optimization by Simultaneously Addressing Affinity, Selectivity and Pharmacokinetic Parameters
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Multiobjective Problem Solving from Nature: From Concepts to Applications
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A Tutorial on Evolutionary Multiobjective Optimization
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Genetic Algorithms + Data Structures = Evolution Programs
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Multiobjective Optimization
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PRO_LIGAND: An approach to de novo molecular design. 1. Application to the design of organic molecules
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PRO_LIGAND: An approach to de novo molecular design. 3. A genetic algorithm for structure refinement
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A genetic algorithm for the automated generation of molecules within constraints
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Evolutionary algorithms in computer-aided molecular design
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A novel workflow for the inverse QSPR problem using multiobjective optimization
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Evolutionary Algorithms in Drug Design
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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1
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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
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SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules
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A Graph-Based Genetic Algorithm and Its Application to the Multiobjective Evolution of Median Molecules
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Flux (1): A Virtual Synthesis Scheme for Fragment-Based de Novo Design
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The Molecule Evoluator. An Interactive Evolutionary Algorithm for the Design of Drug-Like Molecules
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Flux (2): Comparison of Molecular Mutation and Crossover Operators for Ligand-Based de Novo Design
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GlamDock: Development and Validation of a New Docking Tool on Several Thousand Protein−Ligand Complexes
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Chemical Similarity Using Physiochemical Property Descriptors
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RECAPRetrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry
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Comparison of 2D Fingerprint Types and Hierarchy Level Selection Methods for Structural Grouping Using Ward's Clustering
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Application of Complex Aldol Reactions to the Total Synthesis of Phorboxazole B
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Detailed Analysis of Scoring Functions for Virtual Screening
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LEA3D: A Computer-Aided Ligand Design for Structure-Based Drug Design
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A genetic algorithm for the automated generation of small organic molecules: Drug design using an evolutionary algorithm
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De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks
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Principles in the Evolutionary Design of Digital Circuits—Part II
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Molecular Evolution: Automated Manipulation of Hierarchical Chemical Topology and Its Application to Average Molecular Structures
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Towards a new age of virtual ADME/TOX and multidimensional drug discovery
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Computer-based de novo design of drug-like molecules
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Automatic molecular design using evolutionary techniques
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Database resources of the National Center for Biotechnology Information: update
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Database resources of the National Center for Biotechnology Information
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Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
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Multiobjective Optimization in Bioinformatics and Computational Biology
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Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992)
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Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
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Molecular Optimization Using Computational Multi-Objective Methods
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Molecular Substructure Mining Approaches for Computer-Aided Drug Discovery A Review
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Multiobjective Optimization for Drug Discovery
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Advances in Multiobjective Optimization for Drug Discovery and Development
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Multi‐Objective Optimization Applications in Chemical Engineering
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Scaffold Hopping andDe NovoDrug Design
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De NovoDesign: From Models to Molecules
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MultiobjectiveDe NovoDesign of Synthetically Accessible Compounds
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Structure‐BasedDe NovoDrug Design
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Predictive Methods in Lead Generation
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A Bright Future for Evolutionary Methods in Drug Design
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Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets
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Deep generative models for ligand‐based de novo design applied to multi‐parametric optimization
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Fragment Informatics and Computational Fragment‐Based Drug Design: An Overview and Update
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Development of a New De Novo Design Algorithm for Exploring Chemical Space
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A Pareto Algorithm for Efficient De Novo Design of Multi‐functional Molecules
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Enabling future drug discovery by de novo design
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Computational Fragment-Based Drug Design
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Computational Approaches for De Novo Drug Design: Past, Present, and Future
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De Novo Design of Ligands Using Computational Methods
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Molecular Library Design Using Multi-Objective Optimization Methods
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Handling Branched Web Service Composition with a QoS-Aware Graph-Based Method
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Using Multiobjective Optimization and Energy Minimization to Design an Isoform-Selective Ligand of the 14-3-3 Protein
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Bayesian molecular design with a chemical language model
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Network-based piecewise linear regression for QSAR modelling
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Heuristics and Uncertainty Quantification in Rational and Inverse Compound and Catalyst Design
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Generative chemistry in practice: Data-, synthesis-, and pocket- aware workflows for drug design
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Graph-Based Genetic Algorithm for De Novo Molecular Design
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De Novo Molecular Design using a Graph-Based Genetic Algorithm Approach
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Exploring chemical space — Generative models and their evaluation
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Evolutionary algorithms for de novo drug design – A survey
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Automatic outlier sample detection based on regression analysis and repeated ensemble learning
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Compound Collection Enhancement and Paradigms for High-Throughput Screening — an Update
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Evolutionary Multiobjective Molecule Optimization in an Implicit Chemical Space
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MOARF, an Integrated Workflow for Multiobjective Optimization: Implementation, Synthesis, and Biological Evaluation
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Inverse QSPR/QSAR Analysis for Chemical Structure Generation (fromytox)
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GuacaMol: Benchmarking Models for de Novo Molecular Design
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New Data Structure for Computational Molecular Design with Atomic or Fragment Resolution
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Multi-Objective Evolutionary Design of Adenosine Receptor Ligands
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Combination of Similarity Rankings Using Data Fusion
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LiGen: A High Performance Workflow for Chemistry Driven de Novo Design
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Automated design of ligands to polypharmacological profiles
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Deep-learning-based inverse design model for intelligent discovery of organic molecules
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Invalid SMILES are beneficial rather than detrimental to chemical language models
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Optimizing blood–brain barrier permeation through deep reinforcement learning for de novo drug design
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A parallel Multi-objective Evolutionary Algorithm
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Optimal graph design using a knowledge-driven multi-objective evolutionary graph algorithm
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Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model
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End-to-end Deep Reinforcement Learning for Targeted Drug Generation
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A Generative Evolutionary Many-Objective Framework: A Case Study in Antimicrobial Agent Design
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Multiobjective de novo drug design with recurrent neural networks and nondominated sorting
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Diversity oriented Deep Reinforcement Learning for targeted molecule generation
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Individual and collective human intelligence in drug design: evaluating the search strategy
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LEADD: Lamarckian evolutionary algorithm for de novo drug design
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Adaptive language model training for molecular design
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Crossover operators for molecular graphs with an application to virtual drug screening
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Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib
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Multiobjective Reinforcement Learning in Optimized Drug Design
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De novodesign: balancing novelty and confined chemical space
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The quest for novel chemical matter and the contribution of computer-aidedde novodesign
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Strategies of multi-objective optimization in drug discovery and development
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Advances in multiparameter optimization methods for de novo drug design
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Bi-Distance Approach to Determine the Topological Invariants of Silicon Carbide
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Multi-Parameter Optimization: Identifying High Quality Compounds with a Balance of Properties
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Multi-Parameter Optimization: Identifying High Quality Compounds with a Balance of Properties
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Multi-Objective Optimization Methods in De Novo Drug Design
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Desirability-Based Multi-Objective QSAR in Drug Discovery
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Computational Approaches for Fragment-Based and De Novo Design
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Revisiting De Novo Drug Design: Receptor Based Pharmacophore Screening
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Evolutionary Computation and QSAR Research
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FBDD & De Novo Drug Design
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Multi-Objective and Many-Objective Optimisation: Present and Future in de novo Drug Design
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Multi- and Many-Objective Optimisation: Present and Future in de novo Drug Design
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Individual & Collective Human Intelligence in Drug Design: Evaluating the Search Strategy
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Evolutionary Computation for Multifaceted Web Service Composition
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Evolutionary Computation for Multifaceted Web Service Composition
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Multi-and many-objective optimization: present and future in de novo drug design
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Multi-Objective Drug Design Based on Graph-Fragment Molecular Representation and Deep Evolutionary Learning
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Advances in De Novo Drug Design: From Conventional to Machine Learning Methods
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MoleGear: A Java-Based Platform for Evolutionary De Novo Molecular Design
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Multi-objective Monkey Algorithm for Drug Design
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Additional file 1 of Diversity oriented Deep Reinforcement Learning for targeted molecule generation
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Additional file 1 of Individual and collective human intelligence in drug design: evaluating the search strategy
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Additional file 1 of LEADD: Lamarckian evolutionary algorithm for de novo drug design
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Computational design of synthesizable molecules by imitating reference chemistry
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Using a genetic algorithm to find molecules with good docking scores
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