Andreas Bender

Orcid: 0000-0002-6683-7546

Affiliations:
  • University of Cambridge, UK


According to our database1, Andreas Bender authored at least 125 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Online presence:

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Bibliography

2024
MolScore: a scoring, evaluation and benchmarking framework for generative models in de novo drug design.
J. Cheminformatics, December, 2024

Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization.
J. Cheminformatics, December, 2024

DCGG: drug combination prediction using GNN and GAE.
Prog. Artif. Intell., March, 2024

Insights into Drug Cardiotoxicity from Biological and Chemical Data: The First Public Classifiers for FDA Drug-Induced Cardiotoxicity Rank.
J. Chem. Inf. Model., February, 2024

An Open-Source Implementation of the Scaffold Identification and Naming System (SCINS) and Example Applications.
J. Chem. Inf. Model., 2024

Prediction of Inhibitory Activity against the MATE1 Transporter via Combined Fingerprint- and Physics-Based Machine Learning Models.
J. Chem. Inf. Model., 2024

Understanding Biology in the Age of Artificial Intelligence.
CoRR, 2024

2023
Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data.
J. Cheminformatics, December, 2023

On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data.
J. Cheminformatics, December, 2023

Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations.
J. Cheminformatics, December, 2023

Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks.
PLoS Comput. Biol., 2023

On Modelability and Generalizability: Are Machine Learning Models for Drug Synergy Exploiting Artefacts and Biases in Available Data?
Proceedings of the Machine Learning in Computational Biology, November 30, 2023

2022
DOCKSTRING: Easy Molecular Docking Yields Better Benchmarks for Ligand Design.
J. Chem. Inf. Model., 2022

Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation.
J. Cheminformatics, 2022

DDREL: From drug-drug relationships to drug repurposing.
Intell. Data Anal., 2022

Re-evaluating sample efficiency in de novo molecule generation.
CoRR, 2022

Conditional Neural Processes for Molecules.
CoRR, 2022

A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.
Briefings Bioinform., 2022

2021
Comparison of Chemical Structure and Cell Morphology Information for Multitask Bioactivity Predictions.
J. Chem. Inf. Model., 2021

Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study.
J. Cheminformatics, 2021

Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty.
J. Cheminformatics, 2021

Structure-based identification of dual ligands at the A<sub>2A</sub>R and PDE10A with anti-proliferative effects in lung cancer cell-lines.
J. Cheminformatics, 2021

A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective.
CoRR, 2021

2020
Identification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens.
Patterns, 2020

Comparison of Scaling Methods to Obtain Calibrated Probabilities of Activity for Protein-Ligand Predictions.
J. Chem. Inf. Model., 2020

QSAR-derived affinity fingerprints (part 1): fingerprint construction and modeling performance for similarity searching, bioactivity classification and scaffold hopping.
J. Cheminformatics, 2020

QSAR-derived affinity fingerprints (part 2): modeling performance for potency prediction.
J. Cheminformatics, 2020

EMDIP: An Entropy Measure to Discover Important Proteins in PPI networks.
Comput. Biol. Medicine, 2020

2019
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout.
J. Chem. Inf. Model., 2019

Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks.
J. Chem. Inf. Model., 2019

KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images.
J. Cheminformatics, 2019

Leveraging heterogeneous data from GHS toxicity annotations, molecular and protein target descriptors and Tox21 assay readouts to predict and rationalise acute toxicity.
J. Cheminformatics, 2019

Concepts and Applications of Conformal Prediction in Computational Drug Discovery.
CoRR, 2019

Understanding and predicting disease relationships through similarity fusion.
Bioinform., 2019

2018
Conformal Regression for Quantitative Structure-Activity Relationship Modeling - Quantifying Prediction Uncertainty.
J. Chem. Inf. Model., 2018

Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual Screening.
J. Chem. Inf. Model., 2018

Prospectively Validated Proteochemometric Models for the Prediction of Small-Molecule Binding to Bromodomain Proteins.
J. Chem. Inf. Model., 2018

Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening.
J. Chem. Inf. Model., 2018

Maximizing gain in high-throughput screening using conformal prediction.
J. Cheminformatics, 2018

KekuleScope: improved prediction of cancer cell line sensitivity using convolutional neural networks trained on compound images.
CoRR, 2018

Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks.
CoRR, 2018

DeepSynergy: predicting anti-cancer drug synergy with Deep Learning.
Bioinform., 2018

Orthologue chemical space and its influence on target prediction.
Bioinform., 2018

Data-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening.
Briefings Bioinform., 2018

2017
Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?
J. Chem. Inf. Model., November, 2017

Improving Screening Efficiency through Iterative Screening Using Docking and Conformal Prediction.
J. Chem. Inf. Model., 2017

Toward Understanding the Cold, Hot, and Neutral Nature of Chinese Medicines Using in Silico Mode-of-Action Analysis.
J. Chem. Inf. Model., 2017

Computer-aided design of multi-target ligands at A1R, A2AR and PDE10A, key proteins in neurodegenerative diseases.
J. Cheminformatics, 2017

2016
Data-Driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening.
J. Chem. Inf. Model., 2016

A novel applicability domain technique for mapping predictive reliability across the chemical space of a QSAR: reliability-density neighbourhood.
J. Cheminformatics, 2016

Using a Human Drug Network for generating novel hypotheses about drugs.
Intell. Data Anal., 2016

ARWAR: A network approach for predicting Adverse Drug Reactions.
Comput. Biol. Medicine, 2016

Improved large-scale prediction of growth inhibition patterns using the NCI60 cancer cell line panel.
Bioinform., 2016

2015
Analyzing Multitarget Activity Landscapes Using Protein-Ligand Interaction Fingerprints: Interaction Cliffs.
J. Chem. Inf. Model., 2015

Improved Chemical Structure-Activity Modeling Through Data Augmentation.
J. Chem. Inf. Model., 2015

Comparing the Influence of Simulated Experimental Errors on 12 Machine Learning Algorithms in Bioactivity Modeling Using 12 Diverse Data Sets.
J. Chem. Inf. Model., 2015

Proteochemometric modelling coupled to in silico target prediction: an integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.
J. Cheminformatics, 2015

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.
J. Cheminformatics, 2015

Target prediction utilising negative bioactivity data covering large chemical space.
J. Cheminformatics, 2015

Metrabase: a cheminformatics and bioinformatics database for small molecule transporter data analysis and (Q)SAR modeling.
J. Cheminformatics, 2015

Synergy Maps: exploring compound combinations using network-based visualization.
J. Cheminformatics, 2015

Prediction of the potency of mammalian cyclooxygenase inhibitors with ensemble proteochemometric modeling.
J. Cheminformatics, 2015

A multi-label approach to target prediction taking ligand promiscuity into account.
J. Cheminformatics, 2015

Using a Human Disease Network for augmenting prior knowledge about diseases.
Intell. Data Anal., 2015

Applications of proteochemometrics - from species extrapolation to cell line sensitivity modelling.
BMC Bioinform., 2015

2014
How Diverse Are Diversity Assessment Methods? A Comparative Analysis and Benchmarking of Molecular Descriptor Space.
J. Chem. Inf. Model., 2014

Erratum for "In Silico Target Predictions: Defining a Benchmarking Data Set and Comparison of Performance of the Multiclass Naı̈ve Bayes and Parzen-Rosenblatt Window".
J. Chem. Inf. Model., 2014

Proteochemometric modeling in a Bayesian framework.
J. Cheminformatics, 2014

Target Fishing: A Single-Label or Multi-Label Problem?
CoRR, 2014

2013
Significantly Improved HIV Inhibitor Efficacy Prediction Employing Proteochemometric Models Generated From Antivirogram Data.
PLoS Comput. Biol., 2013

In Silico Target Predictions: Defining a Benchmarking Data Set and Comparison of Performance of the Multiclass Naïve Bayes and Parzen-Rosenblatt Window.
J. Chem. Inf. Model., 2013

Chemogenomics Approaches to Rationalizing the Mode-of-Action of Traditional Chinese and Ayurvedic Medicines.
J. Chem. Inf. Model., 2013

Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets.
J. Cheminformatics, 2013

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets.
J. Cheminformatics, 2013

Are phylogenetic trees suitable for chemogenomics analyses of bioactivity data sets: the importance of shared active compounds and choosing a suitable data embedding method, as exemplified on Kinases.
J. Cheminformatics, 2013

Revised classification of kinases based on bioactivity data: the importance of data density and choice of visualization.
J. Cheminformatics, 2013

Annotating targets with pathways: extending approaches to mode of action analysis.
J. Cheminformatics, 2013

Relating GPCRs pharmacological space based on ligands chemical similarities.
J. Cheminformatics, 2013

Chemogenomics approaches to rationalising compound action of traditional Chinese and Ayurvedic medicines.
J. Cheminformatics, 2013

Using machine learning techniques for rationalising phenotypic readouts from a rat sleeping model.
J. Cheminformatics, 2013

Experimental validation of in silico target predictions on synergistic protein targets.
J. Cheminformatics, 2013

Efficient calculation of compound similarity based on maximum common subgraphs and its application to prediction of gene transcript levels.
Int. J. Bioinform. Res. Appl., 2013

Computational Methods Aiding Early-Stage Drug Design (Dagstuhl Seminar 13212).
Dagstuhl Reports, 2013

2012
Predicting Genes Involved in Human Cancer Using Network Contextual Information.
J. Integr. Bioinform., 2012

Recognizing Pitfalls in Virtual Screening: A Critical Review.
J. Chem. Inf. Model., 2012

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms.
J. Chem. Inf. Model., 2012

Multi-Objective Evolutionary Design of Adenosine Receptor Ligands.
J. Chem. Inf. Model., 2012

Molecular dynamics simulations and docking of non-nucleoside reverse transcriptase inhibitors (NNRTIs): a possible approach to personalized HIV treatment.
J. Cheminformatics, 2012

Cheminformatics.
Commun. ACM, 2012

Using Multiobjective Optimization and Energy Minimization to Design an Isoform-Selective Ligand of the 14-3-3 Protein.
Proceedings of the Leveraging Applications of Formal Methods, Verification and Validation. Applications and Case Studies, 2012

2011
P-glycoprotein Substrate Models Using Support Vector Machines Based on a Comprehensive Data set.
J. Chem. Inf. Model., 2011

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.
J. Cheminformatics, 2011

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information.
J. Comput. Aided Mol. Des., 2011

Collaboration-Based Function Prediction in Protein-Protein Interaction Networks.
Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011

2010
Predicting the functions of proteins in Protein-Protein Interaction networks from global information.
Proceedings of the third International Workshop on Machine Learning in Systems Biology, 2010

Molecular bioactivity extrapolation to novel targets by support vector machines.
J. Cheminformatics, 2010

Expanding and understanding metabolite space.
J. Cheminformatics, 2010

Predicting the binding type of compounds on the 4 adenosine receptors using proteochemometric models.
J. Cheminformatics, 2010

Evolutionary design of selective adenosine receptor ligands.
J. Cheminformatics, 2010

A novel chemogenomics analysis of G protein-coupled receptors (GPCRs) and their ligands: a potential strategy for receptor de-orphanization.
BMC Bioinform., 2010

2009
SPREAD - exploiting chemical features that cause differential activity behavior.
Stat. Anal. Data Min., 2009

Chemogenomics: Looking at biology through the lens of chemistry.
Stat. Anal. Data Min., 2009

Gaining Insight into Off-Target Mediated Effects of Drug Candidates with a Comprehensive Systems Chemical Biology Analysis.
J. Chem. Inf. Model., 2009

Characterization of Activity Landscapes Using 2D and 3D Similarity Methods: <i>Consensus Activity Cliffs</i>.
J. Chem. Inf. Model., 2009

Substructure Mining of GPCR Ligands Reveals Activity-Class Specific Functional Groups in an Unbiased Manner.
J. Chem. Inf. Model., 2009

How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space.
J. Chem. Inf. Model., 2009

Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

Combining Aggregation with Pareto Optimization: A Case Study in Evolutionary Molecular Design.
Proceedings of the Evolutionary Multi-Criterion Optimization, 5th International Conference, 2009

2008
Ligand-Target Prediction Using Winnow and Naive Bayesian Algorithms and the Implications of Overall Performance Statistics.
J. Chem. Inf. Model., 2008

Distributed Chemical Computing Using ChemStar: An Open Source Java Remote Method Invocation Architecture Applied to Large Scale Molecular Data from PubChem.
J. Chem. Inf. Model., 2008

A Scenario Implementation in Rfor SubtypeDiscoveryExamplified on Chemoinformatics Data.
Proceedings of the Leveraging Applications of Formal Methods, 2008

2007
Understanding False Positives in Reporter Gene Assays: in Silico Chemogenomics Approaches To Prioritize Cell-Based HTS Data.
J. Chem. Inf. Model., 2007

Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds.
J. Comput. Aided Mol. Des., 2007

2006
Characterizing Bitterness: Identification of Key Structural Features and Development of a Classification Model.
J. Chem. Inf. Model., 2006

Melting Point Prediction Employing <i>k</i>-Nearest Neighbor Algorithms and Genetic Parameter Optimization.
J. Chem. Inf. Model., 2006

Harvesting Chemical Information from the Internet Using a Distributed Approach: ChemXtreme.
J. Chem. Inf. Model., 2006

Analysis of Activity Space by Fragment Fingerprints, 2D Descriptors, and Multitarget Dependent Transformation of 2D Descriptors.
J. Chem. Inf. Model., 2006

Chemoinformatics-Based Classification of Prohibited Substances Employed for Doping in Sport.
J. Chem. Inf. Model., 2006

"Bayes Affinity Fingerprints" Improve Retrieval Rates in Virtual Screening and Define Orthogonal Bioactivity Space: When Are Multitarget Drugs a Feasible Concept?
J. Chem. Inf. Model., 2006

2005
General Melting Point Prediction Based on a Diverse Compound Data Set and Artificial Neural Networks.
J. Chem. Inf. Model., 2005

A Discussion of Measures of Enrichment in Virtual Screening: Comparing the Information Content of Descriptors with Increasing Levels of Sophistication.
J. Chem. Inf. Model., 2005

Molecular Similarity Searching Using COSMO Screening Charges (COSMO/3PP).
Proceedings of the Computational Life Sciences, First International Symposium, 2005

2004
Similarity Searching of Chemical Databases Using Atom Environment Descriptors (MOLPRINT 2D): Evaluation of Performance.
J. Chem. Inf. Model., 2004

Molecular Similarity Searching Using Atom Environments, Information-Based Feature Selection, and a Naïve Bayesian Classifier.
J. Chem. Inf. Model., 2004

Molecular surface point environments for virtual screening and the elucidation of binding patterns (MOLPRINT).
Proceedings of the IEEE International Conference on Systems, 2004


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