Andreas Bender

Molecular similarity searching using atom environments, information-based feature selection, and a naïve Bayesian classifier.

Similarity searching of chemical databases using atom environment descriptors (MOLPRINT 2D): evaluation of performance.

Molecular similarity: a key technique in molecular informatics.

Molecular surface point environments for virtual screening and the elucidation of binding patterns (MOLPRINT 3D).

Assessment of structural diversity in combinatorial synthesis.

Screening for dihydrofolate reductase inhibitors using MOLPRINT 2D, a fast fragment-based method employing the naïve Bayesian classifier: limitations of the descriptor and the importance of balanced chemistry in training and test sets.

A discussion of measures of enrichment in virtual screening: comparing the information content of descriptors with increasing levels of sophistication.

Circular fingerprints: flexible molecular descriptors with applications from physical chemistry to ADME.

Diversity oriented synthesis: a challenge for synthetic chemists.

Skeletal diversity construction via a branching synthetic strategy.

Chemoinformatics-based classification of prohibited substances employed for doping in sport.

Melting point prediction employing k-nearest neighbor algorithms and genetic parameter optimization.

Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds.

Anti-MRSA agent discovery using diversity-oriented synthesis.

Diversity-oriented synthesis; a spectrum of approaches and results.

Ligand-target prediction using Winnow and naive Bayesian algorithms and the implications of overall performance statistics.

The discovery of antibacterial agents using diversity-oriented synthesis.

Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble.

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

Increased diversity of libraries from libraries: chemoinformatic analysis of bis-diazacyclic libraries.

Diversity-oriented synthesis of macrocyclic peptidomimetics.

From in silico target prediction to multi-target drug design: current databases, methods and applications.

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

Which compound to select in lead optimization? Prospectively validated proteochemometric models guide preclinical development.

Understanding and classifying metabolite space and metabolite-likeness.

Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

How similar are those molecules after all? Use two descriptors and you will have three different answers.

A two-directional strategy for the diversity-oriented synthesis of macrocyclic scaffolds.

Chemogenomics approaches to rationalizing the mode-of-action of traditional Chinese and Ayurvedic medicines.

Significantly improved HIV inhibitor efficacy prediction employing proteochemometric models generated from antivirogram data.

Diversity selection of compounds based on 'protein affinity fingerprints' improves sampling of bioactive chemical space.

In silico target predictions: defining a benchmarking data set and comparison of performance of the multiclass Naïve Bayes and Parzen-Rosenblatt window.

Computer-aided (in silico) approaches in the mode-of-action analysis and safety assessment of ostarine and 4-methylamphetamine.

Linking Ayurveda and Western medicine by integrative analysis.

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

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

Design, synthesis, and biological evaluation of an allosteric inhibitor of HSET that targets cancer cells with supernumerary centrosomes.

How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

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.

A-ring dihalogenation increases the cellular activity of combretastatin-templated tetrazoles.

Proteochemometric modeling in a Bayesian framework.

Novel benzoxazine-based aglycones block glucose uptake in vivo by inhibiting glycosidases.

Novel synthetic biscoumarins target tumor necrosis factor-α in hepatocellular carcinoma in vitro and in vivo.

Connecting gene expression data from connectivity map and in silico target predictions for small molecule mechanism-of-action analysis.

Modelling ligand selectivity of serine proteases using integrative proteochemometric approaches improves model performance and allows the multi-target dependent interpretation of features.

Synthesis and characterization of novel 2-amino-chromene-nitriles that target Bcl-2 in acute myeloid leukemia cell lines.

Development of a novel azaspirane that targets the Janus kinase-signal transducer and activator of transcription (STAT) pathway in hepatocellular carcinoma in vitro and in vivo.

Towards predictive resistance models for agrochemicals by combining chemical and protein similarity via proteochemometric modelling.

Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts.

Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project.

Novel synthetic coumarins that targets NF-κB in Hepatocellular carcinoma.

Analyzing multitarget activity landscapes using protein-ligand interaction fingerprints: interaction cliffs.

Prediction of the potency of mammalian cyclooxygenase inhibitors with ensemble proteochemometric modeling.

Comparing global and local likelihood score thresholds in multiclass laplacian-modified Naive Bayes protein target prediction.

Microwave-assisted synthesis, characterization and cytotoxic studies of novel estrogen receptor α ligands towards human breast cancer cells.

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

Comparing the Influence of Simulated Experimental Errors on 12 Machine Learning Algorithms in Bioactivity Modeling Using 12 Diverse Data Sets.

Synthesis and characterization of novel oxazines and demonstration that they specifically target cyclooxygenase 2.

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

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

A One Pot Synthesis of Novel Bioactive Tri-Substitute-Condensed-Imidazopyridines that Targets Snake Venom Phospholipase A2.

Design, synthesis and evaluation of semi-synthetic triazole-containing caffeic acid analogues as 5-lipoxygenase inhibitors.

Synergy Maps: exploring compound combinations using network-based visualization.

Synthesis of 1,2-benzisoxazole tethered 1,2,3-triazoles that exhibit anticancer activity in acute myeloid leukemia cell lines by inhibiting histone deacetylases, and inducing p21 and tubulin acetylation.

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

Synthesis, characterization and in vitro evaluation of novel enantiomerically-pure sulphonamide antimalarials.

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

Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives.

Development of Novel Triazolo-Thiadiazoles from Heterogeneous "Green" Catalysis as Protein Tyrosine Phosphatase 1B Inhibitors.

Cheminformatics Research at the Unilever Centre for Molecular Science Informatics Cambridge.

A Nano-MgO and Ionic Liquid-Catalyzed 'Green' Synthesis Protocol for the Development of Adamantyl-Imidazolo-Thiadiazoles as Anti-Tuberculosis Agents Targeting Sterol 14α-Demethylase (CYP51).

Target prediction utilising negative bioactivity data covering large chemical space.

How Consistent are Publicly Reported Cytotoxicity Data? Large-Scale Statistical Analysis of the Concordance of Public Independent Cytotoxicity Measurements.

Improved Chemical Structure-Activity Modeling Through Data Augmentation.

ARWAR: A network approach for predicting Adverse Drug Reactions.

Adamantyl-tethered-biphenylic compounds induce apoptosis in cancer cells by targeting Bcl homologs.

Analysis of Iterative Screening with Stepwise Compound Selection Based on Novartis In-house HTS Data.

Global Mapping of Traditional Chinese Medicine into Bioactivity Space and Pathways Annotation Improves Mechanistic Understanding and Discovers Relationships between Therapeutic Action (Sub)classes.

Trisubstituted-Imidazoles Induce Apoptosis in Human Breast Cancer Cells by Targeting the Oncogenic PI3K/Akt/mTOR Signaling Pathway.

Synthesis and in vitro evaluation of hydrazinyl phthalazines against malaria parasite, Plasmodium falciparum.

Understanding the mode-of-action of Cassia auriculata via in silico and in vivo studies towards validating it as a long term therapy for type II diabetes.

Virtual Activity Profiling of Bioactive Molecules by 1D Fingerprinting.

Extensions to In Silico Bioactivity Predictions Using Pathway Annotations and Differential Pharmacology Analysis: Application to Xenopus laevis Phenotypic Readouts.

Data-Driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening.

Prediction of PARP Inhibition with Proteochemometric Modelling and Conformal Prediction.

Understanding Cytotoxicity and Cytostaticity in a High-Throughput Screening Collection.

Simultaneous Prediction of four ATP-binding Cassette Transporters' Substrates Using Multi-label QSAR.

Analysis of Differential Efficacy and Affinity of GABA (α1/α2) Selective Modulators.

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

In silico target prediction for elucidating the mode of action of herbicides including prospective validation.

Diversity selection, screening and quantitative structure-activity relationships of osmolyte-like additive effects on the thermal stability of a monoclonal antibody.

Fragment Profiling Approach to Inhibitors of the Orphan M. tuberculosis P450 CYP144A1.

Improving Screening Efficiency through Iterative Screening Using Docking and Conformal Prediction.

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

Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson's disease: a comparison of 33 human and animal studies.

Identification of Novel Class of Triazolo-Thiadiazoles as Potent Inhibitors of Human Heparanase and their Anticancer Activity.

Prediction of Antibiotic Interactions Using Descriptors Derived from Molecular Structure.

Polypharmacological in Silico Bioactivity Profiling and Experimental Validation Uncovers Sedative-Hypnotic Effects of Approved and Experimental Drugs in Rat.

Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies.

Towards understanding polyol additive effects on the pH shift-induced aggregation of a monoclonal antibody using high throughput screening and quantitative structure-activity modeling.

Fragment-Based Drug Discovery of Phosphodiesterase Inhibitors.

Fast, Quantitative and Variant Enabled Mapping of Peptides to Genomes.

Orthologue chemical space and its influence on target prediction.

Innovation in Small-Molecule-Druggable Chemical Space: Where are the Initial Modulators of New Targets Published?

Identification of Novel Aurora Kinase A (AURKA) Inhibitors via Hierarchical Ligand-Based Virtual Screening.

Predicting Genes Involved in Human Cancer Using Network Contextual Information.

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

11th German Conference on Chemoinformatics (GCC 2015) : Fulda, Germany. 8-10 November 2015.

Computer-aided design of multi-target ligands at AR, AR and PDE10A, key proteins in neurodegenerative diseases.

Common structural and pharmacophoric features of mPGES-1 and LTC4S.

Maximizing gain in high-throughput screening using conformal prediction.

eMolTox: prediction of molecular toxicity with confidence.

Special Issue: Cheminformatics in Drug Discovery.

A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria.

Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.