Pages that link to "Q56854153"
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The following pages link to Strategic Pooling of Compounds for High-Throughput Screening (Q56854153):
Displaying 50 items.
- Badapple: promiscuity patterns from noisy evidence (Q27321430) (← links)
- De Novo Fragment Design for Drug Discovery and Chemical Biology (Q27702495) (← links)
- Increasing speed and throughput when using HPLC-MS/MS systems for drug metabolism and pharmacokinetic screening (Q28247246) (← links)
- DOGS: reaction-driven de novo design of bioactive compounds (Q28480868) (← links)
- The open access malaria box: a drug discovery catalyst for neglected diseases (Q28533977) (← links)
- Checking the STEP-Associated Trafficking and Internalization of Glutamate Receptors for Reduced Cognitive Deficits: A Machine Learning Approach-Based Cheminformatics Study and Its Application for Drug Repurposing (Q28548306) (← links)
- The ChEMBL database in 2017 (Q28584450) (← links)
- Computational prediction and validation of an expert's evaluation of chemical probes (Q28829404) (← links)
- Meta-analysis of molecular property patterns and filtering of public datasets of antimalarial “hits” and drugs (Q28842695) (← links)
- New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays (Q29615588) (← links)
- Privileged Structures Revisited (Q30101030) (← links)
- The pK(a) Distribution of Drugs: Application to Drug Discovery (Q30490660) (← links)
- Considerations for designing chemical screening strategies in plant biology. (Q30636976) (← links)
- Library design using BCUT chemistry-space descriptors and multiple four-point pharmacophore fingerprints: simultaneous optimization and structure-based diversity (Q30643727) (← links)
- Library design for NMR-based screening (Q30651042) (← links)
- Visual and computational analysis of structure--activity relationships in high-throughput screening data. (Q30657196) (← links)
- HTS in the new millennium: the role of pharmacology and flexibility (Q30660945) (← links)
- Utility of large-scale transiently transfected cells for cell-based high-throughput screens to identify transient receptor potential channel A1 (TRPA1) antagonists (Q30827889) (← links)
- Prediction of 'drug-likeness'. (Q30829130) (← links)
- Data-mining of potential antitubercular activities from molecular ingredients of traditional Chinese medicines (Q30839938) (← links)
- Determining the optimal size of small molecule mixtures for high throughput NMR screening (Q30849219) (← links)
- Enhancing the hit-to-lead properties of lead optimization libraries (Q30857095) (← links)
- Filtering databases and chemical libraries (Q30883724) (← links)
- Designing chiral libraries for drug discovery (Q30885471) (← links)
- Selection criteria for drug-like compounds (Q30901599) (← links)
- A consensus neural network-based technique for discriminating soluble and poorly soluble compounds. (Q30903074) (← links)
- Enrichment of extremely noisy high-throughput screening data using a naïve Bayes classifier (Q30910355) (← links)
- Simple selection criteria for drug-like chemical matter (Q30990966) (← links)
- Virtual screening using binary kernel discrimination: effect of noisy training data and the optimization of performance (Q31035065) (← links)
- High-throughput identification of promiscuous inhibitors from screening libraries with the use of a thiol-containing fluorescent probe (Q31111842) (← links)
- Design of small molecule libraries for NMR screening and other applications in drug discovery (Q31130509) (← links)
- Molecular diversity management strategies for building and enhancement of diverse and focused lead discovery compound screening collections (Q31133991) (← links)
- High-throughput screening for kinase inhibitors (Q31150791) (← links)
- Selecting compounds for focused screening using linear discriminant analysis and artificial neural networks (Q33203522) (← links)
- Derivation and validation of toxicophores for mutagenicity prediction (Q33210597) (← links)
- Assessment of chemical libraries for their druggability (Q33211319) (← links)
- Computational identification of proteins for selectivity assays (Q33212947) (← links)
- A hierarchical clustering approach for large compound libraries (Q33220363) (← links)
- Surrogate docking: structure-based virtual screening at high throughput speed (Q33227352) (← links)
- An empirical process for the design of high-throughput screening deck filters. (Q33244050) (← links)
- NIPALSTREE: a new hierarchical clustering approach for large compound libraries and its application to virtual screening (Q33264558) (← links)
- Development of a homogeneous calcium mobilization assay for high throughput screening of mas-related gene receptor agonists (Q33267401) (← links)
- Lessons learnt from assembling screening libraries for drug discovery for neglected diseases (Q33309109) (← links)
- Gradual in silico filtering for druglike substances (Q33319499) (← links)
- Evaluation of an orthogonal pooling strategy for rapid high-throughput screening of proteases (Q33348153) (← links)
- FAF-Drugs2: free ADME/tox filtering tool to assist drug discovery and chemical biology projects (Q33371792) (← links)
- Scaffold diversity of natural products: inspiration for combinatorial library design (Q33372355) (← links)
- In silico prediction of drug properties (Q33400509) (← links)
- In silico screening for PTPN22 inhibitors: active hits from an inactive phosphatase conformation (Q33403794) (← links)
- Pooling in high-throughput drug screening. (Q33435425) (← links)