about
Binding inhibitors of the bacterial sliding clamp by designA general model for binary cell fate decision gene circuits with degeneracy: indeterminacy and switch behavior in the absence of cooperativityMaterials Genome in Action: Identifying the Performance Limits of Physical Hydrogen StorageThe role of quantitative structure--activity relationships (QSAR) in biomolecular discovery.Neural networks as robust tools in drug lead discovery and development.Toward novel universal descriptors: charge fingerprints.The X-ray structure of a hemipteran ecdysone receptor ligand-binding domain: comparison with a lepidopteran ecdysone receptor ligand-binding domain and implications for insecticide design.Critical-like self-organization and natural selection: two facets of a single evolutionary process?Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces.Getting to the source: selective drug targeting of cancer stem cells.Sparse feature selection identifies H2A.Z as a novel, pattern-specific biomarker for asymmetrically self-renewing distributed stem cells.Sparse feature selection methods identify unexpected global cellular response to strontium-containing materials.Discovery of a Novel Polymer for Human Pluripotent Stem Cell Expansion and Multilineage DifferentiationAn Experimental and Computational Approach to the Development of ZnO Nanoparticles that are Safe by Design.Bayesian regularization of neural networks.Toward a Rosetta stone for the stem cell genome: stochastic gene expression, network architecture, and external influences.Stem cell decision making and critical-like exploratory networks.Tripeptide motifs in biology: targets for peptidomimetic design.Principal signalling complexes in haematopoiesis: structural aspects and mimetic discovery.Self-organizing circuitry and emergent computation in mouse embryonic stem cells.Quantitative structure-property relationship modeling of diverse materials properties.Applying quantitative structure-activity relationship approaches to nanotoxicology: current status and future potential.Materials for stem cell factories of the future.Computational Modeling and Simulation of CO2 Capture by Aqueous Amines.Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials.The diverse biological properties of the chemically inert noble gases.A renaissance of neural networks in drug discovery.Validating Eaton's Hypothesis: Cubane as a Benzene Bioisostere.A Bright Future for Evolutionary Methods in Drug Design.Modelling and predicting the biological effects of nanomaterials.Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.Aluminum toxicity risk reduction as a result of reduced acid deposition in Adirondack lakes and ponds.Illuminating Flash Point: Comprehensive Prediction Models.Predictive mesoscale network model of cell fate decisions during C. elegans embryogenesis.Beware of R(2): Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models.Relevance Vector Machines: Sparse Classification Methods for QSAR.Immobilisation of a thrombopoietin peptidic mimic by self-assembled monolayers for culture of CD34+ cells.Synthesis, binding and bioactivity of gamma-methylene gamma-lactam ecdysone receptor ligands: advantages of QSAR models for flexible receptors.Zinc is not required for activity of TPO agonists acting at the c-Mpl receptor transmembrane domain.Modeling the molecular basis for α4β1 integrin antagonism.
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description
researcher ORCID: 0000-0002-7301-6076
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name
David A Winkler
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David A Winkler
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David A Winkler
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David A Winkler
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David A Winkler
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David A Winkler
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David A Winkler
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David A Winkler
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Dave Winkler
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David Winkler
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David A Winkler
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David A Winkler
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David A Winkler
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David A Winkler
@nl
P106
P21
P31
P496
0000-0002-7301-6076