pnn learner node (KNIME GmbH)
90
Structured Review
KNIME GmbH
pnn learner node
Pnn Learner Node, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/pnn+learner+node/pnn+learner+node/pmc08373588-424-2-6
Average 90 stars, based on 1 article reviews
Pnn Learner Node, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/pnn+learner+node/pnn+learner+node/pmc08373588-424-2-6
Average 90 stars, based on 1 article reviews
pnn learner node - by Bioz Stars,
2026-11
90/100 stars
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other:Article Title: Protein characteristics substantially influence the propensity of activity cliffs among kinase inhibitors. Article Snippet: On the other hand, we chose to assess the probabilistic Article Title: Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study. Article Snippet: Activity cliffs (ACs) are defined as closely analogous compounds of significant affinity discrepancies against certain biotarget.. In this paper we propose to use AC pair(s) for extracting valid binding pharmacophores through exposing corresponding protein complexes to stochastic deformation/relaxation followed by applying genetic algorithm/machine learning (GA-ML) for selecting optimal pharmacophore(s) that best classify a long list of inhibitors.. We compared the performances of ligandbased and structure-based pharmacophores with counterparts generated by this newly introduced technique. Article Title: Docking-generated multiple ligand poses for bootstrapping bioactivity classifying Machine Learning: Repurposing covalent inhibitors for COVID-19-related TMPRSS2 as case study Article Snippet: We implemented PNN Learner node within Article Title: Protein characteristics substantially influence the propensity of activity cliffs among kinase inhibitors. Article Snippet: We implemented PNN Learner node within Article Title: Computational methods for prediction of in vitro effects of new chemical structures Article Snippet: PNN based model was implemented with the PNN learner and Article Title: Investigating the association of CD36 gene polymorphisms (rs1761667 and rs1527483) with T2DM and dyslipidemia: Statistical analysis, machine learning based prediction, and meta-analysis Article Snippet: We implemented PNN Learner node within Article Title: Protein characteristics substantially influence the propensity of activity cliffs among kinase inhibitors Article Snippet: On the other hand, we chose to assess the probabilistic Activity Assay:Article Title: Discovery of New STAT3 Inhibitors as Anticancer Agents Using Docking-Based Ligand- Receptor Contacts Fingerprints and Bioactivity - Classifying Machine Learning Article Snippet: .. PNN models were built using the PNN learner node default settings within |