experimental workflows (Novartis)
Structured Review
Experimental Workflows, supplied by Novartis, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/workflow/experimental+workflows/pm42288212-15-9-1
Average 86 stars, based on 1 article reviews
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other:Article Title: CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data Article Snippet: The workflow written in the R programming language is deposited in Article Title: Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects. Article Snippet: Medicinal chemistry and drug design efforts can be assisted by machine learning (ML) models that relate the molecular structure to compound properties.. Such quantitative structure−property relationship models are generally trained on large data sets that include diverse chemical series (global models).. In the pharmaceutical industry, these ML global models are available across discovery projects as an “out-ofthe-box” solution to assist in drug design, synthesis prioritization, and experiment selection. Formulation:Article Title: ReSCoSS: a flexible quantum chemistry workflow identifying relevant solution conformers of drug-like molecules. Article Snippet: Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods.. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework.. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known. |

