Why are some properties more difficult to predict than others? A study of QSPR models of solubility, melting point, and Log P.
about
The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTSA review of methods for the calculation of solution free energies and the modelling of systems in solutionUniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike moleculesIs EC class predictable from reaction mechanism?Machine learning methods in chemoinformaticsA Quantitative Structure-Property Relationship (QSPR) Study of aliphatic alcohols by the method of dividing the molecular structure into substructure.Estimating the octanol/water partition coefficient for aliphatic organic compounds using semi-empirical electrotopological index.Comparative molecular field analysis of chromatographic hydrophobicity indices for some coumarin analogs.Using MD Simulations To Calculate How Solvents Modulate Solubility.Literature mining in support of drug discovery.Informatics, machine learning and computational medicinal chemistry.Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology.In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning.How accurately can we predict the melting points of drug-like compounds?Greedy and Linear Ensembles of Machine Learning Methods Outperform Single Approaches for QSPR Regression Problems.The influence of bile salts on the distribution of simvastatin in the octanol/buffer system.Novel high/low solubility classification methods for new molecular entities.Prediction of 1-octanol-water and air-water partition coefficients for nitro-aromatic compounds from molecular dynamics simulations.Can human experts predict solubility better than computers?Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation.On the rational formulation of alternative fuels: melting point and net heat of combustion predictions for fuel compounds using machine learning methods.Economical synthesis of 13C-labeled opiates, cocaine derivatives and selected urinary metabolites by derivatization of the natural products.Accurate calculations of the hydration free energies of druglike molecules using the reference interaction site model.A medicinal chemistry perspective on melting point: matched molecular pair analysis of the effects of simple descriptors on the melting point of drug-like compoundsBenchmarking support vector regression against partial least squares regression and artificial neural network: Effect of sample size on model performance
P2860
Q27902250-46CE848C-A1B3-475A-BC48-1A19626598D3Q28256639-39C54646-528E-4419-A884-AD9FF951EDF7Q28660680-1597CDEB-DB5C-4D4C-837C-8322F8C27C97Q34244212-86CD8A02-929D-4154-A688-48BBF53B0F93Q34271118-E18AA831-224B-4E10-A647-C6E1410E576BQ35079246-277DCB61-46F2-4A30-8AB0-4C23D6F848BEQ35536110-023B2D90-7AB0-4F85-A14C-930F434AB9E2Q36176853-E2317FF1-96AD-4D1A-B22D-348C11455316Q37095169-70F4BBE2-CDF7-4727-8F2A-AB40B5802FF9Q37280361-D64BAD55-67E6-4EE8-AE72-87AF1573EC3BQ37859728-CA8687DB-01A4-4215-BBD0-2BB1F5885B36Q38915404-2FC882E6-51D9-44C2-A71D-C85BA158E9C3Q39071756-1A719E51-2F63-4B94-BBA0-47F5E124DF86Q39079351-4530BBA3-6F52-44C0-A46B-A020C45F1B14Q39525042-96988046-6E4B-49F3-8FE7-1BF158588DA2Q40703785-23817378-22FE-468D-9B99-8E30CBFD0D8DQ40969035-D6302416-0F07-4E8F-8175-2569E34ADD89Q42693896-F2777CDA-AA7D-43EE-978A-C58668CE6FDCQ45942922-699DF7E6-A85F-4995-8B5B-454A27FCE60AQ45950456-010EF13C-9A9B-4A3B-8C68-0D5F28FE42C3Q45959347-173B6C94-CC78-45C6-8F64-F1CC29F9AF02Q47729733-ACABA36B-E851-4042-9BE6-9185312327DFQ51673438-D3D8DB27-9A2F-478E-BBA4-2ECC1D50C312Q56991979-A1DBA303-BF25-4CA0-A8AF-827C480F5206Q57534327-22D1E8F3-55B4-4CB6-B619-717711EB7A61
P2860
Why are some properties more difficult to predict than others? A study of QSPR models of solubility, melting point, and Log P.
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年学术文章
@wuu
2008年学术文章
@zh-cn
2008年学术文章
@zh-hans
2008年学术文章
@zh-my
2008年学术文章
@zh-sg
2008年學術文章
@yue
2008年學術文章
@zh
2008年學術文章
@zh-hant
name
Why are some properties more d ...... ity, melting point, and Log P.
@en
Why are some properties more d ...... ity, melting point, and Log P.
@nl
type
label
Why are some properties more d ...... ity, melting point, and Log P.
@en
Why are some properties more d ...... ity, melting point, and Log P.
@nl
prefLabel
Why are some properties more d ...... ity, melting point, and Log P.
@en
Why are some properties more d ...... ity, melting point, and Log P.
@nl
P356
P1476
Why are some properties more d ...... ity, melting point, and Log P.
@en
P2093
John B O Mitchell
Laura D Hughes
P304
P356
10.1021/CI700307P
P577
2008-01-11T00:00:00Z