相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Have artificial neural networks met expectations in drug discovery as implemented in QSAR framework?
Dimitar Dobchev et al.
EXPERT OPINION ON DRUG DISCOVERY (2016)
Are the Sublimation Thermodynamics of Organic Molecules Predictable?
James L. McDonagh et al.
Journal of Chemical Information and Modeling (2016)
Phase Transition Enthalpy Measurements of Organic and Organometallic Compounds. Sublimation, Vaporization and Fusion Enthalpies From 1880 to 2015. Part 1. C1-C10
William Acree et al.
JOURNAL OF PHYSICAL AND CHEMICAL REFERENCE DATA (2016)
BioPPSy: An Open-Source Platform for QSAR/QSPR Analysis
Marta Enciso et al.
PLOS ONE (2016)
Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models
D. L. J. Alexander et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2015)
Probabilistic machine learning and artificial intelligence
Zoubin Ghahramani
NATURE (2015)
Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds
Cristina Ventura et al.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY (2013)
Capturing the Crystal: Prediction of Enthalpy of Sublimation, Crystal Lattice Energy, and Melting Points of Organic Compounds
Maryam Salahinejad et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2013)
Simple Alternative to Neural Networks for Predicting Sublimation Enthalpies from Fragment Contributions
Didier Mathieu
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2012)
Comparison of Different Approaches to Define the Applicability Domain of QSAR Models
Faizan Sahigara et al.
MOLECULES (2012)
Simple yet accurate prediction method for sublimation enthalpies of organic contaminants using their molecular structure
Mehdi Bagheri et al.
THERMOCHIMICA ACTA (2012)
Prediction of Crystal Lattice Energy Using Enthalpy of Sublimation: A Group Contribution-Based Model
Farhad Gharagheizi et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2011)
Sublimation of Molecular Crystals: Prediction of Sublimation Functions on the Basis of HYBOT Physicochemical Descriptors and Structural Clusterization
German L. Perlovich et al.
CRYSTAL GROWTH & DESIGN (2010)
Current Mathematical Methods Used in QSAR/QSPR Studies
Peixun Liu et al.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2009)
Quantitative structure-property relationship modelling of the degradability rate constant of alkenes by OH radicals in atmosphere
M. H. Fatemi et al.
SAR AND QSAR IN ENVIRONMENTAL RESEARCH (2009)
MS-DOCK: Accurate multiple conformation generator and rigid docking protocol for multi-step virtual ligand screening
Nicolas Sauton et al.
BMC BIOINFORMATICS (2008)
Advantages of support vector machine in QSPR studies for predicting auto-ignition temperatures of organic compounds
Yong Pan et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2008)
A new molecular-based model for prediction of enthalpy of sublimation of pure components
Farhad Gharagheizi
THERMOCHIMICA ACTA (2008)
Theoretical prediction of heats of sublimation of energetic materials using pseudo-atomic orbital density functional theory calculations
Anguang Hu et al.
PROPELLANTS EXPLOSIVES PYROTECHNICS (2007)
Development and validation of a modular, extensible docking program: DOCK 5
Demetri T. Moustakas et al.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2006)
Comparative study of QSAR/QSPR correlations using support vector machines, radial basis function neural networks, and multiple linear regression
XJ Yao et al.
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2004)
Prediction of skin penetration using artificial neural network (ANN) modeling
T Degim et al.
JOURNAL OF PHARMACEUTICAL SCIENCES (2003)
Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties
P Ertl et al.
JOURNAL OF MEDICINAL CHEMISTRY (2000)
分享论文
