标题
Sparse QSAR modelling methods for therapeutic and regenerative medicine
作者
关键词
Quantitative structure–activity relationships, QSAR, Machine learning, Deep learning, Sparse feature selection, Regenerative medicine, Skolnik award
出版物
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
Volume -, Issue -, Pages -
出版商
Springer Nature
发表日期
2018-02-14
DOI
10.1007/s10822-018-0106-1
参考文献
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。- Prediction of Broad-Spectrum Pathogen Attachment to Coating Materials for Biomedical Devices
- (2018) Paulius Mikulskis et al. ACS Applied Materials & Interfaces
- Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
- (2018) Rafael Gómez-Bombarelli et al. ACS Central Science
- Discovery and Optimization of Materials Using Evolutionary Approaches
- (2016) Tu C. Le et al. CHEMICAL REVIEWS
- Understanding the Roles of the “Two QSARs”
- (2016) Toshio Fujita et al. Journal of Chemical Information and Modeling
- Optimization of drug combinations using Feedback System Control
- (2016) Patrycja Nowak-Sliwinska et al. Nature Protocols
- Recent advances, and unresolved issues, in the application of computational modelling to the prediction of the biological effects of nanomaterials
- (2016) David A. Winkler TOXICOLOGY AND APPLIED PHARMACOLOGY
- A Bright Future for Evolutionary Methods in Drug Design
- (2015) Tu C. Le et al. ChemMedChem
- Relevance Vector Machines: Sparse Classification Methods for QSAR
- (2015) Frank R. Burden et al. Journal of Chemical Information and Modeling
- Beware of R2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models
- (2015) D. L. J. Alexander et al. Journal of Chemical Information and Modeling
- Sparse feature selection methods identify unexpected global cellular response to strontium-containing materials
- (2015) Hélène Autefage et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Modelling and Prediction of Bacterial Attachment to Polymers
- (2013) V. C. Epa et al. ADVANCED FUNCTIONAL MATERIALS
- Aqueous Solubility Prediction: Do Crystal Lattice Interactions Help?
- (2013) Maryam Salahinejad et al. MOLECULAR PHARMACEUTICS
- Quantitative Structure–Property Relationship Modeling of Diverse Materials Properties
- (2012) Tu Le et al. CHEMICAL REVIEWS
- Robust, quantitative tools for modelling ex-vivo expansion of haematopoietic stem cells and progenitors
- (2012) David A. Winkler et al. Molecular BioSystems
- Modeling Biological Activities of Nanoparticles
- (2012) V. Chandana Epa et al. NANO LETTERS
- Combinatorial discovery of polymers resistant to bacterial attachment
- (2012) Andrew L Hook et al. NATURE BIOTECHNOLOGY
- Applying quantitative structure–activity relationship approaches to nanotoxicology: Current status and future potential
- (2012) David A. Winkler et al. TOXICOLOGY
- Toward Novel Universal Descriptors: Charge Fingerprints
- (2009) Frank R. Burden et al. Journal of Chemical Information and Modeling
- An Optimal Self-Pruning Neural Network and Nonlinear Descriptor Selection in QSAR
- (2009) Frank R. Burden et al. Quantitative structure-activity relationships & combinatorial science
- Optimal Sparse Descriptor Selection for QSAR Using Bayesian Methods
- (2009) F. R. Burden et al. Quantitative structure-activity relationships & combinatorial science
- Consistent concepts of self-organization and self-assembly
- (2008) Julianne. D. Halley et al. COMPLEXITY
- Classification of emergence and its relation to self-organization
- (2008) Julianne. D. Halley et al. COMPLEXITY
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started