Contact and support
Need help, have a question, or want to contact the ResearchHub team?
© 2026 ResearchHub. Built for responsible scholarly connection.
Research graph
References from Predicting zeta potential of liposomes from their structure: A nano-QSPR model for DOPE, DC-Chol, DOTAP, and EPC formulations. Local targets link to admitted publications; unresolved targets remain external evidence.
Negative staining of phospholipids and their structural modification by surface-active agents as observed in the electron microscope
10.1016/s0022-2836(64)80115-7 · 1964 · External reference
Design of liposomes as drug delivery system for therapeutic applications
10.1016/j.ijpharm.2021.120571 · 2021 · External reference
Zeta potential and surface charge of DPPC and DOPC liposomes in the presence of PLC enzyme
10.1007/s10450-016-9767-z · 2016 · External reference
Composition design and medical application of liposomes
10.1016/j.ejmech.2019.01.007 · 2019 · External reference
Liposomes: structure, composition, types, and clinical applications
10.1016/j.heliyon.2022.e09394 · 2022 · External reference
Liposomal formulations in clinical use: an updated review
10.3390/pharmaceutics9020012 · 2017 · External reference
Physico-chemical stability of colloidal lipid particles
10.1016/s0142-9612(03)00331-4 · 2003 · External reference
Nanotoxicology and nanomedicine: the Yin and Yang of nano-bio interactions for the new decade
10.1016/j.nantod.2021.101184 · 2021 · External reference
Representing and describing nanomaterials in predictive nanoinformatics
10.1038/s41565-022-01173-6 · 2022 · External reference
Converting nanotoxicity data to information using artificial intelligence and simulation
10.1021/acs.chemrev.3c00070 · 2023 · External reference
Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles
10.1038/nnano.2011.10 · 2011 · External reference
Zeta potential for metal oxide nanoparticles: a predictive model developed by a nano-quantitative structure-property relationship approach
10.1021/cm504406a · 2015 · External reference
Quasi-SMILES and Nano-QFPR: the predictive model for zeta Potentials of metal oxide nanoparticles
10.1016/j.cplett.2016.08.018 · 2016 · External reference
10.1039/c8en00085a
10.1039/c8en00085a · External reference
A chemoinformatics approach for the characterization of hybrid nanomaterials: safer and efficient design perspective
10.1039/c9nr01162e · 2019 · External reference
Nano-(Q)SAR for cytotoxicity prediction of engineered nanomaterials
10.3390/molecules24244537 · 2019 · External reference
Transcriptomics-based and AOP-informed structure–activity relationships to predict pulmonary pathology induced by multiwalled carbon nanotubes
10.1002/smll.202003465 · 2021 · External reference
In vitro to in vivo extrapolation to support the development of the next generation risk assessment (NGRA) strategy for nanomaterials
2022 · External reference
Quantitative prediction of inorganic nanomaterial cellular toxicity via machine learning
2023 · External reference
10.20944/preprints202210.0402.v1
10.20944/preprints202210.0402.v1 · External reference
First report of Q-RASAR modeling toward an approach of easy interpretability and efficient transferability
10.1007/s11030-022-10478-6 · 2022 · External reference
Read-across and RASAR tools from the DTC laboratory
2023 · External reference
Machine-learning-based similarity meets traditional QSAR: “Q-RASAR” for the enhancement of the external predictivity and detection of prediction confidence outliers in an HERG toxicity dataset
10.1016/j.chemolab.2023.104829 · 2023 · External reference
Development of a novel in silico model of zeta potential for metal oxide nanoparticles: a nano-QSPR approach
10.1088/0957-4484/27/44/445702 · 2016 · External reference
Zeta potentials (ζ) of metal oxide nanoparticles: a meta-analysis of experimental data and a predictive neural networks modeling
10.1016/j.impact.2021.100317 · 2021 · External reference
Core, coating, or corona? The importance of considering protein coronas in nano-QSPR modeling of zeta potential
10.1021/acsnano.2c06977 · 2023 · External reference
The kernel-weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models
10.1186/s13321-021-00484-5 · 2021 · External reference
Predicting the influence of liposomal lipid composition on liposome size, zeta potential and liposome-induced dendritic cell maturation using a design of experiments approach
10.1016/j.ejpb.2015.06.026 · 2015 · External reference
Overcoming roadblocks in computational roadmaps to the future for safe nanotechnology
10.1088/2399-1984/abe560 · 2021 · External reference
Unresolved reference
External reference
What if the number of nanotoxicity data is too small for developing predictive nano-QSAR models? An alternative read-across based approach for filling data gaps
10.1039/c7nr02211e · 2017 · External reference
Classification of surface-active agents by “HLB”
1949 · External reference
Using nano-QSAR to predict the cytotoxicity of metal oxide nanoparticles
10.1038/nnano.2011.10 · 2011 · External reference
Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies
10.3109/17435390.2014.930195 · 2015 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Unresolved reference
External reference
Pre- and post-processing program for molecular and electronic structures
10.1023/a:1008193805436 · 2000 · External reference
Principles of QSAR modeling
2020 · External reference
Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: towards similarity-based machine learning methods
10.1016/j.chemosphere.2021.130681 · 2021 · External reference
10.1787/9789264085442-en
10.1787/9789264085442-en · External reference
Unresolved reference
External reference
Unresolved reference
External reference
10.1007/978-3-319-24277-4
10.1007/978-3-319-24277-4 · External reference
Unresolved reference
External reference
10.18637/jss.v025.i01
10.18637/jss.v025.i01 · External reference
Unresolved reference
External reference