
This dataset contains the raw files, results files and R workspace files (.RData) associated with the paper: Predicting gene expression using morphological cell responses to nanotopography Please note that this dataset is separated according to the Figure presented in the published and peer-reviewed version of the manuscript. Particular folders contain its own README file to facilitate reproduction/replication of results and figures.
machine learning, rational design, biomaterial, high content imaging, image-based profiling, quantitative structure and function
machine learning, rational design, biomaterial, high content imaging, image-based profiling, quantitative structure and function
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
