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"The advantage of learning how to create workflows on the NeSI HPC platform, is that we could create reproducible science which enables better collaboration amongst scientists."
“Analysing this type of data is very computationally heavy. Last week I analysed seven new data sets in two days. Now we have additional 3D structured genome data sets from different tissues and cell types. It is amazing.”
"Beyond the tangible performance improvements, NeSI have helped us improve our workflow and tooling, and have been an amazing source of feedback for large-scale scientific software development and deployment. "
"Our goal is to create a piece of software that is capable of automatically analysing hundreds of thousands of pupil-tracked coordinates. This would allow a clinician to interpret the results and guide clinical decision making in real-world practice."
“Use of NeSI was central to our software development. We don’t know how big models will get in the future, so we wanted to make this as scalable as possible."