Two of our Research Software Engineers have been working with the University eScience Lab on a BioExcel project to develop Conda packages for GROMACS making it easier for researchers to set up and run the software and to increase its reproducibility from computational workflow systems.

In January 2021, our Research Software Engineers worked with the Digital Experimental Cancer Medicine Team (dECMT) to create a tool to support decisions regarding hospital admissions or discharge in cancer patients presenting with symptoms of COVID-19. The tool has been so successful that multiple improvements are now planned.

Cancer patients are at increased risk of severe COVID-19. Decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical. The objective of this project was to identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool - COVID-19 Risk in Oncology Evaluation Tool (CORONET).

When faced with a large dataset from UK Biobank, Alex Casson’s research group needed an easy and quick way to process it. Christopher Beach explains how they tackled this issue with some help from Research IT.

Find out how Research IT research software engineers are playing a key role in SpiNNaker, part of the Human Brain project.

Two of our Research Software Engineers (RSEs) are named on a recently published paper aiming to motivate users to reflect on their search behaviour, and to experiment with different search functionalities.

Researchers from the Tyndall Centre for Climate Change Research at the University of Manchester have been helping local authorities across the UK plan their carbon emissions reduction strategies with a little help from Research IT.

Find out how a research group in the School of MACE are using our HPC resources in conjunction with those at The Hartree Centre, to help Unilever tackle business challenges and to develop new and better products.

Imagine if you could gather data from thousands of mobile data points reacting to the environment around them? That's what our Research Software Engineers have been helping to do and in more than one language thanks to an international collaboration!

As part of the Data Science Research Partnership between BBC R&D and the University of Manchester, one of our research software engineers (RSE), Josh Woodcock, spent 3 months working with BBC R&D to develop a way to visualise click data from an internal trial of the Cook-Along Kitchen Experience (CAKE). Involved in the project were Jonathan Carlton (PhD student with BBC R&D and University of Manchester), Andy Brown (BBC R&D), John Keane and Caroline Jay (University of Manchester).

Research IT has recently been involved in an exciting new use case which aimed to help people with a chronic lung disease self-report the impact of their symptoms on their wellbeing and to view their data.

Traditionally the first step in interpreting video is to code it into a form that can be analysed systematically. The coding process is currently performed manually, and it can be slow and difficult, and biased by subjectivity. David Mawdsley (Research IT) recently presented a poster at the first “Advances in Data Science” conference explaining how we are helping Dr Caroline Jay’s group develop a way to quickly code human behaviours allowing the rapid analysis of hours of video.