Strategic Alliance Funding: MRC Weatherall Institute of Molecular Medicine (WIMM) at the University of Oxford 22-27
Lead Research Organisation:
University of Oxford
Department Name: UNLISTED
Abstract
Modern biomedical research is driven by advanced technologies, the generation of massive multidimensional datasets and advanced computational analysis is critical for their use. Similarly, research institutes must be able to adopt cutting-edge experimental approaches, such as single cell technologies. However, the huge complexity of these data puts even more pressure on computational biology and machine learning approaches.
In this proposal we laid out our strategic plan to redevelop and focus the computational infrastructure of the WIMM to meet these challenges. To build on existing expertise, to centralise and build synergy between these expert groups. We have made key hires, from diverse fields such as mathematics and computer science, with such expertise. We are developing critical computational talent, by promoting and mentoring young computational scientists from the WIMM. A critical goal for us is to expand and democratise these skills in the WIMM, through new training programmes, in particular with students. We have now completely modernised our High Performance Cluster in both speed and capacity and instituted a sustainable charging business model for long term stability.
In this proposal we laid out our strategic plan to redevelop and focus the computational infrastructure of the WIMM to meet these challenges. To build on existing expertise, to centralise and build synergy between these expert groups. We have made key hires, from diverse fields such as mathematics and computer science, with such expertise. We are developing critical computational talent, by promoting and mentoring young computational scientists from the WIMM. A critical goal for us is to expand and democratise these skills in the WIMM, through new training programmes, in particular with students. We have now completely modernised our High Performance Cluster in both speed and capacity and instituted a sustainable charging business model for long term stability.
Technical Summary
In the proposal, we outlined the plans to develop our expertise in machine learning and implement them into research areas at the WIMM. Below is the progress we have made according to the main objectives set in our proposal:
1. Develop Expertise in Machine Learning
2. Develop Critical Computational Talent
3. Training in Advanced Computational Approaches
4. Expand and Modernise High-Performance Cluster (HPC) / Computing Hub
5. Digital Communications:
The MRC investment has matched the funding provided by the University of Oxford and allowed us to recruit a Digital Productions Officer.
Together with the Institute’s Communications and Public Engagement Officer, this new role is developing video and audio summaries of research, facilities and engagement resources to increase the reach, impact and longevity of our communications and engagement work.
These objectives demonstrate the Institute's commitment to advancing research through ML-AI, developing computational talent, offering diverse training, upgrading computing infrastructure, and enhancing digital communication for broader outreach and impact.
1. Develop Expertise in Machine Learning
2. Develop Critical Computational Talent
3. Training in Advanced Computational Approaches
4. Expand and Modernise High-Performance Cluster (HPC) / Computing Hub
5. Digital Communications:
The MRC investment has matched the funding provided by the University of Oxford and allowed us to recruit a Digital Productions Officer.
Together with the Institute’s Communications and Public Engagement Officer, this new role is developing video and audio summaries of research, facilities and engagement resources to increase the reach, impact and longevity of our communications and engagement work.
These objectives demonstrate the Institute's commitment to advancing research through ML-AI, developing computational talent, offering diverse training, upgrading computing infrastructure, and enhancing digital communication for broader outreach and impact.
Organisations
People |
ORCID iD |
Publications
Antanaviciute A
(2022)
Lymphatic endothelia stakeout cryptic stem cells.
in Cell stem cell
Buckley P
(2023)
A systems approach evaluating the impact of SARS-CoV-2 variant of concern mutations on CD8+ T cell responses
in Immunotherapy Advances
Hudson D
(2024)
A comparison of clustering models for inference of T cell receptor antigen specificity
in ImmunoInformatics
Lee C
(2023)
A robust deep learning workflow to predict CD8 + T-cell epitopes
in Genome Medicine
Matute JD
(2023)
Intelectin-1 binds and alters the localization of the mucus barrier-modifying bacterium Akkermansia muciniphila.
in The Journal of experimental medicine
Repapi E
(2023)
Integration of single-cell RNA-Seq and CyTOF data characterises heterogeneity of rare cell subpopulations
in F1000Research
Riva SG
(2023)
CATCH-UP: A High-Throughput Upstream-Pipeline for Bulk ATAC-Seq and ChIP-Seq Data.
in Journal of visualized experiments : JoVE
Sharma AB
(2023)
C16orf72/HAPSTR1/TAPR1 functions with BRCA1/Senataxin to modulate replication-associated R-loops and confer resistance to PARP disruption.
in Nature communications
Related Projects
Project Reference | Relationship | Related To | Start | End | Award Value |
---|---|---|---|---|---|
MC_UU_00021/2 | 31/03/2022 | 30/03/2027 | £1,504,670 | ||
MC_UU_00021/3 | Transfer | MC_UU_00021/2 | 31/08/2022 | 30/03/2023 | £60,578 |