Modelling of tissue level carcinogenesis through hybrid, biophysical, and executable approaches
Lead Research Organisation:
University of Cambridge
Department Name: UNLISTED
Abstract
Cancer is a major health concern, with one in three adults developing the disease over their lifetime. However, on a cellular level, the probability of a cell developing into a tumour is very low. Cells prevent the development of tumours through a combination of mechanisms, which operate over different scales. Within a single cell, proteins and genes form signalling pathways which reliably interpret and respond to both the cell state and the cell environment, including specific signals passed from other cells. At the same time, within a tissue, the movements and locations of cells can add a further layer of control, by limiting the communication between cells and mixing populations of cells. I will build mathematical representations (a “model”) of the early stages of tumour formation in cancer which bridges these two phenomena. By running simulations using this model, I will learn more about how the signalling and physical components combine to control cell growth and death in the oesophageal epithelium. I will further mutate and wound my model, to explore how these events can cause a breakdown of the controlling mechanisms and lead to tumour growth.
Technical Summary
Cancer is an important and widespread disease, with roughly one in three adults developing the illness in their lifetime. However, the likelihood of a single cell from the hundreds of trillion cells in the adult human body at any one time developing into a tumour is very low due to intrinsic mechanisms of suppression. Stem cells in the body are made robust to deleterious mutations by a large number of poorly characterised mechanisms. One such mechanism for limiting the damage done by mutations is the competition of stem cells within a population. Whilst recent experimental evidence has given us insight into this competition, observing the dynamics of tissue development experimentally is arduous, and requires use of animals.
The objective of this program is to develop models which give insights into experimentally inaccessible phenomena in the development of cancers, by coupling developmental and physical effects within cells. Some of these models will couple the physical dynamics of cells in the tissue with models of the underlying signalling networks to give us insights into the competition between different mutations. I will use these models to explore the nature of tissue growth and study how external events, such as wounding, can alter this competition and trigger stable populations of cells to develop into a tumour. By explicitly modelling the 3D structure of the tissue, the models will allow us to gain insights into the early stages of tumour formation by showing how changes in stratification rate and shape of the basal layer of stem cells are correlated to changes in cell proliferation rate. Alongside this, I will model cellular localisation processes, working on the dynamics and behaviours of mitochondria in the control of metabolic pathways in cancer cells.
These insights will both suggest new experiments, and highlight the most fruitful lines of experimental enquiry. As such, this programme of work will involve extensive collaboration with different members of the cancer unit. By coupling the expertise of the group, with my own skillset, I will develop a set of approaches and discoveries which guide and support our understanding of cancer development.
The objective of this program is to develop models which give insights into experimentally inaccessible phenomena in the development of cancers, by coupling developmental and physical effects within cells. Some of these models will couple the physical dynamics of cells in the tissue with models of the underlying signalling networks to give us insights into the competition between different mutations. I will use these models to explore the nature of tissue growth and study how external events, such as wounding, can alter this competition and trigger stable populations of cells to develop into a tumour. By explicitly modelling the 3D structure of the tissue, the models will allow us to gain insights into the early stages of tumour formation by showing how changes in stratification rate and shape of the basal layer of stem cells are correlated to changes in cell proliferation rate. Alongside this, I will model cellular localisation processes, working on the dynamics and behaviours of mitochondria in the control of metabolic pathways in cancer cells.
These insights will both suggest new experiments, and highlight the most fruitful lines of experimental enquiry. As such, this programme of work will involve extensive collaboration with different members of the cancer unit. By coupling the expertise of the group, with my own skillset, I will develop a set of approaches and discoveries which guide and support our understanding of cancer development.
Organisations
- University of Cambridge (Lead Research Organisation)
- AstraZeneca (Collaboration)
- University of Toulouse (Collaboration)
- UNIVERSITY OF LEICESTER (Collaboration)
- University of Portsmouth (Collaboration)
- Microsoft Research (Collaboration)
- The Wellcome Trust Sanger Institute (Collaboration)
- Medical Research Council (MRC) (Collaboration)
- UNIVERSITY OF CAMBRIDGE (Collaboration)
Publications
Piedrafita G
(2020)
A single-progenitor model as the unifying paradigm of epidermal and esophageal epithelial maintenance in mice.
in Nature communications
Paterson Y
(2018)
A Toolbox for Discrete Modelling of Cell Signalling Dynamics
Paterson Y
(2018)
A Toolbox for Discrete Modelling of Cell Signalling Dynamics
Paterson YZ
(2018)
A toolbox for discrete modelling of cell signalling dynamics.
in Integrative biology : quantitative biosciences from nano to macro
Clarke M
(2019)
Automated Reasoning for Systems Biology and Medicine
Clarke MA
(2018)
Automated Reasoning for Systems Biology and Medicine 18
Ahmed Z
(2017)
Bringing LTL Model Checking to Biologists
Lee M
(2021)
Cancer-causing BRCA2 missense mutations disrupt an intracellular protein assembly mechanism to disable genome maintenance.
in Nucleic acids research
Related Projects
Project Reference | Relationship | Related To | Start | End | Award Value |
---|---|---|---|---|---|
MC_UU_12022/4 | 30/09/2013 | 30/03/2018 | £882,000 | ||
MC_UU_12022/5 | Transfer | MC_UU_12022/4 | 30/09/2013 | 30/03/2022 | £1,713,000 |
MC_UU_12022/6 | Transfer | MC_UU_12022/5 | 30/09/2013 | 30/03/2022 | £2,157,000 |
MC_UU_12022/7 | Transfer | MC_UU_12022/6 | 30/09/2013 | 30/03/2022 | £2,147,000 |
MC_UU_12022/8 | Transfer | MC_UU_12022/7 | 30/09/2013 | 30/03/2022 | £5,896,000 |
MC_UU_12022/9 | Transfer | MC_UU_12022/8 | 30/09/2014 | 30/03/2022 | £869,000 |
MC_UU_12022/10 | Transfer | MC_UU_12022/9 | 01/01/2015 | 30/03/2022 | £987,000 |
Description | A-level worksheet development with OCR |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | Computational science plays a major role in all branches of the natural sciences. Whilst mathematical models have long played a role in hard sciences, driving uptake of computational techniques, this has spread significantly over the last two decades to include the life sciences. This shift in the sciences reflects a wider change in society as computers and computational thinking become more embedded in all areas of life. Whilst there have been substantive shifts in recent years through efforts such as "Computing at schools" to encourage computer science in early years education, this has been predominantly limited to that discipline. Despite its value being recognised, and the requirement of examination boards for modelling approaches, "computational science" has been slower to be adopted due to lack of appropriate software and developed activites. Over the past QQ we have developed a body of work aimed at A-level students to introduce cancer modelling, based on research at MRC CU. At the heart of this work is the use of the open source BioModelAnalyzer tool (http://biomodelanalyzer.org/), a graphical tool for network model construction and analysis. We have presented demonstrations at the Big Biology day, the Cambridge Science Festival, and the MRC Festival of Science. Through connections made with individual teachers during the MRC Festival, we were approached by Richard Tateson (and later Andri Achilleos) of OCR and worked with OCR to develop A-level worksheets. These were first released in 2018 through OCR forums for teachers, and with a blog post made in early 2019 https://www.ocr.org.uk/blog/getting-started-with-computational-biology-in-cancer-research/. Over the past year this has been evaluated by both the Hall group with A-level work experience students and in local schools and separately by OCR, and as part of this work, the Hall group took part in the new schools hub at the Royal Society Exhibition (Summer 2019), demonstrating the tool for students and sharing worksheets with teachers. In response to the detailed evaluation results and broader feedback from OCR, the worksheets are currently undergoing rewriting in preparation for assessment for inclusion in the curriculum. If approved at the "PAG10" standard, these will be suitable for adoption by up to 60,000 A-level biology students a year in the UK. |
URL | https://www.ocr.org.uk/blog/getting-started-with-computational-biology-in-cancer-research/ |
Description | Azure for Research |
Amount | $20,000 (USD) |
Organisation | Microsoft Research |
Sector | Private |
Country | Global |
Start | 11/2016 |
End | 11/2017 |
Description | MRC Capital Bid |
Amount | £42,000 (GBP) |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2017 |
End | 04/2018 |
Description | MRC NIRG |
Amount | £423,706 (GBP) |
Funding ID | MR/S000216/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2018 |
End | 12/2021 |
Description | Microsoft PhD Scholarship |
Amount | £71,650 (GBP) |
Funding ID | Paper#30 |
Organisation | Microsoft Research |
Sector | Private |
Country | Global |
Start | 09/2016 |
End | 09/2019 |
Description | Research Fellows Enhanced Research Expenses 2021 |
Amount | £168,282 (GBP) |
Funding ID | RF\ERE\210188 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 12/2021 |
End | 03/2023 |
Description | Royal Society (Paul Inst) - The cell as a cell phone |
Amount | £447,097 (GBP) |
Funding ID | UF130039 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2014 |
End | 09/2019 |
Description | Royal Society - Hybrid Models of Early Carcinogenesis |
Amount | £124,477 (GBP) |
Funding ID | RG14040440 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 11/2015 |
End | 10/2018 |
Description | Royal Society Enhancement |
Amount | £82,900 (GBP) |
Funding ID | RGF\EA\180224 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2018 |
End | 01/2022 |
Description | University Research Fellowships Renewals 2019 |
Amount | £475,798 (GBP) |
Funding ID | URF\R\191013 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2020 |
End | 03/2023 |
Title | BioModelAnalyzer software for executable modelling |
Description | BioModelAnalyzer is an open source software tool that enables users with a wide range of computational proficiency to engage in modelling of gene regulatory networks. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | This tool has led to and enabled many publications, and been used in outreach activities |
URL | https://biomodelanalyzer.org/ |
Title | Darwinian shift software tool |
Description | This tool generates complex null hypotheses for the analysis of sequencing data sets |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | This has led to two papers to date and is being integrated into other projects. |
URL | https://github.com/michaelhall28/darwinian_shift |
Title | BioModelAnalyzer |
Description | BioModelAnalyzer is a tool for the development and analysis of executable models |
Type Of Material | Computer model/algorithm |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | This has been used in several different publications, public lectures and demonstrations, and undergraduate and post graduate teaching |
URL | https://biomodelanalyzer.org/ |
Title | Darwinian shift |
Description | Darwinian shift enables hypothesis testing of sequencing datasets by developing powerful null hypotheses |
Type Of Material | Data analysis technique |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | This has been published and is being reused in other tool development |
URL | https://github.com/michaelhall28/darwinian_shift |
Description | AstraZeneca collaboration |
Organisation | AstraZeneca |
Department | Research and Development AstraZeneca |
Country | United Kingdom |
Sector | Private |
PI Contribution | Our team analysed and visualised metabolomics datasets, making new discoveries. |
Collaborator Contribution | AstraZeneca supplied metabolomics data used in the project and consulted on the analysis |
Impact | This has led to the publication "Heterogeneity of the cancer cell line metabolic landscape" in Molecular Systems Biology, 2022 |
Start Year | 2018 |
Description | Bacterial osmoregulatory signalling |
Organisation | University of Portsmouth |
Department | School of Pharmacy and Biomedical Sciences Portsmouth |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Training and hosting of students from Dr Draheim's laboratory in the use of Gromacs and the Sidekick simulation software. Discussion and writing of the manuscript, and analysis of the simulation outputs. |
Collaborator Contribution | Experimental methods and validation. |
Impact | Publication currently under review, available as a pre-print https://www.biorxiv.org/content/early/2018/02/03/206888 |
Start Year | 2015 |
Description | Executable modelling of cancer metabolic networks |
Organisation | AstraZeneca |
Department | Research and Development AstraZeneca |
Country | United Kingdom |
Sector | Private |
PI Contribution | Developing network models and analysing large datasets of metabolic changes in cancer |
Collaborator Contribution | Shared datasets, expertise, and training of members of my lab. |
Impact | This is a multidisciplinary project, involving mathematical modelling, data science, and experimental techniques in cancer metabolism |
Start Year | 2018 |
Description | Executable modelling of cancer metabolic networks |
Organisation | University of Cambridge |
Department | MRC Cancer Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Developing network models and analysing large datasets of metabolic changes in cancer |
Collaborator Contribution | Shared datasets, expertise, and training of members of my lab. |
Impact | This is a multidisciplinary project, involving mathematical modelling, data science, and experimental techniques in cancer metabolism |
Start Year | 2018 |
Description | Formal verification of biological models |
Organisation | Microsoft Research |
Department | Microsoft Research Cambridge |
Country | United Kingdom |
Sector | Private |
PI Contribution | Provide biological expertise that is used to help drive tool development forward |
Collaborator Contribution | MSR develops and supports new tools for analysing and simulating biological models, supported by computer scientists at Leicester. |
Impact | This is an interdisciplinary collaboration (computer science and computational biology). Two papers have arisen from the work. Emergent Behaviours of Stem Cells in Organogenesis Demonstrated by Hybrid Modelling Drug Target Optimization in Chronic Myeloid Leukemia Using Innovative Computational Platform |
Start Year | 2014 |
Description | Formal verification of biological models |
Organisation | University of Leicester |
Department | Department of Computer Science |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Provide biological expertise that is used to help drive tool development forward |
Collaborator Contribution | MSR develops and supports new tools for analysing and simulating biological models, supported by computer scientists at Leicester. |
Impact | This is an interdisciplinary collaboration (computer science and computational biology). Two papers have arisen from the work. Emergent Behaviours of Stem Cells in Organogenesis Demonstrated by Hybrid Modelling Drug Target Optimization in Chronic Myeloid Leukemia Using Innovative Computational Platform |
Start Year | 2014 |
Description | Large scale analysis of gene regulatory networks |
Organisation | University of Toulouse |
Country | France |
Sector | Academic/University |
PI Contribution | My team develop and maintain the BioModelAnalyzer tool, used in this project |
Collaborator Contribution | The partners have developed large scale models and contributed code to the BioModelAnalyzer, enabling the code to run on Unix systems |
Impact | This has led to one publication (Zerrouk et al, 2024) |
Start Year | 2021 |
Description | Metabolic maps of cancer |
Organisation | AstraZeneca |
Country | United Kingdom |
Sector | Private |
PI Contribution | Analysis of cell line metabolomics data |
Collaborator Contribution | Generation of metabolomics data |
Impact | None at present |
Start Year | 2018 |
Description | Modelling clonal competition in epithelial tissues (Prof P Jones) |
Organisation | The Wellcome Trust Sanger Institute |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Phil Jones' laboratory studies the growth of individual clones in epithelial tissues, generating a broad array of datatypes. My research team develop models of clonal development and competition that allow for the quantification of key parameters. The mathematical models further aid hypothesis development, allowing us to explore how the tissue grows and develops in response to mutation. |
Collaborator Contribution | Phil Jones' laboratory studies the growth of individual clones in epithelial tissues, generating a broad array of datatypes. My research team develop models of clonal development and competition that allow for the quantification of key parameters. The mathematical models further aid hypothesis development, allowing us to explore how the tissue grows and develops in response to mutation. |
Impact | Manuscripts presently under review |
Start Year | 2015 |
Description | Modelling stromal function in tumour draining lymph nodes |
Organisation | Medical Research Council (MRC) |
Department | MRC Cancer Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This a collaboration between computational biologists and wet lab experimentalists. Experiments yielding large amounts of data were performed by the Shields Lab and analysed by us. This data was then used as a basis for modelling systems, where the predictions were functionally verified by members of the Shields lab. |
Collaborator Contribution | This a collaboration between computational biologists and wet lab experimentalists. Experiments yielding large amounts of data were performed by the Shields Lab and analysed by us. This data was then used as a basis for modelling systems, where the predictions were functionally verified by members of the Shields lab. |
Impact | Riedel et al Nature Immunology 2016. This is a multidisciplinary collaboration crossing wet lab and in silica approaches |
Start Year | 2015 |
Title | BioModelAnalyzer |
Description | BioModelAnalyzer is a platform for the development and analysis of biological network models. It primarily uses formal verification approaches, developed in software research, to analyse complex models. |
Type Of Technology | Software |
Year Produced | 2017 |
Open Source License? | Yes |
Impact | Software has been adopted by AstraZeneca and is being used to model new biological networks rapidly and where precise quantities are not available. |
URL | https://github.com/Microsoft/BioModelAnalyzer |
Title | BioModelAnalyzer |
Description | Software for the construction and analysis of executable models |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | Added features that enable model and motif construction through the introduction of selection and copy tools |
URL | http://biomodelanalyzer.org/ |
Title | BioModelAnalyzer |
Description | Software for the development and analysis of executable models |
Type Of Technology | Software |
Year Produced | 2020 |
Open Source License? | Yes |
Impact | Design refinements and unification of model and motif library, easing the use and reuse of models |
URL | http://biomodelanalyzer.org/ |
Title | BioModelAnalyzer |
Description | Working with AstraZeneca and Microsoft Research, my team developed a library of reusable motifs to make model construction easier. These motifs have been written up as a manuscript (under review, and available as a pre-print https://www.biorxiv.org/content/early/2018/01/18/249888). We have further developed a novel interface to access these motifs available from the github repository. A test deployment (intended to go into production 5/3/2018) is available http://bmainterfacetest.azurewebsites.net/ |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | This has supported the take up of the tool by AstraZeneca by demonstrating the expressivity of the underlying mathematical formalism, and has lead to its adoption by researchers within AZ. |
URL | http://biomodelanalyzer.org/ |
Title | BioModelAnalyzer (2021 |
Description | BioModelAnalyzre is a tool for the construction and analysis of executable models of biological systems |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | Taught at workshop, masters courses, and used heavily in my research |
URL | https://biomodelanalyzer.org/ |
Title | CaSQ |
Description | Software tool for converting formats for describing network maps to models automatically. I added support for BioModelAnalyzer export. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | Will be adopted in the near future by students from collaborators groups. |
URL | https://github.com/soli/casq |
Title | Darwinian shift |
Description | Darwinian shift enables construction of null hypotheses for analysing sequencing datasets |
Type Of Technology | Software |
Year Produced | 2022 |
Open Source License? | Yes |
Impact | Several publications have used this |
URL | https://github.com/michaelhall28/darwinian_shift |
Title | OmnipathR |
Description | Tool for the extraction of networks from the omnipath database of gene interactions. I added BMA motif export support. |
Type Of Technology | Software |
Year Produced | 2019 |
Open Source License? | Yes |
Impact | Aids adoption in the community |
URL | https://bioconductor.org/packages/OmnipathR |
Title | ProPPA |
Description | ProPPA is a software developed at the University of Edinburgh by the group of Professor Jane Hillston. The tool allows inference of parameters in continuous models through a variety of different algorithms. |
Type Of Technology | Software |
Year Produced | 2017 |
Impact | My group has contributed bug reports, feature requests and code to the ProPPA tool, supporting development and adoption of the tool in the life sciences. |
URL | https://github.com/ageorgou/ProPPA |
Title | Sidekick (automated transmembrane helix simulation) |
Description | Sidekick automates the high throughput molecular dynamics simulation of transmembrane helices, from an input sequence. Systems are constructed, simulated, and analysed in an wholly automated process that can be controlled through a web based GUI. |
Type Of Technology | Software |
Year Produced | 2015 |
Open Source License? | Yes |
Impact | This software is used by different groups in the UK who have joined my lab to learn how to deploy and develop the tool. |
URL | https://github.com/hallba/Sidekick |
Description | A-level student projects |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | A 4-week project in structural biology of ion channels was developed for an A-level student (Upasana Das). The student learned how to use unix, build homology models, visualise protein structure and compare and contrast epilepsy causing mutations with cancer associated mutations. The student was awarded a CREST Gold award for a report written about the work done in my laboratory. Additionally, my laboratory hosted another A-level student for a week who worked on analyzing BioModelAnalyzer models of cancer. |
Year(s) Of Engagement Activity | 2017 |
Description | Big Biology Day 2016 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | The Biog Biology Day is an annual event organised at the Hills Road Sixth Form College in Cambridge. Attended by well over 1000 people overall, the event draws expertise from both the local scientific and biotech/pharma community and helps reach out to children across a wide age range and to accompanying adults alike, from across the region. Dr David Shorthouse from the Ben Hall laboratory of the MRC CU demonstrated the use of Modelling and Computational approaches in the study of diseases such as Cancer and drew a lot of attention to this approach, including from reprresentatives of school examination boards. |
Year(s) Of Engagement Activity | 2015,2016 |
URL | http://www.hillsroad.ac.uk/college-life/events/2016/10/15/default-calendar/big-biology-day |
Description | Filming of the work and motivations of the Hall group |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Two videos were generated describing work in my laboratory. One showed me explaining the motivations for my work and the broad overview of the lab, whilst the second showcased individual work in the laboratory. The videos raised awareness of the work done in my laboratory (full video views totally ~250, associated tweet engagements >3500) and led directly to new discussions with researchers in other institutions (Moffit Cancer Centre, University of Oxford). It further directly led to one student application to join the group. |
Year(s) Of Engagement Activity | 2017 |
Description | Lectures on teaching modelling cancer biology |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | Spoke at two Wellcome Connecting Science events to teachers (A-level and T-level) about how to model cancer development. |
Year(s) Of Engagement Activity | 2023 |
URL | https://www.stem.org.uk/cpd/ondemand/519920/cutting-edge-science-genomics-and-artificial-intelligenc... |
Description | MRC Festival of Science 2017 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Software demonstrations, activities, and talks given by myself and my laboratory to A-level students |
Year(s) Of Engagement Activity | 2017 |
Description | MRC Roadshow |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Visited Comberton school where I and members of my group gave talks on careers in research and demonstrations of research software. |
Year(s) Of Engagement Activity | 2017 |
Description | News coverage of JBC publication in MRC Network |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | A news article was published in MRC Network in response to a recently published paper in the Journal of Biological Chemistry. This raised awareness of recent research into the atomic structure of IKK-gamma and the overall implications of this research. |
Year(s) Of Engagement Activity | 2015 |
URL | https://www.mrc.ac.uk/publications/browse/network-autumn-2015/ |
Description | News coverage of JBC publication on MRC website |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | A news article featured on the MRC website in response to a recently published paper in the Journal of Biological Chemistry. This raised awareness of recent research into the atomic structure of IKK-gamma and the overall implications of this research. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.mrc.ac.uk/news/browse/cell-switch-discovered-that-could-shed-light-on-cancer/ |
Description | Participation in MRC Festival of Science Open Day 2016 at MRC CU |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | 60 sixth-form students from across 8 schools in Cambridge visited the MRC Cancer Unit on the afternoon of the 22nd of June, 2016 for an Open Day. All students, accompanied by their teachers, were given a tour of the enitre building with an opportunity for engaging with researchers about the state of the art in cancer research and gaining hands-on experience with setting up experiments. Talks about career opportunities and challenges associated with pursuing cancer research were also available to all attendees. The event sparked a great deal of interest and enthusiasm in students and teachers alike and we have had a request for this event to be continued. We will be pursuing a similar format of activities for the MRC Science Festival in 2017, but reach out to more number of schools, including those outside of Cambridge city perimeters. |
Year(s) Of Engagement Activity | 2016 |
URL | https://mrccancerunit.wordpress.com/2016/07/06/inspiring-the-next-generation-of-cancer-researchers-t... |
Description | Participation in the University of Cambridge Science Festival (2015, 2016, 2017, 2018) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | The Cambridge Science Festival aims to reach out to the general public and communicate about the different aspects of science and research being undertaken at the University. It is a free event, over two weeks, with an excess of 270 events and more than 50000 attendees last year. As part of this, the MRC CU along with other departments from the BioMedical Campus organised a set of talks and activities on the BioMed Campus day of the Festival that were attended by over 2000 people from all walks of life - from young children and young adults to parents/carers and professionals. The Hall lab was part of the MRC CU team at this event. The event generated a lot of interest in cancer research, helped raise awareness about the importance of 'early' in cancer which is the mission of the MRc CU and also led to a lot of interest being generated in the MRC Festival of Medical Research which followed on later in the year. |
Year(s) Of Engagement Activity | 2015,2016,2017,2018 |
URL | https://www.mrc-cu.cam.ac.uk/PublicEngagement/publicengagementhighlights |
Description | School practical session (Perse) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | Around 20 A-level students attended a short talk and a practical session run by myself using the BioModelAnalyzer. Students enjoyed the practical and gave extensive feedback which will be included in future updates. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.instagram.com/p/B3uJGNJpToD/ |
Description | Talk at Hills Road Sixth form |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | Gave an invited talk about my research program and careers in research to A-level students. |
Year(s) Of Engagement Activity | 2017 |
Description | Think Computer Science |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Schools |
Results and Impact | Several schools attended a day of talks, demos and practical demonstrations aimed at engaging children with computer science. There was press coverage (BBC radio Cambridgeshire). Strong positive feedback from participating schools with > 90 % of pupils reporting that the talks and demos were interesting and informative, 82 % reporting that it had increased their interest in computer science, and 68 % stating that it had inspired them to learn how to code. |
Year(s) Of Engagement Activity | 2014 |
URL | http://research.microsoft.com/en-us/um/cambridge/events/thinkcomputerscience/ |
Description | Visit to AstraZeneca Cambridge |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Invited to give a presentation, attend meetings and view facilities at AZ Cambridge by Drs Claus Bendtsen and Matt Bridgland-Taylor. |
Year(s) Of Engagement Activity | 2017 |