Dr GRAZZIELA FIGUEREDO's Outputs (8)

Monitoring university student response to social distancing policy during the SARS-CoV-2 pandemic using Bluetooth: the RADAR study (2024)
Journal Article
Bolton, K. J., Mendez-Villalon, A., Nanji, H., Jia, R., Ayling, K., Figueredo, G., & Vedhara, K. (2024). Monitoring university student response to social distancing policy during the SARS-CoV-2 pandemic using Bluetooth: the RADAR study. Mathematics in Medical and Life Sciences, 1(1), Article 2425096. https://doi.org/10.1080/29937574.2024.2425096

Aim: We use the Remote Assessment of Disease and Relapses platform (RADAR) to collect Bluetooth contact and location data from university students. We test the ability of this technology to objectively capture social interaction, explore the propensi... Read More about Monitoring university student response to social distancing policy during the SARS-CoV-2 pandemic using Bluetooth: the RADAR study.

Association between Nutritional Status Assessed by Body Mass Index and Crohn’s Disease Phenotype: A Nation-Wide Analysis (2024)
Journal Article
Ndzo, J., Vuyyuru, S. K., Trimble, T., Yan, K., Figueredo, G., & Moran, G. W. (in press). Association between Nutritional Status Assessed by Body Mass Index and Crohn’s Disease Phenotype: A Nation-Wide Analysis. Journal of Crohn's and Colitis,

Background & Aims:

Incidence of obesity and Crohn’s disease (CD) is increasing globally. Therefore, understanding any associations between adiposity and disease phenotype is crucial. We aimed explore the relationship between nutritional status me... Read More about Association between Nutritional Status Assessed by Body Mass Index and Crohn’s Disease Phenotype: A Nation-Wide Analysis.

Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP (2022)
Journal Article
Quinlan, P. R., Figeuredo, G., Mongan, N., Jordan, L. B., Bray, S. E., Sreseli, R., Ashfield, A., Mitsch, J., van den Ijssel, P., Thompson, A. M., & Quinlan, R. A. (2022). Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP. Cell Stress and Chaperones, 27(2), 177-188. https://doi.org/10.1007/s12192-022-01258-0

Our cluster analysis of the Cancer Genome Atlas for co-expression of HSP27 and CRYAB in breast cancer patients identified three patient groups based on their expression level combination (high HSP27 + low CRYAB; low HSP27 + high CRYAB; similar HSP27 ... Read More about Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP.

Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion (2021)
Journal Article
Rengasamy, D., Rothwell, B. C., & Figueredo, G. P. (2021). Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion. Applied Sciences, 11(24), Article 11854. https://doi.org/10.3390/app112411854

When machine learning supports decision-making in safety-critical systems, it is important to verify and understand the reasons why a particular output is produced. Although feature importance calculation approaches assist in interpretation, there is... Read More about Towards a more reliable interpretation of machine learning outputs for safety-critical systems using feature importance fusion.

Single-Cell Tracking on Polymer Microarrays Reveals the Impact of Surface Chemistry on Pseudomonas aeruginosa Twitching Speed and Biofilm Development (2020)
Journal Article
Carabelli, A. M., Isgró, M., Sanni, O., Figueredo, G. P., Winkler, D. A., Burroughs, L., Blok, A. J., Dubern, J. F., Pappalardo, F., Hook, A. L., Williams, P., & Alexander, M. R. (2020). Single-Cell Tracking on Polymer Microarrays Reveals the Impact of Surface Chemistry on Pseudomonas aeruginosa Twitching Speed and Biofilm Development. ACS Applied Bio Materials, 3(12), 8471–8480. https://doi.org/10.1021/acsabm.0c00849

© 2020 American Chemical Society. Bacterial biofilms exhibit up to 1000 times greater resistance to antibiotic or host immune clearance than planktonic cells. Pseudomonas aeruginosa produces retractable type IV pili (T4P) that facilitate twitching mo... Read More about Single-Cell Tracking on Polymer Microarrays Reveals the Impact of Surface Chemistry on Pseudomonas aeruginosa Twitching Speed and Biofilm Development.

An innovative approach to multi-method integrated assessment modelling of global climate change (2020)
Journal Article
Siebers, P. O., Lim, Z. E., Figueredo, G. P., & Hey, J. (2020). An innovative approach to multi-method integrated assessment modelling of global climate change. Journal of Artificial Societies and Social Simulation, 23(1), Article 10. https://doi.org/10.18564/jasss.4209

© 2020, University of Surrey. All rights reserved. Modelling and simulation play an increasingly significant role in exploratory studies for informing policy makers on climate change mitigation strategies. There is considerable research being done in... Read More about An innovative approach to multi-method integrated assessment modelling of global climate change.

Fuzzy Hot Spot Identification for Big Data: An Initial Approach (2019)
Presentation / Conference Contribution
Triguero, I., Tickle, R., Figueredo, G. P., Mesgarpour, M., Ozcan, E., & John, R. I. (2019, June). Fuzzy Hot Spot Identification for Big Data: An Initial Approach. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of iden... Read More about Fuzzy Hot Spot Identification for Big Data: An Initial Approach.

PAS3-HSID: a Dynamic Bio-Inspired Approach for Real-Time Hot Spot Identification in Data Streams (2019)
Journal Article
Tickle, R., Triguero, I., Figueredo, G. P., Mesgarpour, M., & John, R. I. (2019). PAS3-HSID: a Dynamic Bio-Inspired Approach for Real-Time Hot Spot Identification in Data Streams. Cognitive Computation, 11(3), 434–458. https://doi.org/10.1007/s12559-019-09638-y

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Hot spot identification is a very relevant problem in a wide variety of areas such as health care, energy or transportation. A hot spot is defined as a region of high likelihood o... Read More about PAS3-HSID: a Dynamic Bio-Inspired Approach for Real-Time Hot Spot Identification in Data Streams.