المؤلفون: Darabi, Sourat, Adeyelu, Tolulope, Elliott, Andrew, Sukari, Ammar, Hodges, Kurt, Abdulla, Farah, Zuazo, Carlos E, Wise-Draper, Trisha, Wang, Thomas, Demeure, Michael J

المصدر: Journal of the American College of Surgeons ; volume 239, issue 1, page 50-60 ; ISSN 1072-7515

الوصف: BACKGROUND: About 75% of medullary thyroid cancers (MTCs) are sporadic with 45% to 70% being driven by a RET mutation. Selpercatinib is an approved treatment for RET-mutated (mut RET ) MTC; however, treatments are needed for wild-type RET MTC (wt RET ). Genomic alterations and transcriptomic signatures of wt RET MTC may reveal new therapeutic insights. STUDY DESIGN: We did a retrospective analysis of MTC samples submitted for DNA/RNA sequencing and programmed cell death ligand 1 expression using immunohistochemistry at a Clinical Laboratory Improvement Amendments/College of American Pathologists-certified laboratory. Tumor microenvironment immune cell fractions were estimated using RNA deconvolution (quanTIseq). Transcriptomic signatures of inflammation and MAP kinase pathway activation scores were calculated. Mann-Whitney U, chi-square, and Fisher’s exact tests were applied (p values adjusted for multiple comparisons). RESULTS: The 160-patient cohort included 108 mut RET and 52 wt RET MTC samples. wt RET tumors frequently harbored mitogen-activated protein kinase (MAPK) pathway mutations, including HRAS (42.31%), KRAS (15.7%), NF1 (6.7%), and BRAF (2%), whereas only 1 MAPK pathway mutation ( NF1 ) was identified among mut RET MTC. Recurrent mutations seen in wt RET MTC included MGA , VHL, APC , STK11 , and NFE2L2 . Increased transcriptional activation of the MAPK pathway was observed in patients with wt RET harboring mutations in MAPK genes. Although the frequency of programmed cell death ligand 1 expression was similar in wt RET and mut RET (10.2% vs 7%, p = 0.531), wt RET tumors were more often tumor mutational burden high (7.7% vs 0%, p = 0.011), and wt RET MTC exhibited higher expression of immune checkpoint genes. CONCLUSIONS: We identified molecular alterations and immune-related features that distinguish wt RET from mut RET MTC. Although RET mutation drives MTC in the absence of other alterations, we showed that wt RET MTC frequently harbors MAPK pathway mutations. These findings may indicate a potential ...

الإتاحة: https://doi.org/10.1097/xcs.0000000000001098Test

المؤلفون: Underwood, William George, Elliott, Andrew, Cucuringu, Mihai

المصدر: Applied Network Science 5, 62 (2020)

مصطلحات موضوعية: Computer Science - Social and Information Networks, Computer Science - Machine Learning, Physics - Physics and Society, Statistics - Machine Learning

الوصف: Clustering is an essential technique for network analysis, with applications in a diverse range of fields. Although spectral clustering is a popular and effective method, it fails to consider higher-order structure and can perform poorly on directed networks. One approach is to capture and cluster higher-order structures using motif adjacency matrices. However, current formulations fail to take edge weights into account, and thus are somewhat limited when weight is a key component of the network under study. We address these shortcomings by exploring motif-based weighted spectral clustering methods. We present new and computationally useful matrix formulae for motif adjacency matrices on weighted networks, which can be used to construct efficient algorithms for any anchored or non-anchored motif on three nodes. In a very sparse regime, our proposed method can handle graphs with a million nodes and tens of millions of edges. We further use our framework to construct a motif-based approach for clustering bipartite networks. We provide comprehensive experimental results, demonstrating (i) the scalability of our approach, (ii) advantages of higher-order clustering on synthetic examples, and (iii) the effectiveness of our techniques on a variety of real world data sets; and compare against several techniques from the literature. We conclude that motif-based spectral clustering is a valuable tool for analysis of directed and bipartite weighted networks, which is also scalable and easy to implement.
Comment: 38 pages, 20 figures

الوصول الحر: http://arxiv.org/abs/2004.01293Test

المؤلفون: Elliott, Andrew, Saul, Michelle, Zeng, Jia, Marshall, John, Kim, Edward, Nagasaka, Misako, Lenz, Heinz-Josef, Schwartzberg, Lee, Spetzler, David, Abraham, Jim, Xiu, Joanne, Stafford, Phillip, Michael Korn, W

المصدر: Scientific Reports. 11(1)

مصطلحات موضوعية: Aged, Angiotensin-Converting Enzyme 2, COVID-19, Case-Control Studies, Female, Humans, Male, Middle Aged, Neoplasms, RNA, Serine Endopeptidases, Tumor Microenvironment, Exome Sequencing

الوصف: Patients with cancer demonstrate particularly poor outcomes from COVID-19. To provide information essential for understanding the biologic underpinnings of this association, we analyzed whole-transcriptome RNA expression data obtained from a large cohort of cancer patients to characterize expression of ACE2, TMPRSS2, and other proteases that are involved in viral attachment to and entry into target cells. We find substantial variability of expression of these factors across tumor types and identify subpopulations expressing ACE2 at very high levels. In some tumor types, especially in gastrointestinal cancers, expression of ACE2 and TMPRSS2 is highly correlated. Furthermore, we found infiltration with T-cell and natural killer (NK) cell infiltration to be particularly pronounced in ACE2-high tumors. These findings suggest that subsets of cancer patients exist with gene expression profiles that may be associated with heightened susceptibility to SARS-CoV-2 infection, in whom malignant tumors function as viral reservoir and possibly promote the frequently detrimental hyper-immune response in patients infected with this virus.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/00k6062xTest

المؤلفون: Elliott, Andrew, Law, Stephen, Russell, Chris

مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning

الوصف: We present a simple regularization of adversarial perturbations based upon the perceptual loss. While the resulting perturbations remain imperceptible to the human eye, they differ from existing adversarial perturbations in that they are semi-sparse alterations that highlight objects and regions of interest while leaving the background unaltered. As a semantically meaningful adverse perturbations, it forms a bridge between counterfactual explanations and adversarial perturbations in the space of images. We evaluate our approach on several standard explainability benchmarks, namely, weak localization, insertion deletion, and the pointing game demonstrating that perceptually regularized counterfactuals are an effective explanation for image-based classifiers.
Comment: CVPR 2021

الوصول الحر: http://arxiv.org/abs/1912.09405Test

المؤلفون: Elliott, Andrew, Chiu, Angus, Bazzi, Marya, Reinert, Gesine, Cucuringu, Mihai

مصطلحات موضوعية: Computer Science - Social and Information Networks, Statistics - Applications, 05C82

الوصف: While studies of meso-scale structures in networks often focus on community structure, core--periphery structures can reveal new insights. This structure typically consists of a well-connected core and a periphery that is well connected to the core but sparsely connected internally. Most studies of core--periphery structure focus on undirected networks. We propose a generalisation of core-periphery structure to directed networks. Our approach yields a family of core-periphery block model formulations in which core and periphery sets are edge-direction dependent. We mainly focus on a particular core--periphery structure consisting of two core sets and two periphery sets which we motivate empirically. To detect this directed core-periphery structure we propose four different methods, with different trade-offs between computational complexity and accuracy. We assess these methods on three benchmarks and compare to four standard methods. On simulated data, the proposed methods match or outperform the standard methods. Applying our methods to three empirical networks -- a political blogs networks, a faculty hiring network, and a trade network -- illustrates that this directed core--periphery structure can offer novel insights about the underlying dataset.

الوصول الحر: http://arxiv.org/abs/1912.00984Test

المؤلفون: Elliott, Andrew, Cucuringu, Mihai, Luaces, Milton Martinez, Reidy, Paul, Reinert, Gesine

مصطلحات موضوعية: Statistics - Applications, Computer Science - Social and Information Networks, Physics - Physics and Society, 05C82

الوصف: This paper is motivated by the task of detecting anomalies in networks of financial transactions, with accounts as nodes and a directed weighted edge between two nodes denoting a money transfer. The weight of the edge is the transaction amount. Examples of anomalies in networks include long paths of large transaction amounts, rings of large payments, and cliques of accounts. There are many methods available which detect such specific structures in networks. Here we introduce a method which is able to detect previously unspecified anomalies in networks. The method is based on a combination of features from network comparison and spectral analysis as well as local statistics, yielding 140 main features. We then use a simple feature sum method, as well as a random forest method, in order to classify nodes as normal or anomalous. We test the method first on synthetic networks which we generated, and second on a set of synthetic networks which were generated without the methods team having access to the ground truth. The first set of synthetic networks was split in a training set of 70 percent of the networks, and a test set of 30 percent of the networks. The resulting classifier was then applied to the second set of synthetic networks. We compare our method with Oddball, a widely used method for anomaly detection in networks, as well as to random classification. While Oddball outperforms random classification, both our feature sum method and our random forest method outperform Oddball. On the test set, the random forest outperforms feature sum, whereas on the second synthetic data set, initially feature sum tends to pick up more anomalies than random forest, with this behaviour reversing for lower-scoring anomalies. In all cases, the top 2 percent of flagged anomalies contained on average over 90 percent of the planted anomalies.

الوصول الحر: http://arxiv.org/abs/1901.00402Test

المؤلفون: Souroullas, George P, Adeyelu, Tolulope, Elliott, Andrew, Park, Soo, Kim, Kevin, VanderWalde, Ari, Ansstas, George

المصدر: Regular and Young Investigator Award Abstracts

الإتاحة: https://doi.org/10.1136/jitc-2023-sitc2023.0180Test

المؤلفون: Campbell, Dalton, Griffin, Kelly Anne, Elliott, Andrew

المصدر: Journal of Historical Research in Marketing, 2022, Vol. 14, Issue 2, pp. 135-154.

الوصول الحر: http://www.emeraldinsight.com/doi/10.1108/JHRM-09-2021-0050Test

المؤلفون: Law, Stephen, Hasegawa, Rikuo, Paige, Brooks, Russell, Chris, Elliott, Andrew

الوصف: We propose a new form of plausible counterfactual explanation designed to explain the behaviour of computer vision systems used in urban analytics that make predictions based on properties across the entire image, rather than specific regions of it. We illustrate the merits of our approach by explaining computer vision models used to analyse street imagery, which are now widely used in GeoAI and urban analytics. Such explanations are important in urban analytics as researchers and practioners are increasingly reliant on it for decision making. Finally, we perform a user study that demonstrate our approach can be used by non-expert users, who might not be machine learning experts, to be more confident and to better understand the behaviour of image-based classifiers/regressors for street view analysis. Furthermore, the method can potentially be used as an engagement tool to visualise how public spaces can plausibly look like. The limited realism of the counterfactuals is a concern which we hope to improve in the future.

وصف الملف: text

العلاقة: https://eprints.gla.ac.uk/299852/1/299852.pdfTest; Law, S., Hasegawa, R., Paige, B., Russell, C. and Elliott, A. (2023) Explaining holistic image regressors and classifiers in urban analytics with plausible counterfactuals. International Journal of Geographical Information Science , 37, pp. 2575-2596. (doi:10.1080/13658816.2023.2214592 )

الإتاحة: https://doi.org/10.1080/13658816.2023.2214592Test
https://eprints.gla.ac.uk/299852Test/
https://eprints.gla.ac.uk/299852/1/299852.pdfTest

المؤلفون: Harper, Alison, Monks, Thomas, Wilson, Rebecca, Redaniel, Maria Theresa, Eyles, Emily, Jones, Tim, Penfold, Chris, Elliott, Andrew, Keen, Tim, Pitt, Martin, Blom, Ashley, Whitehouse, Michael R, Judge, Andrew

المصدر: Harper , A , Monks , T , Wilson , R , Redaniel , M T , Eyles , E , Jones , T , Penfold , C , Elliott , A , Keen , T , Pitt , M , Blom , A , Whitehouse , M R & Judge , A 2023 , ' Development and application of simulation modelling for orthopaedic elective resource planning in England ' , BMJ Open , vol. 13 , no. 12 , e076298 . https://doi.org/10.1136/bmjopen-2023-076221Test

العلاقة: https://research-information.bris.ac.uk/en/publications/48a99fe5-3c55-46af-b07b-f2f8a382b4f4Test

الإتاحة: https://doi.org/10.1136/bmjopen-2023-076221Test
https://hdl.handle.net/1983/48a99fe5-3c55-46af-b07b-f2f8a382b4f4Test
https://research-information.bris.ac.uk/en/publications/48a99fe5-3c55-46af-b07b-f2f8a382b4f4Test