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217 results on '"Obolski, Uri"'

1. Distinguishing immunological and behavioral effects of vaccination

Author

Stensrud, Mats, Nevo, Daniel, and Obolski, Uri

Subjects
Statistics - Applications, Statistics - Methodology
Abstract

The interpretation of vaccine efficacy estimands is subtle, even in randomized trials designed to quantify immunological effects of vaccination. In this article, we introduce terminology to distinguish between different vaccine efficacy estimands and clarify their interpretations. This allows us to explicitly consider immunological and behavioural effects of vaccination, and establish that policy-relevant estimands can differ substantially from those commonly reported in vaccine trials. We further show that a conventional vaccine trial allows identification and estimation of different vaccine estimands under plausible conditions, if one additional post-treatment variable is measured. Specifically, we utilize a ``belief variable'' that indicates the treatment an individual believed they had received. The belief variable is similar to ``blinding assessment'' variables that are occasionally collected in placebo-controlled trials in other fields. We illustrate the relations between the different estimands, and their practical relevance, in numerical examples based on an influenza vaccine trial.

Published
2023

4. Inherent Inconsistencies of Feature Importance

Author

Harel, Nimrod, Obolski, Uri, and Gilad-Bachrach, Ran

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

The rapid advancement and widespread adoption of machine learning-driven technologies have underscored the practical and ethical need for creating interpretable artificial intelligence systems. Feature importance, a method that assigns scores to the contribution of individual features on prediction outcomes, seeks to bridge this gap as a tool for enhancing human comprehension of these systems. Feature importance serves as an explanation of predictions in diverse contexts, whether by providing a global interpretation of a phenomenon across the entire dataset or by offering a localized explanation for the outcome of a specific data point. Furthermore, feature importance is being used both for explaining models and for identifying plausible causal relations in the data, independently from the model. However, it is worth noting that these various contexts have traditionally been explored in isolation, with limited theoretical foundations. This paper presents an axiomatic framework designed to establish coherent relationships among the different contexts of feature importance scores. Notably, our work unveils a surprising conclusion: when we combine the proposed properties with those previously outlined in the literature, we demonstrate the existence of an inconsistency. This inconsistency highlights that certain essential properties of feature importance scores cannot coexist harmoniously within a single framework.

Published
2022

5. The metabolic, virulence and antimicrobial resistance profiles of colonising Streptococcus pneumoniae shift after PCV13 introduction in urban Malawi

Author

Obolski, Uri, Swarthout, Todd D., Kalizang’oma, Akuzike, Mwalukomo, Thandie S., Chan, Jia Mun, Weight, Caroline M., Brown, Comfort, Cave, Rory, Cornick, Jen, Kamng’ona, Arox Wadson, Msefula, Jacquline, Ercoli, Giuseppe, Brown, Jeremy S., Lourenço, José, Maiden, Martin C., French, Neil, Gupta, Sunetra, and Heyderman, Robert S.

Published
2023
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10. DOPE: D-Optimal Pooling Experimental design with application for SARS-CoV-2 screening

Author

Daon, Yair, Huppert, Amit, and Obolski, Uri

Subjects
Statistics - Applications, Quantitative Biology - Quantitative Methods, Statistics - Computation, 62K05, 92C60 (Primary) 62C10 (Secondary)
Abstract

Testing individuals for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen causing the coronavirus disease 2019 (COVID-19), is crucial for curtailing transmission chains. Moreover, rapidly testing many potentially infected individuals is often a limiting factor in controlling COVID-19 outbreaks. Hence, pooling strategies, wherein individuals are grouped and tested simultaneously, are employed. We present a novel pooling strategy that implements D-Optimal Pooling Experimental design (DOPE). DOPE defines optimal pooled tests as those maximizing the mutual information between data and infection states. We estimate said mutual information via Monte-Carlo sampling and employ a discrete optimization heuristic for maximizing it. DOPE outperforms common pooling strategies both in terms of lower error rates and fewer tests utilized. DOPE holds several additional advantages: it provides posterior distributions of the probability of infection, rather than only binary classification outcomes; it naturally incorporates prior information of infection probabilities and test error rates; and finally, it can be easily extended to include other, newly discovered information regarding COVID-19. Hence, we believe that implementation of Bayesian D-optimal experimental design holds a great promise for the efforts of combating COVID-19 and other future pandemics., Comment: 18 pages, 3 figures

Published
2021

13. West Nile virus transmission potential in Portugal

Author

Lourenço, José, Barros, Sílvia C., Zé-Zé, Líbia, Damineli, Daniel S. C., Giovanetti, Marta, Osório, Hugo C., Amaro, Fátima, Henriques, Ana M., Ramos, Fernanda, Luís, Tiago, Duarte, Margarida D., Fagulha, Teresa, Alves, Maria J., and Obolski, Uri

Published
2022
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33. Fatal COVID-19 outcomes are associated with an antibody response targeting epitopes shared with endemic coronaviruses

Author

McNaughton, Anna L., primary, Paton, Robert S., additional, Edmans, Matthew, additional, Youngs, Jonathan, additional, Wellens, Judith, additional, Phalora, Prabhjeet, additional, Fyfe, Alex, additional, Belij-Rammerstorfer, Sandra, additional, Bolton, Jai S., additional, Ball, Jonathan, additional, Carnell, George W., additional, Dejnirattisai, Wanwisa, additional, Dold, Christina, additional, Eyre, David W., additional, Hopkins, Philip, additional, Howarth, Alison, additional, Kooblall, Kreepa, additional, Klim, Hannah, additional, Leaver, Susannah, additional, Lee, Lian Ni, additional, López-Camacho, César, additional, Lumley, Sheila F., additional, Macallan, Derek C., additional, Mentzer, Alexander J., additional, Provine, Nicholas M., additional, Ratcliff, Jeremy, additional, Slon-Compos, Jose, additional, Skelly, Donal, additional, Stolle, Lucas, additional, Supasa, Piyada, additional, Temperton, Nigel, additional, Walker, Chris, additional, Wang, Beibei, additional, Wyncoll, Duncan, additional, Simmonds, Peter, additional, Lambe, Teresa, additional, Baillie, John Kenneth, additional, Semple, Malcolm G., additional, Openshaw, Peter J.M., additional, Obolski, Uri, additional, Turner, Marc, additional, Carroll, Miles, additional, Mongkolsapaya, Juthathip, additional, Screaton, Gavin, additional, Kennedy, Stephen H., additional, Jarvis, Lisa, additional, Barnes, Eleanor, additional, Dunachie, Susanna, additional, Lourenço, José, additional, Matthews, Philippa C., additional, Bicanic, Tihana, additional, Klenerman, Paul, additional, Gupta, Sunetra, additional, and Thompson, Craig P., additional

Published
2022
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35. 1163: BOTH VEDOLIZUMAB AND ANTI-TNF THERAPY ARE ASSOCIATED WITH ATTENUATION OF SEROLOGICAL AND NEUTRALIZING RESPONSES TO SARS-COV-2 INFECTION IN INFLAMMATORY BOWEL DISEASE

Author

Wellens, Judith, primary, Edmans, Matthew, additional, Obolski, Uri, additional, Marlow, Luke, additional, Brann, Stephanie, additional, Dunachie, Susanna, additional, Eyre, David W., additional, Helmus, Drew, additional, Barnes, Eleanor, additional, Colombel, Jean Frederic, additional, Wong, Serre-Yu, additional, Klenerman, Paul, additional, Lindsay, James O., additional, Thompson, Craig, additional, and Satsangi, Jack J., additional

Published
2022
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38. Polymorphisms predicting phylogeny in hepatitis B virus.

Author

Lourenço, José, McNaughton, Anna L, Pley, Caitlin, Obolski, Uri, Gupta, Sunetra, and Matthews, Philippa C

Subjects
HEPATITIS B virus, RANDOM forest algorithms, PHYLOGENY, HEPATITIS viruses, REVERSE transcriptase
Abstract

Hepatitis B viruses (HBVs) are compact viruses with circular genomes of ∼3.2 kb in length. Four genes (HBx, Core, Surface, and Polymerase) generating seven products are encoded on overlapping reading frames. Ten HBV genotypes have been characterised (A–J), which may account for differences in transmission, outcomes of infection, and treatment response. However, HBV genotyping is rarely undertaken, and sequencing remains inaccessible in many settings. We set out to assess which amino acid (aa) sites in the HBV genome are most informative for determining genotype, using a machine learning approach based on random forest algorithms (RFA). We downloaded 5,496 genome-length HBV sequences from a public database, excluding recombinant sequences, regions with conserved indels, and genotypes I and J. Each gene was separately translated into aa, and the proteins concatenated into a single sequence (length 1,614 aa). Using RFA, we searched for aa sites predictive of genotype and assessed covariation among the sites with a mutual information–based method. We were able to discriminate confidently between genotypes A–H using ten aa sites. Half of these sites (5/10) sites were identified in Polymerase (Pol), of which 4/5 were in the spacer domain and one in reverse transcriptase. A further 4/10 sites were located in Surface protein and a single site in HBx. There were no informative sites in Core. Properties of the aa were generally not conserved between genotypes at informative sites. Among the highest co-varying pairs of sites, there were fifty-five pairs that included one of these 'top ten' sites. Overall, we have shown that RFA analysis is a powerful tool for identifying aa sites that predict the HBV lineage, with an unexpectedly high number of such sites in the spacer domain, which has conventionally been viewed as unimportant for structure or function. Our results improve ease of genotype prediction from limited regions of HBV sequences and may have future applications in understanding HBV evolution. [ABSTRACT FROM AUTHOR]

Published
2023
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43. Supplementary text and figures from Interventions targeting non-symptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case study

Author

Lovell-Read, Francesca A., Funk, Sebastian, Obolski, Uri, Donnelly, Christl A., and Thompson, Robin N.

Subjects
human activities
Abstract

Contains further information on calculating the probability of a local outbreak and computation of the steepest descent contours, and the results of the sensitivity analyses conducted

Published
2021
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46. Modeling the growth and sporulation dynamics of the macroalga Ulva in mixed-age populations in cultivation and the formation of green tides.

Author

Obolski, Uri, Wichard, Thomas, Israel, Alvaro, Golberg, Alexander, and Liberzon, Alexander

Subjects
ULVA, AGE distribution, DIFFERENTIAL equations, INDUSTRIAL research, BIOMASS
Abstract

Ulva is a widespread green algal genus with important ecological roles and promising potential as a seagriculture crop. One of the major challenges when cultivating Ulva is sudden biomass disappearance, likely caused by uncontrolled and unpredicted massive sporulation. However, the dynamics of this process are still poorly understood. In this study, we propose a mathematical model describing the biomass accumulation and degradation of Ulva, considering the potential impact of sporulation inhibitors. We developed a differential equation model describing the time evolution of Ulva biomass. Our model simulates biomass in compartments of different Ulva "age" classes, with varying growth and sporulation rates. Coupled with these classes is a differential equation describing the presence of a sporulation inhibitor, produced and secreted by the algae. Our model mimics observed Ulva dynamics. We present Ulva's biomass accumulation under different initial algae population, age distributions and sporulation rates. Furthermore, we simulate water replacement, effectively depleting the sporulation inhibitor, and examine its effects on Ulva's biomass accumulation. The model developed in this work is the first step towards understanding the dynamics of Ulva growth and degradation. Future work refining and expanding our results should prove beneficial to the ecological research and industrial growth of Ulva. [ABSTRACT FROM AUTHOR]

Published
2022
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