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191 results on '"Wild, P.-J."'

1. Somatic CAG repeat expansion in blood associates with biomarkers of neurodegeneration in Huntington’s disease decades before clinical motor diagnosis

Author

Scahill, Rachael I., Farag, Mena, Murphy, Michael J., Hobbs, Nicola Z., Leocadi, Michela, Langley, Christelle, Knights, Harry, Ciosi, Marc, Fayer, Kate, Nakajima, Mitsuko, Thackeray, Olivia, Gobom, Johan, Rönnholm, John, Weiner, Sophia, Hassan, Yara R., Ponraj, Nehaa K. P., Estevez-Fraga, Carlos, Parker, Christopher S., Malone, Ian B., Hyare, Harpreet, Long, Jeffrey D., Heslegrave, Amanda, Sampaio, Cristina, Zhang, Hui, Robbins, Trevor W., Zetterberg, Henrik, Wild, Edward J., Rees, Geraint, Rowe, James B., Sahakian, Barbara J., Monckton, Darren G., Langbehn, Douglas R., and Tabrizi, Sarah J.

Published
2025
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10. A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer’s disease

Author

Boeddrich, Annett, Haenig, Christian, Neuendorf, Nancy, Blanc, Eric, Ivanov, Andranik, Kirchner, Marieluise, Schleumann, Philipp, Bayraktaroğlu, Irem, Richter, Matthias, Molenda, Christine Mirjam, Sporbert, Anje, Zenkner, Martina, Schnoegl, Sigrid, Suenkel, Christin, Schneider, Luisa-Sophie, Rybak-Wolf, Agnieszka, Kochnowsky, Bianca, Byrne, Lauren M., Wild, Edward J., Nielsen, Jørgen E., Dittmar, Gunnar, Peters, Oliver, Beule, Dieter, and Wanker, Erich E.

Published
2023
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13. CT-radiomics and clinical risk scores for response and overall survival prognostication in TACE HCC patients

Author

Bernatz, Simon, Elenberger, Oleg, Ackermann, Jörg, Lenga, Lukas, Martin, Simon S., Scholtz, Jan-Erik, Koch, Vitali, Grünewald, Leon D., Herrmann, Yannis, Kinzler, Maximilian N., Stehle, Angelika, Koch, Ina, Zeuzem, Stefan, Bankov, Katrin, Doering, Claudia, Reis, Henning, Flinner, Nadine, Schulze, Falko, Wild, Peter J., Hammerstingl, Renate, Eichler, Katrin, Gruber-Rouh, Tatjana, Vogl, Thomas J., dos Santos, Daniel Pinto, and Mahmoudi, Scherwin

Published
2023
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16. On Traversing the Data Landscape: Introducing APIs to Data-Science Students

Author

Fergusson, Anna and Wild, Chris J.

Abstract

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data science being fun to teach and fun to learn. We advocate curiosity-driven, exploratory learning for pursuing these goals. Our illustrations use tasks embedded in contexts that teenagers can relate to, provide visual rewards for computational actions, use rich data-contexts, and integrate statistical and computational thinking. They provide engaging introductions to modern data sourced from databases via Application Programming Interfaces (APIs) that are accessible to a broad range of students and facilitate student personalization for investigation. We provide in-depth discussion of teaching strategies that heavily involve questioning and student tinkering supported by graphical-user interfaces that enable students to interact with the data sources rapidly in multiple ways.

Published
2021
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17. Computational Skills by Stealth in Introductory Data Science Teaching

Author

Burr, Wesley, Chevalier, Fanny, Collins, Christopher, Gibbs, Alison L, Ng, Raymond, and Wild, Chris J

Abstract

In 2010, Nolan and Temple Lang proposed "integration of computing concepts into statistics curricula at all levels." The unprecedented growth in data and emphasis on data science has provided an impetus to finally realizing full implementations of this in new statistics and data science programs and courses. We discuss a proposal for the stealth development of computational skills in students' exposure to introductory data science through careful, scaffolded exposure to computation and its power. Our intent is to support students, regardless of interest and self-efficacy in coding, in becoming data-driven learners, who are capable of asking complex questions about the world around them, and then answering those questions through the use of data-driven inquiry. Reference is made to the computer science and statistics consensus curriculum frameworks the International Data Science in Schools Project (IDSSP) recently published for secondary school data science or introductory tertiary programs, designed to optimize data-science accessibility.

Published
2021
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24. Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features

Author

Bernatz, Simon, Ackermann, Jörg, Mandel, Philipp, Kaltenbach, Benjamin, Zhdanovich, Yauheniya, Harter, Patrick N., Döring, Claudia, Hammerstingl, Renate, Bodelle, Boris, Smith, Kevin, Bucher, Andreas, Albrecht, Moritz, Rosbach, Nicolas, Basten, Lajos, Yel, Ibrahim, Wenzel, Mike, Bankov, Katrin, Koch, Ina, Chun, Felix K.-H., Köllermann, Jens, Wild, Peter J., and Vogl, Thomas J.

Published
2020
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25. Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series

Author

Koriath, C., Kenny, J., Adamson, G., Druyeh, R., Taylor, W., Beck, J., Quinn, L., Mok, T. H., Dimitriadis, A., Norsworthy, P., Bass, N., Carter, J., Walker, Z., Kipps, C., Coulthard, E., Polke, J. M., Bernal-Quiros, M., Denning, N., Thomas, R., Raybould, R., Williams, J., Mummery, C. J., Wild, E. J., Houlden, H., Tabrizi, S. J., Rossor, M. N., Hummerich, H., Warren, J. D., Rowe, J. B., Rohrer, J. D., Schott, J. M., Fox, N. C., Collinge, J., and Mead, S.

Published
2020
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31. Statistical Literacy as the Earth Moves

Author

Wild, Chris J.

Abstract

"The Times They Are a-Changin'" says the old Bob Dylan song. But it is not just the times that are a-changin'. For statistical literacy, the very earth is moving under our feet (apologies to Carole King). The seismic forces are (i) new forms of communication and discourse and (ii) new forms of data, data display and human interaction with data. These upheavals in the worlds of communication and data are ongoing. If anything, the pace of change is accelerating. And with it, what it means to be statistically literate is also changing. So how can we tell what is important? We will air some enduring themes and guiding principles.

Published
2017

32. What Is Right with the Wrong Answer? How Teacher Language Ideology Impacts Science Teaching

Author

Brown, Bryan A., Lemmi, Catherine, Wild, Andrew J., Zummo, Lynne, and Sedlacek, Quentin

Abstract

As teachers evaluate students' responses, the belief system they use to make sense of students' work becomes critical. This focus group interview study (n=25) of high school science teachers examined teachers' language ideology in science. Teachers were asked to evaluate the accuracy of students work by watching videos of lessons and written samples of students' work. We coded teachers' responses into two prominent categories--"Binary Thinking" and "Spectrum Thinking." When using "Binary Thinking" teachers viewed language and concepts as either completely correct or incorrect. When using "Spectrum Thinking" teachers viewed components of language and concepts as being partially correct. We found that teacher used each approach inconsistently. We discovered that teachers used both models inconsistently and influenced each other.

Published
2017

33. Convergent network effects along the axis of gene expression during prostate cancer progression

Author

Charmpi, Konstantina, Guo, Tiannan, Zhong, Qing, Wagner, Ulrich, Sun, Rui, Toussaint, Nora C., Fritz, Christine E., Yuan, Chunhui, Chen, Hao, Rupp, Niels J., Christiansen, Ailsa, Rutishauser, Dorothea, Rüschoff, Jan H., Fankhauser, Christian, Saba, Karim, Poyet, Cedric, Hermanns, Thomas, Oehl, Kathrin, Moore, Ariane L., Beisel, Christian, Calzone, Laurence, Martignetti, Loredana, Zhang, Qiushi, Zhu, Yi, Martínez, María Rodríguez, Manica, Matteo, Haffner, Michael C., Aebersold, Ruedi, Wild, Peter J., and Beyer, Andreas

Published
2020
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34. Inferring clonal composition from multiple tumor biopsies

Author

Manica, Matteo, Kim, Hyunjae Ryan, Mathis, Roland, Chouvarine, Philippe, Rutishauser, Dorothea, De Vargas Roditi, Laura, Szalai, Bence, Wagner, Ulrich, Oehl, Kathrin, Saba, Karim, Pati, Arati, Saez-Rodriguez, Julio, Roy, Angshumoy, Parsons, Donald W., Wild, Peter J., Martínez, María Rodríguez, and Sumazin, Pavel

Published
2020
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35. Strategies to enable large-scale proteomics for reproducible research

Author

Poulos, Rebecca C., Hains, Peter G., Shah, Rohan, Lucas, Natasha, Xavier, Dylan, Manda, Srikanth S., Anees, Asim, Koh, Jennifer M. S., Mahboob, Sadia, Wittman, Max, Williams, Steven G., Sykes, Erin K., Hecker, Michael, Dausmann, Michael, Wouters, Merridee A., Ashman, Keith, Yang, Jean, Wild, Peter J., deFazio, Anna, Balleine, Rosemary L., Tully, Brett, Aebersold, Ruedi, Speed, Terence P., Liu, Yansheng, Reddel, Roger R., Robinson, Phillip J., and Zhong, Qing

Published
2020
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36. What I See Is Not Quite the Way It Really Is: Students' Emergent Reasoning about Sampling Variability

Author

Pfannkuch, Maxine, Arnold, Pip, and Wild, Chris J.

Abstract

Currently, instruction pays little attention to the development of students' sampling variability reasoning in relation to statistical inference. In this paper, we briefly discuss the especially designed sampling variability learning experiences students aged about 15 engaged in as part of a research project. We examine assessment and interview responses from four students to describe their emergent reasoning about sampling variability. Their reasoning is analyzed using our adaptations of a statistical inference framework and a mental processes framework. Our findings suggest that these students are beginning to develop understanding of sampling variability concepts from probabilistic and generalization perspectives and to articulate the evidence used from the data. We conjecture that these students' understanding of sampling variability is aided by the development in instruction of the three mental processes of visualization, analysis, and verbal description.

Published
2015
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37. Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins

Author

Shao, Wenguang, Guo, Tiannan, Toussaint, Nora C., Xue, Peng, Wagner, Ulrich, Li, Li, Charmpi, Konstantina, Zhu, Yi, Wu, Jianmin, Buljan, Marija, Sun, Rui, Rutishauser, Dorothea, Hermanns, Thomas, Fankhauser, Christian Daniel, Poyet, Cedric, Ljubicic, Jelena, Rupp, Niels, Rüschoff, Jan H., Zhong, Qing, Beyer, Andreas, Ji, Jiafu, Collins, Ben C., Liu, Yansheng, Rätsch, Gunnar, Wild, Peter J., and Aebersold, Ruedi

Published
2019
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39. Sources of Formaldehyde in U.S. Oil and Gas Production Regions.

Author

Dix, Barbara, Li, Meng, Roosenbrand, Esther, Francoeur, Colby, Brown, Steven S., Gilman, Jessica B., Hanisco, Thomas F., Keutsch, Frank, Koss, Abigail, Lerner, Brian M., Peischl, Jeff, Roberts, James M., Ryerson, Thomas B., St. Clair, Jason M., Veres, Patrick R., Warneke, Carsten, Wild, Robert J., Wolfe, Glenn M., Yuan, Bin, and Veefkind, J. Pepijn

Published
2023
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46. Enhancing Students' Inferential Reasoning: From Hands-On to 'Movies'

Author

Arnold, Pip, Pfannkuch, Maxine, Wild, Chris J., Regan, Matt, and Budgett, Stephanie

Abstract

Computer simulations and animations for developing statistical concepts are often not understood by beginners. Hands-on physical simulations that morph into computer simulations are teaching approaches that can build students' concepts. In this paper we review the literature on visual and verbal cognitive processing and on the efficacy of animations in promoting learning. We describe an instructional sequence, from hands-on to animations, developed for 14 year-old students. The instruction focused on developing students' understanding of sampling variability and using samples to make inferences about populations. The learning trajectory from hands-on to animations is analyzed from the perspective of multimedia learning theories while the learning outcomes of about 100 students are explored, including images and reasoning processes used when comparing two box plots. The findings suggest that carefully designed learning trajectories can stimulate students to gain access to inferential concepts and reasoning processes. The role of verbal, visual, and sensory cues in developing students' reasoning is discussed and important questions for further research on these elements are identified. (Contains 12 figures and 1 table.)

Published
2011

49. A new volcanic multi-hazard impact model for water supply systems: Application at Taranaki Mounga, Aotearoa New Zealand.

Author

Porter, Harley, Wilson, Thomas M., Weir, Alana, Stewart, Carol, Craig, Heather M., Wild, Alec J., Paulik, Ryan, Fairclough, Roger, and Buzzella, Maria

Abstract

Water supply systems provide an essential service for society and are highly vulnerable to damage and disruption during volcanic eruptions. Impacts sustained by water supply systems during volcanic eruptions have resulted in prolonged and repeated supply outages. Previous approaches to assessing volcanic impacts to water supply systems have been relatively simplistic, based on hazard intensity thresholds, and only considering direct damage. There is a need for water supply risk assessment approaches informed by vulnerability models that consider the pivotal role of system design and indirect impacts; such as supply and demand fluctuations, personnel shortages, and disruptions to interdependent infrastructure networks. We present a whole-of-system volcanic vulnerability model and impact assessment framework for water supply systems that can be used to estimate system-wide impacts during future volcanic eruptions. This model is developed in collaboration with volcanic risk researchers and water supply engineers in Aotearoa New Zealand and applied to a case study in the Taranaki region for a long-duration and multi-hazard eruption scenario from the active stratovolcano Taranaki Mounga. The model provides an assessment of the functionality of water supply systems affected directly and indirectly by the scenario eruption, interdependent critical infrastructure services, and associated emergency management actions (e.g., evacuations). This scenario, and its modelled impacts, allows practitioners to explore potential mitigation and emergency response options. This framework can be applied in other volcanic contexts to assess impacts on water supplies from future eruptions, highlight key systemic vulnerabilities, and provide a basis for the prioritisation and implementation of risk management strategies. • Water supply systems are vulnerable to damage and outages due to volcanic hazards. • We propose a whole-of-system volcanic vulnerability model for water supply systems. • This framework can be applied in other volcanic contexts to assess impacts. • It can also highlight systemic vulnerabilities to help prioritise risk management. [ABSTRACT FROM AUTHOR]

Published
2025
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