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1. Personalizing Driver Safety Interfaces via Driver Cognitive Factors Inference

Author

Sumner, Emily S, DeCastro, Jonathan, Costa, Jean, Gopinath, Deepak E, Kimani, Everlyne, Hakimi, Shabnam, Morgan, Allison, Best, Andrew, Nguyen, Hieu, Brooks, Daniel J, Haq, Bassam ul, Patrikalakis, Andrew, Yasuda, Hiroshi, Sieck, Kate, Balachandran, Avinash, Chen, Tiffany, and Rosman, Guy

Subjects
Computer Science - Human-Computer Interaction
Abstract

Recent advances in AI and intelligent vehicle technology hold promise to revolutionize mobility and transportation, in the form of advanced driving assistance (ADAS) interfaces. Although it is widely recognized that certain cognitive factors, such as impulsivity and inhibitory control, are related to risky driving behavior, play a significant role in on-road risk-taking, existing systems fail to leverage such factors. Varying levels of these cognitive factors could influence the effectiveness and acceptance of driver safety interfaces. We demonstrate an approach for personalizing driver interaction via driver safety interfaces that are triggered based on a learned recurrent neural network. The network is trained from a population of human drivers to infer impulsivity and inhibitory control from recent driving behavior. Using a high-fidelity vehicle motion simulator, we demonstrate the ability to deduce these factors from driver behavior. We then use these inferred factors to make instantaneous determinations on whether or not to engage a driver safety interface. This interface aims to decrease a driver's speed during yellow lights and reduce their inclination to run through them., Comment: 12 pages, 7 figures

Published
2024

4. The children's brain tumor network (CBTN) - Accelerating research in pediatric central nervous system tumors through collaboration and open science

Author

Lilly, Jena V, Rokita, Jo Lynne, Mason, Jennifer L, Patton, Tatiana, Stefankiewiz, Stephanie, Higgins, David, Trooskin, Gerri, Larouci, Carina A, Arya, Kamnaa, Appert, Elizabeth, Heath, Allison P, Zhu, Yuankun, Brown, Miguel A, Zhang, Bo, Farrow, Bailey K, Robins, Shannon, Morgan, Allison M, Nguyen, Thinh Q, Frenkel, Elizabeth, Lehmann, Kaitlin, Drake, Emily, Sullivan, Catherine, Plisiewicz, Alexa, Coleman, Noel, Patterson, Luke, Koptyra, Mateusz, Helili, Zeinab, Van Kuren, Nicholas, Young, Nathan, Kim, Meen Chul, Friedman, Christopher, Lubneuski, Alex, Blackden, Christopher, Williams, Marti, Baubet, Valerie, Tauhid, Lamiya, Galanaugh, Jamie, Boucher, Katie, Ijaz, Heba, Cole, Kristina A, Choudhari, Namrata, Santi, Mariarita, Moulder, Robert W, Waller, Jonathan, Rife, Whitney, Diskin, Sharon J, Mateos, Marion, Parsons, Donald W, Pollack, Ian F, Goldman, Stewart, Leary, Sarah, Caporalini, Chiara, Buccoliero, Anna Maria, Scagnet, Mirko, Haussler, David, Hanson, Derek, Firestein, Ron, Cain, Jason, Phillips, Joanna J, Gupta, Nalin, Mueller, Sabine, Grant, Gerald, Monje-Deisseroth, Michelle, Partap, Sonia, Greenfield, Jeffrey P, Hashizume, Rintaro, Smith, Amy, Zhu, Shida, Johnston, James M, Fangusaro, Jason R, Miller, Matthew, Wood, Matthew D, Gardner, Sharon, Carter, Claire L, Prolo, Laura M, Pisapia, Jared, Pehlivan, Katherine, Franson, Andrea, Niazi, Toba, Rubin, Josh, Abdelbaki, Mohamed, Ziegler, David S, Lindsay, Holly B, Stucklin, Ana Guerreiro, Gerber, Nicolas, Vaske, Olena M, Quinsey, Carolyn, Rood, Brian R, Nazarian, Javad, Raabe, Eric, Jackson, Eric M, Stapleton, Stacie, Lober, Robert M, Kram, David E, Koschmann, Carl, Storm, Phillip B, Lulla, Rishi R, Prados, Michael, Resnick, Adam C, and Waanders, Angela J

Subjects
Neurosciences, Pediatric Cancer, Brain Disorders, Pediatric Research Initiative, Pediatric, Brain Cancer, Rare Diseases, Cancer, Good Health and Well Being, Adult, Humans, Child, Quality of Life, Brain Neoplasms, Collaborative international research infrastructure, Pediatric brain tumors, Multi-omic data, Longitudinal clinical data, Biospecimens, Molecular clinical trials, Clinical Sciences, Oncology & Carcinogenesis
Abstract

Pediatric brain tumors are the leading cause of cancer-related death in children in the United States and contribute a disproportionate number of potential years of life lost compared to adult cancers. Moreover, survivors frequently suffer long-term side effects, including secondary cancers. The Children's Brain Tumor Network (CBTN) is a multi-institutional international clinical research consortium created to advance therapeutic development through the collection and rapid distribution of biospecimens and data via open-science research platforms for real-time access and use by the global research community. The CBTN's 32 member institutions utilize a shared regulatory governance architecture at the Children's Hospital of Philadelphia to accelerate and maximize the use of biospecimens and data. As of August 2022, CBTN has enrolled over 4700 subjects, over 1500 parents, and collected over 65,000 biospecimen aliquots for research. Additionally, over 80 preclinical models have been developed from collected tumors. Multi-omic data for over 1000 tumors and germline material are currently available with data generation for > 5000 samples underway. To our knowledge, CBTN provides the largest open-access pediatric brain tumor multi-omic dataset annotated with longitudinal clinical and outcome data, imaging, associated biospecimens, child-parent genomic pedigrees, and in vivo and in vitro preclinical models. Empowered by NIH-supported platforms such as the Kids First Data Resource and the Childhood Cancer Data Initiative, the CBTN continues to expand the resources needed for scientists to accelerate translational impact for improved outcomes and quality of life for children with brain and spinal cord tumors.

Published
2023

5. Socioeconomic roots of academic faculty

Author

Morgan, Allison C, LaBerge, Nicholas, Larremore, Daniel B, Galesic, Mirta, Brand, Jennie E, and Clauset, Aaron

Subjects
Biomedical and Clinical Sciences, Health Sciences, Psychology, Behavioral and Social Science, Quality Education, Humans, Child, Faculty, Fellowships and Scholarships, Universities, Socioeconomic Factors, Biomedical and clinical sciences, Health sciences
Abstract

Despite the special role of tenure-track faculty in society, training future researchers and producing scholarship that drives scientific and technological innovation, the sociodemographic characteristics of the professoriate have never been representative of the general population. Here we systematically investigate the indicators of faculty childhood socioeconomic status and consider how they may limit efforts to diversify the professoriate. Combining national-level data on education, income and university rankings with a 2017-2020 survey of 7,204 US-based tenure-track faculty across eight disciplines in STEM, social science and the humanities, we show that faculty are up to 25 times more likely to have a parent with a Ph.D. Moreover, this rate nearly doubles at prestigious universities and is stable across the past 50 years. Our results suggest that the professoriate is, and has remained, accessible disproportionately to the socioeconomically privileged, which is likely to deeply shape their scholarship and their reproduction.

Published
2022

6. Subfield prestige and gender inequality in computing

Author

LaBerge, Nicholas, Wapman, K. Hunter, Morgan, Allison C., Zhang, Sam, Larremore, Daniel B., and Clauset, Aaron

Subjects
Computer Science - Computers and Society
Abstract

Women and people of color remain dramatically underrepresented among computing faculty, and improvements in demographic diversity are slow and uneven. Effective diversification strategies depend on quantifying the correlates, causes, and trends of diversity in the field. But field-level demographic changes are driven by subfield hiring dynamics because faculty searches are typically at the subfield level. Here, we quantify and forecast variations in the demographic composition of the subfields of computing using a comprehensive database of training and employment records for 6882 tenure-track faculty from 269 PhD-granting computing departments in the United States, linked with 327,969 publications. We find that subfield prestige correlates with gender inequality, such that faculty working in computing subfields with more women tend to hold positions at less prestigious institutions. In contrast, we find no significant evidence of racial or socioeconomic differences by subfield. Tracking representation over time, we find steady progress toward gender equality in all subfields, but more prestigious subfields tend to be roughly 25 years behind the less prestigious subfields in gender representation. These results illustrate how the choice of subfield in a faculty search can shape a department's gender diversity., Comment: 20 pages, 12 figures, 5 tables

Published
2022

11. Measuring the predictability of life outcomes with a scientific mass collaboration

Author

Salganik, Matthew J, Lundberg, Ian, Kindel, Alexander T, Ahearn, Caitlin E, Al-Ghoneim, Khaled, Almaatouq, Abdullah, Altschul, Drew M, Brand, Jennie E, Carnegie, Nicole Bohme, Compton, Ryan James, Datta, Debanjan, Davidson, Thomas, Filippova, Anna, Gilroy, Connor, Goode, Brian J, Jahani, Eaman, Kashyap, Ridhi, Kirchner, Antje, McKay, Stephen, Morgan, Allison C, Pentland, Alex, Polimis, Kivan, Raes, Louis, Rigobon, Daniel E, Roberts, Claudia V, Stanescu, Diana M, Suhara, Yoshihiko, Usmani, Adaner, Wang, Erik H, Adem, Muna, Alhajri, Abdulla, AlShebli, Bedoor, Amin, Redwane, Amos, Ryan B, Argyle, Lisa P, Baer-Bositis, Livia, Büchi, Moritz, Chung, Bo-Ryehn, Eggert, William, Faletto, Gregory, Fan, Zhilin, Freese, Jeremy, Gadgil, Tejomay, Gagné, Josh, Gao, Yue, Halpern-Manners, Andrew, Hashim, Sonia P, Hausen, Sonia, He, Guanhua, Higuera, Kimberly, Hogan, Bernie, Horwitz, Ilana M, Hummel, Lisa M, Jain, Naman, Jin, Kun, Jurgens, David, Kaminski, Patrick, Karapetyan, Areg, Kim, EH, Leizman, Ben, Liu, Naijia, Möser, Malte, Mack, Andrew E, Mahajan, Mayank, Mandell, Noah, Marahrens, Helge, Mercado-Garcia, Diana, Mocz, Viola, Mueller-Gastell, Katariina, Musse, Ahmed, Niu, Qiankun, Nowak, William, Omidvar, Hamidreza, Or, Andrew, Ouyang, Karen, Pinto, Katy M, Porter, Ethan, Porter, Kristin E, Qian, Crystal, Rauf, Tamkinat, Sargsyan, Anahit, Schaffner, Thomas, Schnabel, Landon, Schonfeld, Bryan, Sender, Ben, Tang, Jonathan D, Tsurkov, Emma, van Loon, Austin, Varol, Onur, Wang, Xiafei, Wang, Zhi, Wang, Julia, Wang, Flora, Weissman, Samantha, Whitaker, Kirstie, Wolters, Maria K, Woon, Wei Lee, Wu, James, Wu, Catherine, and Yang, Kengran

Subjects
Pediatric, Behavioral and Social Science, Generic health relevance, Adolescent, Child, Child, Preschool, Cohort Studies, Family, Female, Humans, Infant, Life, Machine Learning, Male, Predictive Value of Tests, Social Sciences, life course, prediction, machine learning, mass collaboration
Abstract

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

Published
2020

12. The children's brain tumor network (CBTN) - Accelerating research in pediatric central nervous system tumors through collaboration and open science

Author

Lilly, Jena V., Rokita, Jo Lynne, Mason, Jennifer L., Patton, Tatiana, Stefankiewiz, Stephanie, Higgins, David, Trooskin, Gerri, Larouci, Carina A., Arya, Kamnaa, Appert, Elizabeth, Heath, Allison P., Zhu, Yuankun, Brown, Miguel A., Zhang, Bo, Farrow, Bailey K., Robins, Shannon, Morgan, Allison M., Nguyen, Thinh Q., Frenkel, Elizabeth, Lehmann, Kaitlin, Drake, Emily, Sullivan, Catherine, Plisiewicz, Alexa, Coleman, Noel, Patterson, Luke, Koptyra, Mateusz, Helili, Zeinab, Van Kuren, Nicholas, Young, Nathan, Kim, Meen Chul, Friedman, Christopher, Lubneuski, Alex, Blackden, Christopher, Williams, Marti, Baubet, Valerie, Tauhid, Lamiya, Galanaugh, Jamie, Boucher, Katie, Ijaz, Heba, Cole, Kristina A., Choudhari, Namrata, Santi, Mariarita, Moulder, Robert W., Waller, Jonathan, Rife, Whitney, Diskin, Sharon J., Mateos, Marion, Parsons, Donald W., Pollack, Ian F., Goldman, Stewart, Leary, Sarah, Caporalini, Chiara, Buccoliero, Anna Maria, Scagnet, Mirko, Haussler, David, Hanson, Derek, Firestein, Ron, Cain, Jason, Phillips, Joanna J., Gupta, Nalin, Mueller, Sabine, Grant, Gerald, Monje-Deisseroth, Michelle, Partap, Sonia, Greenfield, Jeffrey P., Hashizume, Rintaro, Smith, Amy, Zhu, Shida, Johnston, James M., Fangusaro, Jason R., Miller, Matthew, Wood, Matthew D., Gardner, Sharon, Carter, Claire L., Prolo, Laura M., Pisapia, Jared, Pehlivan, Katherine, Franson, Andrea, Niazi, Toba, Rubin, Josh, Abdelbaki, Mohamed, Ziegler, David S., Lindsay, Holly B., Stucklin, Ana Guerreiro, Gerber, Nicolas, Vaske, Olena M., Quinsey, Carolyn, Rood, Brian R., Nazarian, Javad, Raabe, Eric, Jackson, Eric M., Stapleton, Stacie, Lober, Robert M., Kram, David E., Koschmann, Carl, Storm, Phillip B., Lulla, Rishi R., Prados, Michael, Resnick, Adam C., and Waanders, Angela J.

Published
2023
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13. Prestige drives epistemic inequality in the diffusion of scientific ideas

Author

Morgan, Allison C., Economou, Dimitrios J., Way, Samuel F., and Clauset, Aaron

Subjects
Computer Science - Social and Information Networks, Computer Science - Computers and Society, Physics - Physics and Society
Abstract

The spread of ideas in the scientific community is often viewed as a competition, in which good ideas spread further because of greater intrinsic fitness, and publication venue and citation counts correlate with importance and impact. However, relatively little is known about how structural factors influence the spread of ideas, and specifically how where an idea originates might influence how it spreads. Here, we investigate the role of faculty hiring networks, which embody the set of researcher transitions from doctoral to faculty institutions, in shaping the spread of ideas in computer science, and the importance of where in the network an idea originates. We consider comprehensive data on the hiring events of 5032 faculty at all 205 Ph.D.-granting departments of computer science in the U.S. and Canada, and on the timing and titles of 200,476 associated publications. Analyzing five popular research topics, we show empirically that faculty hiring can and does facilitate the spread of ideas in science. Having established such a mechanism, we then analyze its potential consequences using epidemic models to simulate the generic spread of research ideas and quantify the impact of where an idea originates on its longterm diffusion across the network. We find that research from prestigious institutions spreads more quickly and completely than work of similar quality originating from less prestigious institutions. Our analyses establish the theoretical trade-offs between university prestige and the quality of ideas necessary for efficient circulation. Our results establish faculty hiring as an underlying mechanism that drives the persistent epistemic advantage observed for elite institutions, and provide a theoretical lower bound for the impact of structural inequality in shaping the spread of ideas in science., Comment: 10 pages, 8 figures, 1 table

Published
2018
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14. Automatically assembling a full census of an academic field

Author

Morgan, Allison C., Way, Samuel F., and Clauset, Aaron

Subjects
Computer Science - Digital Libraries, Computer Science - Computers and Society, Computer Science - Social and Information Networks, Physics - Physics and Society
Abstract

The composition of the scientific workforce shapes the direction of scientific research, directly through the selection of questions to investigate, and indirectly through its influence on the training of future scientists. In most fields, however, complete census information is difficult to obtain, complicating efforts to study workforce dynamics and the effects of policy. This is particularly true in computer science, which lacks a single, all-encompassing directory or professional organization. A full census of computer science would serve many purposes, not the least of which is a better understanding of the trends and causes of unequal representation in computing. Previous academic census efforts have relied on narrow or biased samples, or on professional society membership rolls. A full census can be constructed directly from online departmental faculty directories, but doing so by hand is prohibitively expensive and time-consuming. Here, we introduce a topical web crawler for automating the collection of faculty information from web-based department rosters, and demonstrate the resulting system on the 205 PhD-granting computer science departments in the U.S. and Canada. This method constructs a complete census of the field within a few minutes, and achieves over 99% precision and recall. We conclude by comparing the resulting 2017 census to a hand-curated 2011 census to quantify turnover and retention in computer science, in general and for female faculty in particular, demonstrating the types of analysis made possible by automated census construction., Comment: 11 pages, 6 figures, 2 tables

Published
2018
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17. The misleading narrative of the canonical faculty productivity trajectory

Author

Way, Samuel F., Morgan, Allison C., Clauset, Aaron, and Larremore, Daniel B.

Subjects
Computer Science - Digital Libraries, Physics - Physics and Society
Abstract

A scientist may publish tens or hundreds of papers over a career, but these contributions are not evenly spaced in time. Sixty years of studies on career productivity patterns in a variety of fields suggest an intuitive and universal pattern: productivity tends to rise rapidly to an early peak and then gradually declines. Here, we test the universality of this conventional narrative by analyzing the structures of individual faculty productivity time series, constructed from over 200,000 publications and matched with hiring data for 2453 tenure-track faculty in all 205 Ph.D-granting computer science departments in the U.S. and Canada. Unlike prior studies, which considered only some faculty or some institutions, or lacked common career reference points, here we combine a large bibliographic dataset with comprehensive information on career transitions that covers an entire field of study. We show that the conventional narrative confidently describes only one fifth of faculty, regardless of department prestige or researcher gender, and the remaining four fifths of faculty exhibit a rich diversity of productivity patterns. To explain this diversity, we introduce a simple model of productivity trajectories, and explore correlations between its parameters and researcher covariates, showing that departmental prestige predicts overall individual productivity and the timing of the transition from first- to last-author publications. These results demonstrate the unpredictability of productivity over time, and open the door for new efforts to understand how environmental and individual factors shape scientific productivity., Comment: 18 pages, 16 figures

Published
2016
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18. Decision-Making Regarding Newborn Circumcision: A Qualitative Analysis

Author

Morgan, Allison M., Hu, Yue-Yung, Benin, Andrea, and Lockwood, Gina M.

Subjects
Circumcision -- Demographic aspects, Decision-making -- Health aspects, Infants (Newborn) -- Health aspects, Health care industry
Abstract

Objectives Circumcision of newborn males is left to parental preference, as medical necessity has not been demonstrated. For medical providers seeking to help parents make decisions and provide informed consent, there is little information regarding how parents gather and process information about circumcision. This study aimed to characterize the comprehensive range of parental attitudes, gaps in knowledge, and decision-making regarding circumcision. Methods Qualitative data was obtained from semi-structured open-ended interviews conducted during the postpartum hospitalization. Interviews were recorded, transcribed, and coded by multiple independent reviewers. A grounded theory approach was used to identify emergent themes regarding attitudes towards, sources of information about, and decision-making surrounding circumcision. Results Ten mothers were interviewed, of whom six planned to circumcise and four did not. Major themes emerged: the importance of cultural norms, limited yet influential discussions, and the lack of, but desire for, more knowledge. Discussions with medical providers were often limited, though when physician conversation was more extensive, provider input was highly influential. Parents lacked evidence-based knowledge of the risks and benefits of the procedure. They uniformly desire more information and counseling from their medical providers. Conclusions for Practice This study affirms the importance of sociocultural factors and identified a discrepancy between parents' desire for empiric information and the counsel offered by providers, identifying a need for improved parent counseling. The qualitative themes that emerged from this work enabled the development of a comprehensive conceptual model that can be further tested to develop a decision aid for circumcision of the newborn., Author(s): Allison M. Morgan [sup.1] , Yue-Yung Hu [sup.1] [sup.2] [sup.3] , Andrea Benin [sup.3] , Gina M. Lockwood [sup.3] [sup.4] Author Affiliations: (1) grid.16753.36, 0000 0001 2299 3507, Surgical [...]

Published
2021
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19. Effect of differentiated service delivery models for HIV treatment on healthcare providers’ job satisfaction and workloads in sub-Saharan Africa: a mixed methods study from Malawi, Zambia, and South Africa

Author

Ntjikelane, Vinolia, primary, Phiri, Bevis, additional, Kaiser, Jeanette L., additional, Rosen, Sydney, additional, Morgan, Allison J, additional, Huber, Amy, additional, Mokhele, Idah, additional, Tchereni, Timothy, additional, Ngoma, Stanley, additional, Mulenga, Priscilla Lumano, additional, Pascoe, Sophie, additional, and Scott, Nancy, additional

Published
2024
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23. Landscape of cancer clinical trials in India – a comprehensive analysis of the Clinical Trial Registry-India

Author

Gao, Peng, primary, Chen, Justin, additional, Hong, Zhongyu, additional, Choi, Marcus, additional, Morgan, Allison, additional, Petushkov, Anton, additional, Lall, Rajuli, additional, Liu, Chao, additional, Muddu, Vamshi K., additional, Arroju, Venugopal, additional, Sunkavalli, Chinnababu, additional, Kim, Geoffrey, additional, and Reddy, Bobby Y., additional

Published
2023
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27. Gender and retention patterns among U.S. faculty

Author

Spoon, Katie, primary, LaBerge, Nicholas, additional, Wapman, K. Hunter, additional, Zhang, Sam, additional, Morgan, Allison C., additional, Galesic, Mirta, additional, Fosdick, Bailey K., additional, Larremore, Daniel B., additional, and Clauset, Aaron, additional

Published
2023
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30. Subfield Prestige and Gender Inequality among U.S. Computing Faculty: A study of the intersections of gender, race, socioeconomic status, prestige, and subfield structure in computing.

Author

LABERGE, NICHOLAS, WAPMAN, K. HUNTER, MORGAN, ALLISON C., SAM ZHANG, LARREMORE, DANIEL B., and CLAUSET, AARON

Subjects
GENDER inequality, COMPUTER science teachers, WOMEN college teachers, DIVERSITY in education, PEOPLE of color, HUMAN-computer interaction, ARTIFICIAL intelligence, ACADEMIC departments
Abstract

The article discusses gender inequality and subfield prestige in relation to the underrepresentation of female and people of color faculty members in American college computing programs, and it mentions computer science subfields such as human-computer interaction and artificial intelligence. Rankings of computer science graduate departments are assessed, along with the impact that computing departments' choices of subfields during the hiring process can have on gender diversity.

Published
2022
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38. Collective information processing of long-form text in multi-generational social networks

Author

Garcia-Bernardo, Javier, Aloric, Aleksandra, Santoro, Andrea, Neu, Zohar, Morgan, Allison, Hardy, Mathew, Griffiths, Tom, and Krafft, P.M.

Subjects
Applied Mathematics, Physics, network, Physical Sciences and Mathematics, FOS: Mathematics, Social and Behavioral Sciences, information processing
Abstract

This study will investigate how social network structure affects how narratives are processed in multi-generational human populations. Participants will be asked to reconstruct a text based on the texts produced by participants in the previous generation (similar to the children's game "telephone"). Our main manipulation will modify how many texts participants read: In one condition, participants will learn from one other participant in simple transmission chains. In the second, participants will learn from three participants in fully-connected feed-forward networks.

Published
2023
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39. The Children’s Brain Tumor Network (CBTN) - Accelerating Research in Pediatric Central Nervous System Tumors through Collaboration and Open Science

Author

Lilly, Jena V., primary, Rokita, Jo Lynne, additional, Mason, Jennifer L., additional, Patton, Tatiana, additional, Stefankiewiz, Stephanie, additional, Higgins, David, additional, Trooskin, Gerri, additional, Larouci, Carina A., additional, Arya, Kamnaa, additional, Appert, Elizabeth, additional, Heath, Allison P., additional, Zhu, Yuankun, additional, Brown, Miguel A., additional, Zhang, Bo, additional, Farrow, Bailey K., additional, Robins, Shannon, additional, Morgan, Allison M., additional, Nguyen, Thinh Q., additional, Frenkel, Elizabeth, additional, Lehmann, Kaitlin, additional, Drake, Emily, additional, Sullivan, Catherine, additional, Plisiewicz, Alexa, additional, Coleman, Noel, additional, Patterson, Luke, additional, Koptyra, Mateusz, additional, Helili, Zeinab, additional, Van Kuren, Nicholas, additional, Young, Nathan, additional, Kim, Meen Chul, additional, Friedman, Christopher, additional, Lubneuski, Alex, additional, Blackden, Christopher, additional, Williams, Marti, additional, Baubet, Valerie, additional, Tauhid, Lamiya, additional, Galanaugh, Jamie, additional, Boucher, Katie, additional, Ijaz, Heba, additional, Cole, Kristina A., additional, Choudhari, Namrata, additional, Santi, Mariarita, additional, Moulder, Robert W., additional, Waller, Jonathan, additional, Rife, Whitney, additional, Diskin, Sharon J., additional, Mateos, Marion, additional, Parsons, Donald W., additional, Pollack, Ian F., additional, Goldman, Stewart, additional, Leary, Sarah, additional, Caporalini, Chiara, additional, Buccoliero, Anna Maria, additional, Scagnet, Mirko, additional, Haussler, David, additional, Hanson, Derek, additional, Firestein, Ron, additional, Cain, Jason, additional, Phillips, Joanna J., additional, Gupta, Nalin, additional, Mueller, Sabine, additional, Grant, Gerald, additional, Monje-Deisseroth, Michelle, additional, Partap, Sonia, additional, Greenfield, Jeffrey P., additional, Hashizume, Rintaro, additional, Smith, Amy, additional, Zhu, Shida, additional, Johnston, James M., additional, Fangusaro, Jason R, additional, Miller, Matthew, additional, Wood, Matthew D., additional, Gardner, Sharon, additional, Carter, Claire L., additional, Prolo, Laura M., additional, Pisapia, Jared, additional, Pehlivan, Katherine, additional, Franson, Andrea, additional, Niazi, Toba, additional, Rubin, Josh, additional, Abdelbaki, Mohamed, additional, Ziegler, David S., additional, Lindsay, Holly B., additional, Stucklin, Ana Guerreiro, additional, Gerber, Nicolas, additional, Vaske, Olena M., additional, Quinsey, Carolyn, additional, Rood, Brian R., additional, Nazarian, Javad, additional, Raabe, Eric, additional, Jackson, Eric M., additional, Stapleton, Stacie, additional, Lober, Robert M., additional, Kram, David E., additional, Koschmann, Carl, additional, Storm, Phillip B., additional, Lulla, Rishi R., additional, Prados, Michael, additional, Resnick, Adam C., additional, and Waanders, Angela J., additional

Published
2022
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47. MODL-30. Children’s Brain Tumor Network preclinical tumor models development and sharing platform: collaborative model empowering pediatric brain tumor discovery and global research.

Author

Koptyra, Mateusz, primary, Baubet, Valerie, additional, Beale, David, additional, Patterson, Luke, additional, Biluck, Ian, additional, Hollawell, Madison, additional, Beck, Christopher M, additional, Sonawane, Poonam, additional, Griffin, Crystal, additional, Stern, Allison, additional, Madsen, Peter, additional, Foster, Jessica, additional, Lilly, Jena, additional, Mason, Jennifer, additional, Trooskin, Gerri, additional, Sullivan, Catherine, additional, Morgan, Allison, additional, Frenkel, Beth, additional, Lehmann, Kaitlin, additional, Lopez, Lina, additional, Nguyen, Thinh, additional, Agbodza, Ena, additional, Lopez-Gil, Valeria, additional, Helili, Zeinab, additional, Plisiewicz, Alexa, additional, Coleman, Noel, additional, Patton, Tatiana, additional, Stefankiewicz, Stephanie, additional, Arya, Kamnaa, additional, Velasco, Ryan, additional, Santi, Mariarita, additional, Viaene, Angela, additional, Storm, Phillip B, additional, and Resnick, Adam, additional

Published
2022
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