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2. Connecting omics signatures and revealing biological mechanisms with iLINCS

Author

Pilarczyk, Marcin, Fazel-Najafabadi, Mehdi, Kouril, Michal, Shamsaei, Behrouz, Vasiliauskas, Juozas, Niu, Wen, Mahi, Naim, Zhang, Lixia, Clark, Nicholas A., Ren, Yan, White, Shana, Karim, Rashid, Xu, Huan, Biesiada, Jacek, Bennett, Mark F., Davidson, Sarah E., Reichard, John F., Roberts, Kurt, Stathias, Vasileios, Koleti, Amar, Vidovic, Dusica, Clarke, Daniel J. B., Schürer, Stephan C., Ma’ayan, Avi, Meller, Jarek, and Medvedovic, Mario

Published
2022
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3. The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations

Author

Keenan, Alexandra B, Jenkins, Sherry L, Jagodnik, Kathleen M, Koplev, Simon, He, Edward, Torre, Denis, Wang, Zichen, Dohlman, Anders B, Silverstein, Moshe C, Lachmann, Alexander, Kuleshov, Maxim V, Ma'ayan, Avi, Stathias, Vasileios, Terryn, Raymond, Cooper, Daniel, Forlin, Michele, Koleti, Amar, Vidovic, Dusica, Chung, Caty, Schürer, Stephan C, Vasiliauskas, Jouzas, Pilarczyk, Marcin, Shamsaei, Behrouz, Fazel, Mehdi, Ren, Yan, Niu, Wen, Clark, Nicholas A, White, Shana, Mahi, Naim, Zhang, Lixia, Kouril, Michal, Reichard, John F, Sivaganesan, Siva, Medvedovic, Mario, Meller, Jaroslaw, Koch, Rick J, Birtwistle, Marc R, Iyengar, Ravi, Sobie, Eric A, Azeloglu, Evren U, Kaye, Julia, Osterloh, Jeannette, Haston, Kelly, Kalra, Jaslin, Finkbiener, Steve, Li, Jonathan, Milani, Pamela, Adam, Miriam, Escalante-Chong, Renan, Sachs, Karen, Lenail, Alex, Ramamoorthy, Divya, Fraenkel, Ernest, Daigle, Gavin, Hussain, Uzma, Coye, Alyssa, Rothstein, Jeffrey, Sareen, Dhruv, Ornelas, Loren, Banuelos, Maria, Mandefro, Berhan, Ho, Ritchie, Svendsen, Clive N, Lim, Ryan G, Stocksdale, Jennifer, Casale, Malcolm S, Thompson, Terri G, Wu, Jie, Thompson, Leslie M, Dardov, Victoria, Venkatraman, Vidya, Matlock, Andrea, Van Eyk, Jennifer E, Jaffe, Jacob D, Papanastasiou, Malvina, Subramanian, Aravind, Golub, Todd R, Erickson, Sean D, Fallahi-Sichani, Mohammad, Hafner, Marc, Gray, Nathanael S, Lin, Jia-Ren, Mills, Caitlin E, Muhlich, Jeremy L, Niepel, Mario, Shamu, Caroline E, Williams, Elizabeth H, Wrobel, David, Sorger, Peter K, Heiser, Laura M, Gray, Joe W, Korkola, James E, Mills, Gordon B, LaBarge, Mark, Feiler, Heidi S, Dane, Mark A, Bucher, Elmar, Nederlof, Michel, Sudar, Damir, and Gross, Sean

Subjects
Bioengineering, Cancer, Genetics, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, Good Health and Well Being, Cataloging, Computational Biology, Databases, Chemical, Gene Expression Profiling, Gene Library, Humans, Information Storage and Retrieval, National Health Programs, National Institutes of Health (U.S.), Systems Biology, Transcriptome, United States, BD2K, L1000, MCF10A, MEMA, P100, data integration, lincsprogram, lincsproject, systems biology, systems pharmacology, Biochemistry and Cell Biology
Abstract

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.

Published
2018

7. Advancing culturally responsive-sustaining computer science through K-12 teacher professional development strategies.

Author

White, Shana V., Koshy, Sonia, and Scott, Allison

Abstract

AbstractTo address racial and gender inequality in K-12 computer science (CS) education, there needs to be a multi-pronged approach. In addition to curricula that are culturally responsive and sustaining inclusive, K-12 CS teachers need to be equipped to implement the curriculum, pedagogy, and instruction to mitigate the racial and gender gaps in classrooms. Key results showed significant improvements in teachers’ confidence in carrying out culturally responsive-sustaining practices upon the completion of PD to improve teachers’ pedagogy within K-12 classrooms. A three-month follow-up showed that teachers integrated the CRCS practices to different degrees. Furthermore, examples of how the framework was integrated are shared. The PD and associated findings were made available as proposed scalable and replicable models for in-service CS teacher PD across the nation. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Data sharing as a national quality improvement program: reporting on BRCA1 and BRCA2 variant-interpretation comparisons through the Canadian Open Genetics Repository (COGR)

Author

Lebo, Matthew S., Zakoor, Kathleen-Rose, Chun, Kathy, Speevak, Marsha D., Waye, John S., McCready, Elizabeth, Parboosingh, Jillian S., Lamont, Ryan E., Feilotter, Harriet, Bosdet, Ian, Tucker, Tracy, Young, Sean, Karsan, Aly, Charames, George S., Agatep, Ronald, Spriggs, Elizabeth L., Chisholm, Caitlin, Vasli, Nasim, Daoud, Hussein, Jarinova, Olga, Tomaszewski, Robert, Hume, Stacey, Taylor, Sherryl, Akbari, Mohammad R., Lerner-Ellis, Jordan, Agatep, Ron, Ainsworth, Peter, Aronson, Melyssa, Basran, Raveen, Blavier, Andre, Blumenthal, Andrea, Boycott, Kym, Brudno, Michael, Buckley, Kathleen, Campbell, Jodi, M. Campeau, Philippe, Care, Melanie, Carson, Nancy, Carter, Ronald, Charames, George, Chitayat, David, Chong, George, Chouinard, Edmond, Craddock, Kenneth J., Docking, Rod, Eisen, Andrea, Faghfoury, Hanna, Farrell, Sandra, Fernandez, Bridget, Fiume, Marc, Forster-Gibson, Cynthia, Friedman, Jan, Foulkes, William, Goodhand, Peter, Gu, Jessica, Hegele, Robert, Holter, Spring, Horsburgh, Sheri, Hughes, Lauren, Jewett, Franny, Junker, Anne, Khalouei, Sam, Knoll, Joan, Kolomeitz, Elena, Knoppers, Bartha, Lamont, Ryan, Lebo, Matthew, Maire, Georges, Marshall, Christian, Mitchell, Grant, J Moorhouse, Michael, Morel, Chantal, Nelson, Tanya, Noor, Abdul, O'Connor, Brian, O'Rielly, Darren, Ouellette, Francis, Parboosingh, Jillian, Racher, Hilary, Ray, Peter, Rehm, Heidi, Riddell, Christie, Riviere, Jean-Baptiste, Rosenblatt, David S., Rouleau, Guy, Ruchon, Andrea, Sabatini, Peter, Sadikovic, Bekim, Semotiuk, Kara, Scherer, Stephen W., Shuman, Cheryl, Silver, Josh, Siminovitch, Katherine, Solomon-Izsak, Lesley, Soucy, Jean-Francois, Speevak, Marsha, Stavropoulos, James, Stein, Lincoln, Tannenbaum, Rhonda, Terespolsky, Deborah, Wintle, Richard F., Wong, Beatrix, Wong, Nora, Wang, Marina, Watkins, Nicholas, White, Shana, Woods, Michael O., and Wyatt, Philip

Published
2018
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9. A Quantitative Assessment of Tremor and Ataxia in Female FMR1 Premutation Carriers Using CATSYS

Author

Narcisa, Vivien, Aguilar, Dalila, Nguyen, Danh V, Campos, Luis, Brodovsky, Jeffrey, White, Shana, Adams, Patrick, Tassone, Flora, Hagerman, Paul J, and Hagerman, Randi J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Women's Health, Brain Disorders, Clinical Research, Neurosciences, Rare Diseases, Fragile X Syndrome, Intellectual and Developmental Disabilities (IDD), Aging, Clinical sciences
Abstract

The fragile X-associated tremor/ataxia syndrome (FXTAS) is a relatively common cause of balance problems leading to gait disturbances in older males (40%) with the premutation. FXTAS is less common in females. We utilized the CATSYS system, a quantitative measure of movement, in 23 women with FXTAS (mean age 62.7; SD 12.3), 90 women with the premutation without FXTAS (mean age 52.9; SD 9.4), and 37 controls (mean age 56.53; SD 7.8). CATSYS distinguished differences between carriers with and without FXTAS in postural tremor, postural sway, hand coordination, and reaction time tasks. Differences were also seen between carriers without FXTAS and controls in finger tapping, reaction time, and one postural sway task. However, these differences did not persist after statistical correction for multiple comparisons. Notably, there were no differences across groups in intention tremor. This is likely due to the milder symptoms in females compared to males with FXTAS.

Published
2011

11. Supporting the Integration of Social Justice Topics within K-12 Computing Education

Author

Massachusetts Institute of Technology. Media Laboratory, Jayathirtha, Gayithri, Goode, Joanna, Washington, Nicki, White, Shana, Yadav, Aman, Sadler, Cecil?, Massachusetts Institute of Technology. Media Laboratory, Jayathirtha, Gayithri, Goode, Joanna, Washington, Nicki, White, Shana, Yadav, Aman, and Sadler, Cecil?

Published
2023

13. Loss-of-function variants in SRRM2 cause a neurodevelopmental disorder

Author

Cuinat, Silvestre, Nizon, Mathilde, Isidor, Bertrand, Stegmann, Alexander, van Jaarsveld, Richard H., van Gassen, Koen L., van der Smagt, Jasper J., Volker-Touw, Catharina M.L., Holwerda, Sjoerd J.B., Terhal, Paulien A., Schuhmann, Sarah, Vasileiou, Georgia, Khalifa, Mohamed, Nugud, Alaa A., Yasaei, Hemad, Ousager, Lilian Bomme, Brasch-Andersen, Charlotte, Deb, Wallid, Besnard, Thomas, Simon, Marleen E.H., Amsterdam, Karin Huijsdens-van, Verbeek, Nienke E., Matalon, Dena, Dykzeul, Natalie, White, Shana, Spiteri, Elizabeth, Devriendt, Koen, Boogaerts, Anneleen, Willemsen, Marjolein, Brunner, Han G., Sinnema, Margje, De Vries, Bert B.A., Gerkes, Erica H., Pfundt, Rolph, Izumi, Kosuke, Krantz, Ian D., Xu, Zhou L., Murrell, Jill R., Valenzuela, Irene, Cusco, Ivon, Rovira-Moreno, Eulàlia, Yang, Yaping, Bizaoui, Varoona, Patat, Olivier, Faivre, Laurence, Tran-Mau-Them, Frederic, Vitobello, Antonio, Denommé-Pichon, Anne-Sophie, Philippe, Christophe, Bezieau, Stéphane, and Cogné, Benjamin

Published
2022
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14. Loss-of-function variants in SRRM2 cause a neurodevelopmental disorder

Author

Genetica Sectie Genoomdiagnostiek, Child Health, Genetica Klinische Genetica, Circulatory Health, Cuinat, Silvestre, Nizon, Mathilde, Isidor, Bertrand, Stegmann, Alexander, van Jaarsveld, Richard H, van Gassen, Koen L, van der Smagt, Jasper J, Volker-Touw, Catharina M L, Holwerda, Sjoerd J B, Terhal, Paulien A, Schuhmann, Sarah, Vasileiou, Georgia, Khalifa, Mohamed, Nugud, Alaa A, Yasaei, Hemad, Ousager, Lilian Bomme, Brasch-Andersen, Charlotte, Deb, Wallid, Besnard, Thomas, Simon, Marleen E H, Amsterdam, Karin Huijsdens-van, Verbeek, Nienke E, Matalon, Dena, Dykzeul, Natalie, White, Shana, Spiteri, Elizabeth, Devriendt, Koen, Boogaerts, Anneleen, Willemsen, Marjolein, Brunner, Han G, Sinnema, Margje, De Vries, Bert B A, Gerkes, Erica H, Pfundt, Rolph, Izumi, Kosuke, Krantz, Ian D, Xu, Zhou L, Murrell, Jill R, Valenzuela, Irene, Cusco, Ivon, Rovira-Moreno, Eulàlia, Yang, Yaping, Bizaoui, Varoona, Patat, Olivier, Faivre, Laurence, Tran-Mau-Them, Frederic, Vitobello, Antonio, Denommé-Pichon, Anne-Sophie, Philippe, Christophe, Bezieau, Stéphane, Cogné, Benjamin, Genetica Sectie Genoomdiagnostiek, Child Health, Genetica Klinische Genetica, Circulatory Health, Cuinat, Silvestre, Nizon, Mathilde, Isidor, Bertrand, Stegmann, Alexander, van Jaarsveld, Richard H, van Gassen, Koen L, van der Smagt, Jasper J, Volker-Touw, Catharina M L, Holwerda, Sjoerd J B, Terhal, Paulien A, Schuhmann, Sarah, Vasileiou, Georgia, Khalifa, Mohamed, Nugud, Alaa A, Yasaei, Hemad, Ousager, Lilian Bomme, Brasch-Andersen, Charlotte, Deb, Wallid, Besnard, Thomas, Simon, Marleen E H, Amsterdam, Karin Huijsdens-van, Verbeek, Nienke E, Matalon, Dena, Dykzeul, Natalie, White, Shana, Spiteri, Elizabeth, Devriendt, Koen, Boogaerts, Anneleen, Willemsen, Marjolein, Brunner, Han G, Sinnema, Margje, De Vries, Bert B A, Gerkes, Erica H, Pfundt, Rolph, Izumi, Kosuke, Krantz, Ian D, Xu, Zhou L, Murrell, Jill R, Valenzuela, Irene, Cusco, Ivon, Rovira-Moreno, Eulàlia, Yang, Yaping, Bizaoui, Varoona, Patat, Olivier, Faivre, Laurence, Tran-Mau-Them, Frederic, Vitobello, Antonio, Denommé-Pichon, Anne-Sophie, Philippe, Christophe, Bezieau, Stéphane, and Cogné, Benjamin

Published
2022

18. Canadian Open Genetics Repository (COGR): a unified clinical genomics database as a community resource for standardising and sharing genetic interpretations

Author

Lerner-Ellis, Jordan, Wang, Marina, White, Shana, Lebo, Matthew S, Agatep, Ron, Ainsworth, Peter, Akbari, Mohammad R, Aronson, Melyssa, Bader, Gary D, Basran, Raveen, Blavier, Andre, Blumenthal, Andrea, Buckley, Kathleen, Campbell, Jodi, Campeau, Philippe M, Care, Melanie, Carson, Nancy, Carter, Ronald, Charames, George, Chitayat, David, Chong, George, Chouinard, Edmond, Chun, Kathy, Craddock, Kenneth J, Docking, Rod, Eisen, Andrea, Faghfoury, Hanna, Farrell, Sandra, Feilotter, Harriet, Fernandez, Bridget, Forster-Gibson, Cynthia, Foulkes, William, Hegele, Robert, Holter, Spring, Horsburgh, Sheri, Hughes, Lauren, Hume, Stacey, Jewett, Franny, Karsan, Aly, Khalouei, Sam, Knoll, Joan, Kolomeitz, Elena, Maire, Georges, Marshall, Christian, McCready, Elizabeth, Moorhouse, Michael J, Morel, Chantal, Nelson, Tanya, OʼConnor, Brian, Ouellette, Francis, Parboosingh, Jillian, Ray, Peter, Rehm, Heidi, Riddell, Christie, Rosenblatt, David S, Ruchon, Andrea, Sadikovic, Bekim, Semotiuk, Kara, Scherer, Stephen W, Shuman, Cheryl, Silver, Josh, Siminovitch, Katherine, Solomon-Izsak, Lesley, Speevak, Marsha, Stavropoulos, James, Stein, Lincoln, Tannenbaum, Rhonda, Terespolsky, Deborah, Wintle, Richard F, Wong, Beatrix, Wong, Nora, Waye, John S, Woods, Michael O, Wyatt, Philip, and Young, Sean

Published
2015
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20. Assessment of network module identification across complex diseases

Author

Choobdar, Sarvenaz, Ahsen, Mehmet E., Natoli, Ted, Lysenko, Artem, Ma, Tianle, Mall, Raghvendra, Marbach, Daniel, Mattia, Tomasoni, Medvedovic, Mario, Menche, Jörg, Mercer, Johnathan, Micarelli, Elisa, Monaco, Alfonso, Narayan, Rajiv, Müller, Felix, Narykov, Oleksandr, Norman, Thea, Park, Sungjoon, Perfetto, Livia, Perrin, Dimitri, Pirrò, Stefano, Przytycka, Teresa M., DREAM Module Identification Challenge Consortium, Qian, Xiaoning, Raman, Karthik, Ramazzotti, Daniele, Ramsahai, Emilie, Ravindran, Balaraman, Rennert, Philip, Sáez Rodríguez, Julio, Schärfe, Charlotta, Sharan, Roded, Shi, Ning, Subramanian, Aravind, Shin, Wonho, Shu, Hai, Sinha, Himanshu, Slonim, Donna K., Spinelli, Lionel, Srinivasan, Suhas, Suver, Christine, Szklarczyk, Damian, Tangaro, Sabina, Zhang, Jitao D., Thiagarajan, Suresh, Tichit, Laurent, Tiede, Thorsten, Tripathi, Beethika, Tsherniak, Aviad, Tsunoda, Tatsuhiko, Türei, Dénes, Ullah, Ehsan, Vahedi, Golnaz, Valdeolivas, Alberto, Stolovitzky, Gustavo, Vivek, Jayaswal, von Mering, Christian, Waagmeester, Andra, Wang, Bo, Wang, Yijie, Weir, Barbara A., White, Shana, Winkler, Sebastian, Xu, Ke, Xu, Taosheng, Kutalik, Zoltán, Yan, Chunhua, Yang, Liuqing, Yu, Kaixian, Yu, Xiangtian, Zaffaroni, Gaia, Zaslavskiy, Mikhail, Zeng, Tao, Zhang, Lu, Zhang, Weijia, Lage, Kasper, Zhang, Lixia, Zhang, Xinyu, Zhang, Junpeng, Zhou, Xin, Zhou, Jiarui, Zhu, Hongtu, Zhu, Junjie, Zuccon, Guido, Crawford, Jake, Cowen, Lenore J., Bergmann, Sven, Aicheler, Fabian, Amoroso, Nicola, Arenas, Alex, Azhagesan, Karthik, Baker, Aaron, Banf, Michael, Batzoglou, Serafim, Tomasoni, Mattia, Baudot, Anaïs, Bellotti, Roberto, Boroevich, Keith A., Brun, Christine, Cai, Stanley, Caldera, Michael, Calderone, Alberto, Cesareni, Gianni, Chen, Weiqi, Fang, Tao, Chichester, Christine, Cowen, Lenore, Cui, Hongzhu, Dao, Phuong, De Domenico, Manlio, Dhroso, Andi, Didier, Gilles, Divine, Mathew, Lamparter, David, Del Sol, Antonio, Feng, Xuyang, Flores-Canales, Jose C., Fortunato, Santo, Gitter, Anthony, Gorska, Anna, Guan, Yuanfang, Guénoche, Alain, Gómez, Sergio, Lin, Junyuan, Hamza, Hatem, Hartmann, András, He, Shan, Heijs, Anton, Heinrich, Julian, Hescott, Benjamin, Hu, Xiaozhe, Hu, Ying, Huang, Xiaoqing, Hughitt, V. Keith, Jeon, Minji, Jeub, Lucas, Johnson, Nathan T., Joo, Keehyoung, Joung, InSuk, Jung, Sascha, Kalko, Susana G., Kamola, Piotr J., Kang, Jaewoo, Kaveelerdpotjana, Benjapun, Kim, Minjun, Kim, Yoo-Ah, Kohlbacher, Oliver, Korkin, Dmitry, Krzysztof, Kiryluk, Kunji, Khalid, Kutalik, Zoltàn, Lang-Brown, Sean, Le, Thuc Duy, Lee, Jooyoung, Lee, Sunwon, Lee, Juyong, Li, Dong, Li, Jiuyong, Liu, Lin, Loizou, Antonis, Luo, Zhenhua, Choobdar, Sarvenaz, Ahsen, Mehmet E., Crawford, Jake, Tomasoni, Mattia, Le, Thuc Duy, Li, Jiuyong, Liu, Lin, Zhang, W, Marbach, D, The DREAM Module Identification Challenge Consortium, Choobdar, S, Ahsen, M, Crawford, J, Tomasoni, M, Fang, T, Lamparter, D, Lin, J, Hescott, B, Hu, X, Mercer, J, Natoli, T, Narayan, R, Aicheler, F, Amoroso, N, Arenas, A, Azhagesan, K, Baker, A, Banf, M, Batzoglou, S, Baudot, A, Bellotti, R, Bergmann, S, Boroevich, K, Brun, C, Cai, S, Caldera, M, Calderone, A, Cesareni, G, Chen, W, Chichester, C, Cowen, L, Cui, H, Dao, P, De Domenico, M, Dhroso, A, Didier, G, Divine, M, del Sol, A, Feng, X, Flores-Canales, J, Fortunato, S, Gitter, A, Gorska, A, Guan, Y, Guenoche, A, Gomez, S, Hamza, H, Hartmann, A, He, S, Heijs, A, Heinrich, J, Hu, Y, Huang, X, Hughitt, V, Jeon, M, Jeub, L, Johnson, N, Joo, K, Joung, I, Jung, S, Kalko, S, Kamola, P, Kang, J, Kaveelerdpotjana, B, Kim, M, Kim, Y, Kohlbacher, O, Korkin, D, Krzysztof, K, Kunji, K, Kutalik, Z, Lage, K, Lang-Brown, S, Le, T, Lee, J, Lee, S, Li, D, Li, J, Liu, L, Loizou, A, Luo, Z, Lysenko, A, Ma, T, Mall, R, Mattia, T, Medvedovic, M, Menche, J, Micarelli, E, Monaco, A, Muller, F, Narykov, O, Norman, T, Park, S, Perfetto, L, Perrin, D, Pirro, S, Przytycka, T, Qian, X, Raman, K, Ramazzotti, D, Ramsahai, E, Ravindran, B, Rennert, P, Saez-Rodriguez, J, Scharfe, C, Sharan, R, Shi, N, Shin, W, Shu, H, Sinha, H, Slonim, D, Spinelli, L, Srinivasan, S, Subramanian, A, Suver, C, Szklarczyk, D, Tangaro, S, Thiagarajan, S, Tichit, L, Tiede, T, Tripathi, B, Tsherniak, A, Tsunoda, T, Turei, D, Ullah, E, Vahedi, G, Valdeolivas, A, Vivek, J, von Mering, C, Waagmeester, A, Wang, B, Wang, Y, Weir, B, White, S, Winkler, S, Xu, K, Xu, T, Yan, C, Yang, L, Yu, K, Yu, X, Zaffaroni, G, Zaslavskiy, M, Zeng, T, Zhang, J, Zhang, L, Zhang, X, Zhou, X, Zhou, J, Zhu, H, Zhu, J, Zuccon, G, Stolovitzky, G, Spinelli, Lionel, Institut de Mathématiques de Marseille (I2M), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Theories and Approaches of Genomic Complexity (TAGC), DREAM Module Identification Challenge Consortium, Aicheler, F., Amoroso, N., Arenas, A., Azhagesan, K., Baker, A., Banf, M., Batzoglou, S., Baudot, A., Bellotti, R., Bergmann, S., Boroevich, K.A., Brun, C., Cai, S., Caldera, M., Calderone, A., Cesareni, G., Chen, W., Chichester, C., Choobdar, S., Cowen, L., Crawford, J., Cui, H., Dao, P., De Domenico, M., Dhroso, A., Didier, G., Divine, M., Del Sol, A., Fang, T., Feng, X., Flores-Canales, J.C., Fortunato, S., Gitter, A., Gorska, A., Guan, Y., Guénoche, A., Gómez, S., Hamza, H., Hartmann, A., He, S., Heijs, A., Heinrich, J., Hescott, B., Hu, X., Hu, Y., Huang, X., Hughitt, V.K., Jeon, M., Jeub, L., Johnson, N.T., Joo, K., Joung, I., Jung, S., Kalko, S.G., Kamola, P.J., Kang, J., Kaveelerdpotjana, B., Kim, M., Kim, Y.A., Kohlbacher, O., Korkin, D., Krzysztof, K., Kunji, K., Kutalik, Z., Lage, K., Lamparter, D., Lang-Brown, S., Le, T.D., Lee, J., Lee, S., Li, D., Li, J., Lin, J., Liu, L., Loizou, A., Luo, Z., Lysenko, A., Ma, T., Mall, R., Marbach, D., Mattia, T., Medvedovic, M., Menche, J., Mercer, J., Micarelli, E., Monaco, A., Müller, F., Narayan, R., Narykov, O., Natoli, T., Norman, T., Park, S., Perfetto, L., Perrin, D., Pirrò, S., Przytycka, T.M., Qian, X., Raman, K., Ramazzotti, D., Ramsahai, E., Ravindran, B., Rennert, P., Saez-Rodriguez, J., Schärfe, C., Sharan, R., Shi, N., Shin, W., Shu, H., Sinha, H., Slonim, D.K., Spinelli, L., Srinivasan, S., Subramanian, A., Suver, C., Szklarczyk, D., Tangaro, S., Thiagarajan, S., Tichit, L., Tiede, T., Tripathi, B., Tsherniak, A., Tsunoda, T., Türei, D., Ullah, E., Vahedi, G., Valdeolivas, A., Vivek, J., von Mering, C., Waagmeester, A., Wang, B., Wang, Y., Weir, B.A., White, S., Winkler, S., Xu, K., Xu, T., Yan, C., Yang, L., Yu, K., Yu, X., Zaffaroni, G., Zaslavskiy, M., Zeng, T., Zhang, J.D., Zhang, L., Zhang, W., Zhang, X., Zhang, J., Zhou, X., Zhou, J., Zhu, H., Zhu, J., and Zuccon, G.

Subjects
Identification methods, Cellular signalling networks, Computer science, Population genetics, [SDV]Life Sciences [q-bio], Quantitative Trait Loci, Gene regulatory network, DREAM challenge, network, modules, predictions, Genome-wide association study, Computational biology, Biochemistry, Models, Biological, Polymorphism, Single Nucleotide, Gene regulatory networks, Functional clustering, 03 medical and health sciences, Human disease, Humans, Disease, ddc:610, Protein Interaction Maps, Molecular Biology, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, Network module, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Network topology, Gene Expression Profiling, Computational Biology, Cell Biology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Gene expression profiling, [SDV] Life Sciences [q-bio], Molecular network, Phenotype, Protein network, Network Module Identification, Analysis, Algorithms, Biotechnology, Genome-Wide Association Study
Abstract

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the ‘Disease Module Identification DREAM Challenge’, an open competition to comprehensively assess module identification methods across diverse protein–protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology., In this DREAM challenge, 75 methods for the identification of disease-relevant modules from molecular networks are compared and validated with GWAS data. The authors provide practical guidelines for users and establish benchmarks for network analysis.

Published
2019
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21. Connecting omics signatures of diseases, drugs, and mechanisms of actions with iLINCS

Author

Pilarczyk, Marcin, primary, Kouril, Michal, additional, Shamsaei, Behrouz, additional, Vasiliauskas, Juozas, additional, Niu, Wen, additional, Mahi, Naim, additional, Zhang, Lixia, additional, Clark, Nicholas, additional, Ren, Yan, additional, White, Shana, additional, Karim, Rashid, additional, Xu, Huan, additional, Biesiada, Jacek, additional, Bennett, Mark F., additional, Davidson, Sarah, additional, Reichard, John F, additional, Roberts, Kurt, additional, Stathias, Vasileios, additional, Koleti, Amar, additional, Vidovic, Dusica, additional, Clarke, Daniel J.B., additional, Schurer, Stephan C., additional, Ma’ayan, Avi, additional, Meller, Jarek, additional, and Medvedovic, Mario, additional

Published
2019
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23. Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

Author

Choobdar, Sarvenaz, Ahsen, Mehmet E., Crawford, Jake, Tomasoni, Mattia, Fang, Tao, Lamparter, David, Lin, Junyuan, Hescott, Benjamin, Hu, Xiaozhe, Mercer, Johnathan, Natoli, Ted, Narayan, Rajiv, Subramanian, Aravind, Zhang, Jitao D., Stolovitzky, Gustavo, Kutalik, Zoltán, Lage, Kasper, Slonim, Donna K., Saez-Rodriguez, Julio, Cowen, Lenore J., Bergmann, Sven, Marbach, Daniel, Aicheler, Fabian, Amoroso, Nicola, Arenas, Alex, Azhagesan, Karthik, Baker, Aaron, Banf, Michael, Batzoglou, Serafim, Baudot, Anaïs, Bellotti, Roberto, Boroevich, Keith A., Brun, Christine, Cai, Stanley, Caldera, Michael, Calderone, Alberto, Cesareni, Gianni, Chen, Weiqi, Chichester, Christine, Cowen, Lenore, Cui, Hongzhu, Dao, Phuong, Domenico, Manlio De, Dhroso, Andi, Didier, Gilles, Divine, Mathew, Sol, Antonio del, Feng, Xuyang, Flores-Canales, Jose C., Fortunato, Santo, Gitter, Anthony, Gorska, Anna, Guan, Yuanfang, Guénoche, Alain, Gómez, Sergio, Hamza, Hatem, Hartmann, András, He, Shan, Heijs, Anton, Heinrich, Julian, Hu, Ying, Huang, Xiaoqing, Hughitt, V. Keith, Jeon, Minji, Jeub, Lucas, Johnson, Nathan, Joo, Keehyoung, Joung, InSuk, Jung, Sascha, Kalko, Susana G., Kamola, Piotr J., Kang, Jaewoo, Kaveelerdpotjana, Benjapun, Kim, Minjun, Kim, Yoo-Ah, Kohlbacher, Oliver, Korkin, Dmitry, Krzysztof, Kiryluk, Kunji, Khalid, Kutalik, Zoltàn, Lang-Brown, Sean, Le, Thuc Duy, Lee, Jooyoung, Lee, Sunwon, Lee, Juyong, Li, Dong, Li, Jiuyong, Liu, Lin, Loizou, Antonis, Luo, Zhenhua, Lysenko, Artem, Ma, Tianle, Mall, Raghvendra, Mattia, Tomasoni, Medvedovic, Mario, Menche, Jörg, Micarelli, Elisa, Monaco, Alfonso, Müller, Felix, Narykov, Oleksandr, Norman, Thea, Park, Sungjoon, Perfetto, Livia, Perrin, Dimitri, Pirrò, Stefano, Przytycka, Teresa M., Qian, Xiaoning, Raman, Karthik, Ramazzotti, Daniele, Ramsahai, Emilie, Ravindran, Balaraman, Rennert, Philip, Schärfe, Charlotta, Sharan, Roded, Shi, Ning, Shin, Wonho, Shu, Hai, Sinha, Himanshu, Spinelli, Lionel, Srinivasan, Suhas, Suver, Christine, Szklarczyk, Damian, Tangaro, Sabina, Thiagarajan, Suresh, Tichit, Laurent, Tiede, Thorsten, Tripathi, Beethika, Tsherniak, Aviad, Tsunoda, Tatsuhiko, Türei, Dénes, Ullah, Ehsan, Vahedi, Golnaz, Valdeolivas, Alberto, Vivek, Jayaswal, Mering, Christian von, Waagmeester, Andra, Wang, Bo, Wang, Yijie, Weir, Barbara A., White, Shana, Winkler, Sebastian, Xu, Ke, Xu, Taosheng, Yan, Chunhua, Yang, Liuqing, Yu, Kaixian, Yu, Xiangtian, Zaffaroni, Gaia, Zaslavskiy, Mikhail, Zeng, Tao, Zhang, Lu, Zhang, Weijia, Zhang, Lixia, Zhang, Xinyu, Zhang, Junpeng, Zhou, Xin, Zhou, Jiarui, Zhu, Hongtu, Zhu, Junjie, and Zuccon, Guido

Subjects
Identification methods, Molecular network, Computer science, Association (object-oriented programming), Key (cryptography), Open community, Genome-wide association study, Identification (biology), Computational biology, Disease
Abstract

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).

Published
2018
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27. Pharmacological inhibition of apical sodium-dependent bile acid transporter changes bile composition and blocks progression of sclerosing cholangitis in multidrug resistance 2 knockout mice

Author

Miethke, Alexander G., primary, Zhang, Wujuan, additional, Simmons, Julia, additional, Taylor, Amy E., additional, Shi, Tiffany, additional, Shanmukhappa, Shiva Kumar, additional, Karns, Rebekah, additional, White, Shana, additional, Jegga, Anil G., additional, Lages, Celine S., additional, Nkinin, Stephenson, additional, Keller, Bradley T., additional, and Setchell, Kenneth D.R., additional

Published
2015
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28. Cognitive Performance Scores for the Pediatric Automated Neuropsychological Assessment Metrics in Childhood-Onset Systemic Lupus Erythematosus

Author

Vega-Fernandez, Patricia, primary, Vanderburgh White, Shana, additional, Zelko, Frank, additional, Ruth, Natasha M., additional, Levy, Deborah M., additional, Muscal, Eyal, additional, Klein-Gitelman, Marisa S., additional, Huber, Adam M., additional, Tucker, Lori B., additional, Roebuck-Spencer, Tresa, additional, Ying, Jun, additional, and Brunner, Hermine I., additional

Published
2015
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29. 166-P Want a good read? Next-generation HLA sequencing using the Roche 454 GS FLX platform for five NIH projects

Author

Trachtenberg, Elizabeth, primary, Ladner, Martha, additional, Osoegawa, Kazu, additional, Cohen, Franziska, additional, Hawbecker, Sherry, additional, Zacarias, Fernanda Ribas, additional, Noonan, David, additional, White, Shana, additional, Graham, Kellie, additional, Agraz, John, additional, Mohr, Kathy, additional, Vinson, Margaret, additional, and Goodridge, Damian, additional

Published
2011
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31. 15-OR: A Multi-Site Study Employing High Resolution HLA Genotyping by Next Generation 454 GS FLX Sequencing

Author

Holcomb, Cherie L., primary, Höglund, Bryan, additional, Anderson, Matthew W., additional, Blake, Lisbeth A., additional, Böhme, Irena, additional, Egholm, Michael, additional, Ferriola, Deborah, additional, Gabriel, Christian, additional, Goodridge, Damian, additional, Klein, Rolf, additional, Ladner, Martha, additional, Lind, Curt, additional, Monos, Dimitri, additional, Pando, Marcelo, additional, Pröll, Johannes, additional, Sayer, David C., additional, Schmitz-Agheguian, Gudrun, additional, Simen, Birgitte B., additional, Thiele, Bernhard, additional, Trachtenberg, Elizabeth, additional, Tyan, Dolly B., additional, Wassmuth, Ralf, additional, White, Shana, additional, and Erlich, Henry A., additional

Published
2010
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33. Application and Development of Novel Methods for Pathway Analysis and Visualization of the LINCS L1000 Dataset

Author

White, Shana

Subjects
Biostatistics, Pathway Analysis, Cell Signaling, Cancer Cell Lines
Abstract

The LINCS L1000 dataset is a large-scale compendium that contains records of the cell line specific transcriptional effects of cellular perturbation that was established to provide mechanistic and circuit-level insights with regard to cancer biology. This undertaking is a scaled-up version of the Connectivity Map (CMap) project whose goal was to connect transcriptional signatures of the downstream effects of genetic and small-molecule perturbations in a high-throughput yet cost-effective manner. This was accomplished by profiling a reduced representation of the human transcriptome – nearly 1,000 landmark transcripts whose expression is predictive of roughly 80% of non-measured genes. Whereas the choice to measure a subset of the transcriptome was primarily cost-based, reducing the representation of transcriptional data is a common method for amplifying the signal amidst the noisy background of large datasets. It can also be a valuable tool for making data amenable to a variety of bioinformatics-based analyses, for example, when lists of genes and their direction of regulation is considered based on continuously valued measurements subjected to a significance-based threshold. In the work presented in this document, we subject the records contained in the L1000 dataset to a thresholding procedure and explore how connections between over 2,000 common genetic perturbations differ between a core set of seven cancer cell lines. Specifically, we frame the connections in the context of edges between nodes in a novel adaptation of pathway-level analysis.We begin by conducting a simulation study in order to interrogate the data-generating mechanism best suited to reproduce our data of interest with the least amount of bias. This will be followed by a power analysis to assess the appropriate threshold for edge-based measurements for our dataset. Then, we will demonstrate how these measurements can be incorporated into the topology of cellular signaling pathways and introduce an R Bioconductor package that easily integrates this type of data into pathways from the Kyoto Encyclopedia of Genes and Genomes or KEGG – one of the most widely known online repositories for biological pathways. Finally, we will conduct an edge set enrichment analysis of our data that applies the well-known methodology of gene set enrichment analysis to this novel edge-data type.

Published
2021

34. Loss-of-function variants in SRRM2cause a neurodevelopmental disorder

Author

Cuinat, Silvestre, Nizon, Mathilde, Isidor, Bertrand, Stegmann, Alexander, van Jaarsveld, Richard H., van Gassen, Koen L., van der Smagt, Jasper J., Volker-Touw, Catharina M.L., Holwerda, Sjoerd J.B., Terhal, Paulien A., Schuhmann, Sarah, Vasileiou, Georgia, Khalifa, Mohamed, Nugud, Alaa A., Yasaei, Hemad, Ousager, Lilian Bomme, Brasch-Andersen, Charlotte, Deb, Wallid, Besnard, Thomas, Simon, Marleen E.H., Amsterdam, Karin Huijsdens-van, Verbeek, Nienke E., Matalon, Dena, Dykzeul, Natalie, White, Shana, Spiteri, Elizabeth, Devriendt, Koen, Boogaerts, Anneleen, Willemsen, Marjolein, Brunner, Han G., Sinnema, Margje, De Vries, Bert B.A., Gerkes, Erica H., Pfundt, Rolph, Izumi, Kosuke, Krantz, Ian D., Xu, Zhou L., Murrell, Jill R., Valenzuela, Irene, Cusco, Ivon, Rovira-Moreno, Eulàlia, Yang, Yaping, Bizaoui, Varoona, Patat, Olivier, Faivre, Laurence, Tran-Mau-Them, Frederic, Vitobello, Antonio, Denommé-Pichon, Anne-Sophie, Philippe, Christophe, Bezieau, Stéphane, and Cogné, Benjamin

Abstract

SRRM2encodes the SRm300 protein, a splicing factor of the SR-related protein family characterized by its serine- and arginine-enriched domains. It promotes interactions between messenger RNA and the spliceosome catalytic machinery. This gene, predicted to be highly intolerant to loss of function (LoF) and very conserved through evolution, has not been previously reported in constitutive human disease.

Published
2022
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35. Assessment of network module identification across complex diseases

Author

Choobdar, Sarvenaz, Ahsen, Mehmet E., Crawford, Jake, Tomasoni, Mattia, Fang, Tao, Lamparter, David, Lin, Junyuan, Hescott, Benjamin, Hu, Xiaozhe, Mercer, Johnathan, Natoli, Ted, Narayan, Rajiv, Subramanian, Aravind, Zhang, Jitao D., Stolovitzky, Gustavo, Kutalik, Zoltán, Lage, Kasper, Slonim, Donna K., Sáez Rodríguez, Julio, Cowen, Lenore J., Bergmann, Sven, Marbach, Daniel, Aicheler, Fabian, Amoroso, Nicola, Arenas, Alex, Azhagesan, Karthik, Baker, Aaron, Banf, Michael, Batzoglou, Serafim, Baudot, Anaïs, Bellotti, Roberto, Boroevich, Keith A., Brun, Christine, Cai, Stanley, Caldera, Michael, Calderone, Alberto, Cesareni, Gianni, Chen, Weiqi, Chichester, Christine, Cowen, Lenore, Cui, Hongzhu, Dao, Phuong, De Domenico, Manlio, Dhroso, Andi, Didier, Gilles, Divine, Mathew, Del Sol, Antonio, Feng, Xuyang, Flores-Canales, Jose C., Fortunato, Santo, Gitter, Anthony, Gorska, Anna, Guan, Yuanfang, Guénoche, Alain, Gómez, Sergio, Hamza, Hatem, Hartmann, András, He, Shan, Heijs, Anton, Heinrich, Julian, Hu, Ying, Huang, Xiaoqing, Hughitt, V. Keith, Jeon, Minji, Jeub, Lucas, Johnson, Nathan T., Joo, Keehyoung, Joung, InSuk, Jung, Sascha, Kalko, Susana G., Kamola, Piotr J., Kang, Jaewoo, Kaveelerdpotjana, Benjapun, Kim, Minjun, Kim, Yoo-Ah, Kohlbacher, Oliver, Korkin, Dmitry, Krzysztof, Kiryluk, Kunji, Khalid, Kutalik, Zoltàn, Lang-Brown, Sean, Le, Thuc Duy, Lee, Jooyoung, Lee, Sunwon, Lee, Juyong, Li, Dong, Li, Jiuyong, Liu, Lin, Loizou, Antonis, Luo, Zhenhua, Lysenko, Artem, Ma, Tianle, Mall, Raghvendra, Mattia, Tomasoni, Medvedovic, Mario, Menche, Jörg, Micarelli, Elisa, Monaco, Alfonso, Müller, Felix, Narykov, Oleksandr, Norman, Thea, Park, Sungjoon, Perfetto, Livia, Perrin, Dimitri, Pirrò, Stefano, Przytycka, Teresa M., Qian, Xiaoning, Raman, Karthik, Ramazzotti, Daniele, Ramsahai, Emilie, Ravindran, Balaraman, Rennert, Philip, Schärfe, Charlotta, Sharan, Roded, Shi, Ning, Shin, Wonho, Shu, Hai, Sinha, Himanshu, Spinelli, Lionel, Srinivasan, Suhas, Suver, Christine, Szklarczyk, Damian, Tangaro, Sabina, Thiagarajan, Suresh, Tichit, Laurent, Tiede, Thorsten, Tripathi, Beethika, Tsherniak, Aviad, Tsunoda, Tatsuhiko, Türei, Dénes, Ullah, Ehsan, Vahedi, Golnaz, Valdeolivas, Alberto, Vivek, Jayaswal, Von Mering, Christian, Waagmeester, Andra, Wang, Bo, Wang, Yijie, Weir, Barbara A., White, Shana, Winkler, Sebastian, Xu, Ke, Xu, Taosheng, Yan, Chunhua, Yang, Liuqing, Yu, Kaixian, Yu, Xiangtian, Zaffaroni, Gaia, Zaslavskiy, Mikhail, Zeng, Tao, Zhang, Lu, Zhang, Weijia, Zhang, Lixia, Zhang, Xinyu, Zhang, Junpeng, Zhou, Xin, Zhou, Jiarui, Zhu, Hongtu, Zhu, Junjie, and Zuccon, Guido

Subjects
3. Good health
Abstract

Nature methods 16(9), 843-852 (2019). doi:10.1038/s41592-019-0509-5, Published by Nature Publishing Group, London [u.a.]

36. Developing a genomics rotation: Practical training around variant interpretation for genetic counseling students.

Author

Grove ME, White S, Fisk DG, Rego S, Dagan-Rosenfeld O, Kohler JN, Reuter CM, Bonner D, Wheeler MT, Bernstein JA, Ormond KE, and Hanson-Kahn AK

Subjects
Adult, Humans, Program Development, Universities, Counselors education, Curriculum, Genetic Counseling, Genetic Testing, Genomics education
Abstract

With the wide adoption of next-generation sequencing (NGS)-based genetic tests, genetic counselors require increased familiarity with NGS technology, variant interpretation concepts, and variant assessment tools. The use of exome and genome sequencing in clinical care has expanded the reach and diversity of genetic testing. Regardless of the setting where genetic counselors are performing variant interpretation or reporting, most of them have learned these skills from colleagues, while on the job. Though traditional, lecture-based learning around these topics is important, there has been growing need for the inclusion of case-based, experiential training of genomics and variant interpretation for genetic counseling students, with the goal of creating a strong foundation in variant interpretation for new genetic counselors, regardless of what area of practice they enter. To address this need, we established a genomics and variant interpretation rotation for Stanford's genetic counseling training program. In response to changes in the genomics landscape, this has now evolved into three unique rotation experiences, each focused on variant interpretation in the context of various genomic settings, including clinical laboratory, research laboratory, and healthy genomic analysis studies. Here, we describe the goals and learning objectives that we have developed for these variant interpretation rotations, and illustrate how these concepts are applied in practice., (© 2019 National Society of Genetic Counselors.)

Published
2019
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