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1. Toward Constraint Compliant Goal Formulation and Planning

Author

Jones, Steven J. and Wray, Robert E.

Subjects
Computer Science - Artificial Intelligence, I.2.11, I.2.8
Abstract

One part of complying with norms, rules, and preferences is incorporating constraints (such as knowledge of ethics) into one's goal formulation and planning processing. We explore in a simple domain how the encoding of knowledge in different ethical frameworks influences an agent's goal formulation and planning processing and demonstrate ability of an agent to satisfy and satisfice when its collection of relevant constraints includes a mix of "hard" and "soft" constraints of various types. How the agent attempts to comply with ethical constraints depends on the ethical framing and we investigate tradeoffs between deontological framing and utilitarian framing for complying with an ethical norm. Representative scenarios highlight how performing the same task with different framings of the same norm leads to different behaviors. Our explorations suggest an important role for metacognitive judgments in resolving ethical conflicts during goal formulation and planning., Comment: 16 pages + refs. 5 figures, 2 tables. Minor revisions based on reviewer feedback. Accepted for presentation at Advances in Cognitive Systems (Jun 2024, Palermo)

Published
2024

2. AI-based histopathology image analysis reveals a distinct subset of endometrial cancers

Author

Darbandsari, Amirali, Farahani, Hossein, Asadi, Maryam, Wiens, Matthew, Cochrane, Dawn, Khajegili Mirabadi, Ali, Jamieson, Amy, Farnell, David, Ahmadvand, Pouya, Douglas, Maxwell, Leung, Samuel, Abolmaesumi, Purang, Jones, Steven J. M., Talhouk, Aline, Kommoss, Stefan, Gilks, C. Blake, Huntsman, David G., Singh, Naveena, McAlpine, Jessica N., and Bashashati, Ali

Published
2024
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3. Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers

Author

Deyell, Rebecca J., Shen, Yaoqing, Titmuss, Emma, Dixon, Katherine, Williamson, Laura M., Pleasance, Erin, Nelson, Jessica M. T., Abbasi, Sanna, Krzywinski, Martin, Armstrong, Linlea, Bonakdar, Melika, Ch’ng, Carolyn, Chuah, Eric, Dunham, Chris, Fok, Alexandra, Jones, Martin, Lee, Anna F., Ma, Yussanne, Moore, Richard A., Mungall, Andrew J., Mungall, Karen L., Rogers, Paul C., Schrader, Kasmintan A., Virani, Alice, Wee, Kathleen, Young, Sean S., Zhao, Yongjun, Jones, Steven J. M., Laskin, Janessa, Marra, Marco A., and Rassekh, Shahrad R.

Published
2024
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5. Computational-level Analysis of Constraint Compliance for General Intelligence

Author

Wray, Robert E., Jones, Steven J., and Laird, John E.

Subjects
Computer Science - Artificial Intelligence, I.2.0, I.2.8
Abstract

Human behavior is conditioned by codes and norms that constrain action. Rules, ``manners,'' laws, and moral imperatives are examples of classes of constraints that govern human behavior. These systems of constraints are "messy:" individual constraints are often poorly defined, what constraints are relevant in a particular situation may be unknown or ambiguous, constraints interact and conflict with one another, and determining how to act within the bounds of the relevant constraints may be a significant challenge, especially when rapid decisions are needed. Despite such messiness, humans incorporate constraints in their decisions robustly and rapidly. General, artificially-intelligent agents must also be able to navigate the messiness of systems of real-world constraints in order to behave predictability and reliably. In this paper, we characterize sources of complexity in constraint processing for general agents and describe a computational-level analysis for such constraint compliance. We identify key algorithmic requirements based on the computational-level analysis and outline an initial, exploratory implementation of a general approach to constraint compliance., Comment: 10 pages, 2 figures. Accepted for presentation at AGI 2023. Corrected author list (segmented list) and abstract text artifacts

Published
2023

7. macroH2A2 antagonizes epigenetic programs of stemness in glioblastoma

Author

Nikolic, Ana, Maule, Francesca, Bobyn, Anna, Ellestad, Katrina, Paik, Seungil, Marhon, Sajid A., Mehdipour, Parinaz, Lun, Xueqing, Chen, Huey-Miin, Mallard, Claire, Hay, Alexander J., Johnston, Michael J., Gafuik, Christopher J., Zemp, Franz J., Shen, Yaoqing, Ninkovic, Nicoletta, Osz, Katalin, Labit, Elodie, Berger, N. Daniel, Brownsey, Duncan K., Kelly, John J., Biernaskie, Jeff, Dirks, Peter B., Derksen, Darren J., Jones, Steven J. M., Senger, Donna L., Chan, Jennifer A., Mahoney, Douglas J., De Carvalho, Daniel D., and Gallo, Marco

Published
2023
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9. Homologous recombination deficiency signatures in gastrointestinal and thoracic cancers correlate with platinum therapy duration

Author

Tsang, Erica S., Csizmok, Veronika, Williamson, Laura M., Pleasance, Erin, Topham, James T., Karasinska, Joanna M., Titmuss, Emma, Schrader, Intan, Yip, Stephen, Tessier-Cloutier, Basile, Mungall, Karen, Ng, Tony, Sun, Sophie, Lim, Howard J., Loree, Jonathan M., Laskin, Janessa, Marra, Marco A., Jones, Steven J. M., Schaeffer, David F., and Renouf, Daniel J.

Published
2023
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10. Modeling the Remote Associates Test as Retrievals from Semantic Memory

Author

Schatz, Jule, Jones, Steven J., and Laird, John E.

Abstract

The Remote Associates Test (RAT) is a word association retrieval task that consists of a series of problems, each with three seemingly unrelated prompt words. The subject is asked to produce a single word that is related to all three prompt words. In this paper, we provide support for a theory in which the RAT assesses a person's ability to retrieve relevant word associations from long-term memory. We present a computational model of humans solving the RAT and investigate how prior knowledge and memory retrieval mechanisms influence the model's ability to match human behavior. We expand prior modeling attempts by investigating multiple large knowledge bases and by creating a cognitive process model that uses long-term memory spreading activation retrieval processes inspired by ACT-R and implemented in Soar. We evaluate multiple model variants for their ability to model human problem difficulty, including the incorporation of noise and base-level activation into memory retrieval. We conclude that the main factors affecting human difficulty are the existence of associations between prompt words and solutions, the relative strengths and directions of those associations compared to associations to other words, and the ability to perform multiple retrievals.

Published
2022
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13. Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer Learning

Author

Wang, Yiping, Farnell, David, Farahani, Hossein, Nursey, Mitchell, Tessier-Cloutier, Basile, Jones, Steven J. M., Huntsman, David G., Gilks, C. Blake, and Bashashati, Ali

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Ovarian cancer is the most lethal cancer of the female reproductive organs. There are $5$ major histological subtypes of epithelial ovarian cancer, each with distinct morphological, genetic, and clinical features. Currently, these histotypes are determined by a pathologist's microscopic examination of tumor whole-slide images (WSI). This process has been hampered by poor inter-observer agreement (Cohen's kappa $0.54$-$0.67$). We utilized a \textit{two}-stage deep transfer learning algorithm based on convolutional neural networks (CNN) and progressive resizing for automatic classification of epithelial ovarian carcinoma WSIs. The proposed algorithm achieved a mean accuracy of $87.54\%$ and Cohen's kappa of $0.8106$ in the slide-level classification of $305$ WSIs; performing better than a standard CNN and pathologists without gynecology-specific training.

Published
2020

14. The transcriptional landscape of Shh medulloblastoma.

Author

Skowron, Patryk, Farooq, Hamza, Cavalli, Florence MG, Morrissy, A Sorana, Ly, Michelle, Hendrikse, Liam D, Wang, Evan Y, Djambazian, Haig, Zhu, Helen, Mungall, Karen L, Trinh, Quang M, Zheng, Tina, Dai, Shizhong, Stucklin, Ana S Guerreiro, Vladoiu, Maria C, Fong, Vernon, Holgado, Borja L, Nor, Carolina, Wu, Xiaochong, Abd-Rabbo, Diala, Bérubé, Pierre, Wang, Yu Chang, Luu, Betty, Suarez, Raul A, Rastan, Avesta, Gillmor, Aaron H, Lee, John JY, Zhang, Xiao Yun, Daniels, Craig, Dirks, Peter, Malkin, David, Bouffet, Eric, Tabori, Uri, Loukides, James, Doz, François P, Bourdeaut, Franck, Delattre, Olivier O, Masliah-Planchon, Julien, Ayrault, Olivier, Kim, Seung-Ki, Meyronet, David, Grajkowska, Wieslawa A, Carlotti, Carlos G, de Torres, Carmen, Mora, Jaume, Eberhart, Charles G, Van Meir, Erwin G, Kumabe, Toshihiro, French, Pim J, Kros, Johan M, Jabado, Nada, Lach, Boleslaw, Pollack, Ian F, Hamilton, Ronald L, Rao, Amulya A Nageswara, Giannini, Caterina, Olson, James M, Bognár, László, Klekner, Almos, Zitterbart, Karel, Phillips, Joanna J, Thompson, Reid C, Cooper, Michael K, Rubin, Joshua B, Liau, Linda M, Garami, Miklós, Hauser, Peter, Li, Kay Ka Wai, Ng, Ho-Keung, Poon, Wai Sang, Yancey Gillespie, G, Chan, Jennifer A, Jung, Shin, McLendon, Roger E, Thompson, Eric M, Zagzag, David, Vibhakar, Rajeev, Ra, Young Shin, Garre, Maria Luisa, Schüller, Ulrich, Shofuda, Tomoko, Faria, Claudia C, López-Aguilar, Enrique, Zadeh, Gelareh, Hui, Chi-Chung, Ramaswamy, Vijay, Bailey, Swneke D, Jones, Steven J, Mungall, Andrew J, Moore, Richard A, Calarco, John A, Stein, Lincoln D, Bader, Gary D, Reimand, Jüri, Ragoussis, Jiannis, Weiss, William A, Marra, Marco A, Suzuki, Hiromichi, and Taylor, Michael D

Subjects
Humans, Medulloblastoma, Cerebellar Neoplasms, Signal Transduction, Gene Expression Regulation, Neoplastic, Adolescent, Adult, Middle Aged, Child, Child, Preschool, Infant, Female, Male, Hedgehog Proteins, Gene Regulatory Networks, Genetic Variation, Young Adult, Transcriptome, Pediatric Research Initiative, Brain Cancer, Pediatric, Rare Diseases, Genetics, Pediatric Cancer, Clinical Research, Brain Disorders, Neurosciences, Biotechnology, Human Genome, Cancer, 2.1 Biological and endogenous factors
Abstract

Sonic hedgehog medulloblastoma encompasses a clinically and molecularly diverse group of cancers of the developing central nervous system. Here, we use unbiased sequencing of the transcriptome across a large cohort of 250 tumors to reveal differences among molecular subtypes of the disease, and demonstrate the previously unappreciated importance of non-coding RNA transcripts. We identify alterations within the cAMP dependent pathway (GNAS, PRKAR1A) which converge on GLI2 activity and show that 18% of tumors have a genetic event that directly targets the abundance and/or stability of MYCN. Furthermore, we discover an extensive network of fusions in focally amplified regions encompassing GLI2, and several loss-of-function fusions in tumor suppressor genes PTCH1, SUFU and NCOR1. Molecular convergence on a subset of genes by nucleotide variants, copy number aberrations, and gene fusions highlight the key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma and open up opportunities for therapeutic intervention.

Published
2021

16. An associative learning account for retrieval-induced forgetting

Author

Hiatt, Laura M. and Jones, Steven J.

Subjects
associative learning, spreading activation, prim-ing, cognitive architecture, retrieval-induced forgetting
Abstract

Retrieval-induced forgetting (RIF) is a paradigm where re-peated study and cue-based retrieval of words impair retrievalof related, but unstudied, words. We present a process model,situated in the ACT-R/E cognitive architecture, that accountsfor the RIF task using the architecture’s overarching theory ofassociative learning. In this theory, studying words strengthenstheir association with their related cues; this, in turn, weakensthe association between those cues and any other words theyare related to. We show this account fits a recent dataset thatexplores cueing in the RIF task (Perfect et al., 2004).

Published
2020

18. Failure of human rhombic lip differentiation underlies medulloblastoma formation

Author

Hendrikse, Liam D., Haldipur, Parthiv, Saulnier, Olivier, Millman, Jake, Sjoboen, Alexandria H., Erickson, Anders W., Ong, Winnie, Gordon, Victor, Coudière-Morrison, Ludivine, Mercier, Audrey L., Shokouhian, Mohammad, Suárez, Raúl A., Ly, Michelle, Borlase, Stephanie, Scott, David S., Vladoiu, Maria C., Farooq, Hamza, Sirbu, Olga, Nakashima, Takuma, Nambu, Shohei, Funakoshi, Yusuke, Bahcheli, Alec, Diaz-Mejia, J. Javier, Golser, Joseph, Bach, Kathleen, Phuong-Bao, Tram, Skowron, Patryk, Wang, Evan Y., Kumar, Sachin A., Balin, Polina, Visvanathan, Abhirami, Lee, John J. Y., Ayoub, Ramy, Chen, Xin, Chen, Xiaodi, Mungall, Karen L., Luu, Betty, Bérubé, Pierre, Wang, Yu C., Pfister, Stefan M., Kim, Seung-Ki, Delattre, Olivier, Bourdeaut, Franck, Doz, François, Masliah-Planchon, Julien, Grajkowska, Wieslawa A., Loukides, James, Dirks, Peter, Fèvre-Montange, Michelle, Jouvet, Anne, French, Pim J., Kros, Johan M., Zitterbart, Karel, Bailey, Swneke D., Eberhart, Charles G., Rao, Amulya A. N., Giannini, Caterina, Olson, James M., Garami, Miklós, Hauser, Peter, Phillips, Joanna J., Ra, Young S., de Torres, Carmen, Mora, Jaume, Li, Kay K. W., Ng, Ho-Keung, Poon, Wai S., Pollack, Ian F., López-Aguilar, Enrique, Gillespie, G. Yancey, Van Meter, Timothy E., Shofuda, Tomoko, Vibhakar, Rajeev, Thompson, Reid C., Cooper, Michael K., Rubin, Joshua B., Kumabe, Toshihiro, Jung, Shin, Lach, Boleslaw, Iolascon, Achille, Ferrucci, Veronica, de Antonellis, Pasqualino, Zollo, Massimo, Cinalli, Giuseppe, Robinson, Shenandoah, Stearns, Duncan S., Van Meir, Erwin G., Porrati, Paola, Finocchiaro, Gaetano, Massimino, Maura, Carlotti, Carlos G., Faria, Claudia C., Roussel, Martine F., Boop, Frederick, Chan, Jennifer A., Aldinger, Kimberly A., Razavi, Ferechte, Silvestri, Evelina, McLendon, Roger E., Thompson, Eric M., Ansari, Marc, Garre, Maria L., Chico, Fernando, Eguía, Pilar, Pérezpeña, Mario, Morrissy, A. Sorana, Cavalli, Florence M. G., Wu, Xiaochong, Daniels, Craig, Rich, Jeremy N., Jones, Steven J. M., Moore, Richard A., Marra, Marco A., Huang, Xi, Reimand, Jüri, Sorensen, Poul H., Wechsler-Reya, Robert J., Weiss, William A., Pugh, Trevor J., Garzia, Livia, Kleinman, Claudia L., Stein, Lincoln D., Jabado, Nada, Malkin, David, Ayrault, Olivier, Golden, Jeffrey A., Ellison, David W., Doble, Brad, Ramaswamy, Vijay, Werbowetski-Ogilvie, Tamra E., Suzuki, Hiromichi, Millen, Kathleen J., and Taylor, Michael D.

Published
2022
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22. A community approach to the cancer-variant-interpretation bottleneck

Author

Krysiak, Kilannin, Danos, Arpad M., Kiwala, Susanna, McMichael, Joshua F., Coffman, Adam C., Barnell, Erica K., Sheta, Lana, Saliba, Jason, Grisdale, Cameron J., Kujan, Lynzey, Pema, Shahil, Lever, Jake, Spies, Nicholas C., Chiorean, Andreea, Rieke, Damian T., Clark, Kaitlin A., Jani, Payal, Takahashi, Hideaki, Horak, Peter, Ritter, Deborah I., Zhou, Xin, Ainscough, Benjamin J., Delong, Sean, Lamping, Mario, Marr, Alex R., Li, Brian V., Lin, Wan-Hsin, Terraf, Panieh, Salama, Yasser, Campbell, Katie M., Farncombe, Kirsten M., Ji, Jianling, Zhao, Xiaonan, Xu, Xinjie, Kanagal-Shamanna, Rashmi, Cotto, Kelsy C., Skidmore, Zachary L., Walker, Jason R., Zhang, Jinghui, Milosavljevic, Aleksandar, Patel, Ronak Y., Giles, Rachel H., Kim, Raymond H., Schriml, Lynn M., Mardis, Elaine R., Jones, Steven J. M., Raca, Gordana, Rao, Shruti, Madhavan, Subha, Wagner, Alex H., Griffith, Obi L., and Griffith, Malachi

Published
2022
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23. A platform for oncogenomic reporting and interpretation

Author

Reisle, Caralyn, Williamson, Laura M., Pleasance, Erin, Davies, Anna, Pellegrini, Brayden, Bleile, Dustin W., Mungall, Karen L., Chuah, Eric, Jones, Martin R., Ma, Yussanne, Lewis, Eleanor, Beckie, Isaac, Pham, David, Matiello Pletz, Raphael, Muhammadzadeh, Amir, Pierce, Brandon M., Li, Jacky, Stevenson, Ross, Wong, Hansen, Bailey, Lance, Reisle, Abbey, Douglas, Matthew, Bonakdar, Melika, Nelson, Jessica M. T., Grisdale, Cameron J., Krzywinski, Martin, Fisic, Ana, Mitchell, Teresa, Renouf, Daniel J., Yip, Stephen, Laskin, Janessa, Marra, Marco A., and Jones, Steven J. M.

Published
2022
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25. Integrative analysis of KRAS wildtype metastatic pancreatic ductal adenocarcinoma reveals mutation and expression-based similarities to cholangiocarcinoma

Author

Topham, James T., Tsang, Erica S., Karasinska, Joanna M., Metcalfe, Andrew, Ali, Hassan, Kalloger, Steve E., Csizmok, Veronika, Williamson, Laura M., Titmuss, Emma, Nielsen, Karina, Negri, Gian Luca, Spencer Miko, Sandra E., Jang, Gun Ho, Denroche, Robert E., Wong, Hui-li, O’Kane, Grainne M., Moore, Richard A., Mungall, Andrew J., Loree, Jonathan M., Notta, Faiyaz, Wilson, Julie M., Bathe, Oliver F., Tang, Patricia A., Goodwin, Rachel, Morin, Gregg B., Knox, Jennifer J., Gallinger, Steven, Laskin, Janessa, Marra, Marco A., Jones, Steven J. M., Schaeffer, David F., and Renouf, Daniel J.

Published
2022
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27. Enhancing clinical genomic accuracy with panelGC: a novel metric and tool for quantifying and monitoring GC biases in hybridization capture panel sequencing.

Author

Cheng, Xuanjin, Goktas, Murathan T, Williamson, Laura M, Krzywinski, Martin, Mulder, David T, Swanson, Lucas, Slind, Jill, Sihvonen, Jelena, Chow, Cynthia R, Carr, Amy, Bosdet, Ian, Tucker, Tracy, Young, Sean, Moore, Richard, Mungall, Karen L, Yip, Stephen, and Jones, Steven J M

Subjects
POLYMERASE chain reaction, QUALITY control, CLINICAL medicine, GENOMICS, GENOMES
Abstract

Accurate assessment of fragment abundance within a genome is crucial in clinical genomics applications such as the analysis of copy number variation (CNV). However, this task is often hindered by biased coverage in regions with varying guanine–cytosine (GC) content. These biases are particularly exacerbated in hybridization capture sequencing due to GC effects on probe hybridization and polymerase chain reaction (PCR) amplification efficiency. Such GC content–associated variations can exert a negative impact on the fidelity of CNV calling within hybridization capture panels. In this report, we present panelGC, a novel metric, to quantify and monitor GC biases in hybridization capture sequencing data. We establish the efficacy of panelGC, demonstrating its proficiency in identifying and flagging potential procedural anomalies, even in situations where instrument and experimental monitoring data may not be readily accessible. Validation using real-world datasets demonstrates that panelGC enhances the quality control and reliability of hybridization capture panel sequencing. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Megastudies improve the impact of applied behavioural science

Author

Milkman, Katherine L., Gromet, Dena, Ho, Hung, Kay, Joseph S., Lee, Timothy W., Pandiloski, Pepi, Park, Yeji, Rai, Aneesh, Bazerman, Max, Beshears, John, Bonacorsi, Lauri, Camerer, Colin, Chang, Edward, Chapman, Gretchen, Cialdini, Robert, Dai, Hengchen, Eskreis-Winkler, Lauren, Fishbach, Ayelet, Gross, James J., Horn, Samantha, Hubbard, Alexa, Jones, Steven J., Karlan, Dean, Kautz, Tim, Kirgios, Erika, Klusowski, Joowon, Kristal, Ariella, Ladhania, Rahul, Loewenstein, George, Ludwig, Jens, Mellers, Barbara, Mullainathan, Sendhil, Saccardo, Silvia, Spiess, Jann, Suri, Gaurav, Talloen, Joachim H., Taxer, Jamie, Trope, Yaacov, Ungar, Lyle, Volpp, Kevin G., Whillans, Ashley, Zinman, Jonathan, and Duckworth, Angela L.

Published
2021
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29. Exploration of Germline Correlates and Risk of Immune-Related Adverse Events in Advanced Cancer Patients Treated with Immune Checkpoint Inhibitors

Author

Titmuss, Emma, primary, Yu, Irene S., additional, Pleasance, Erin D., additional, Williamson, Laura M., additional, Mungall, Karen, additional, Mungall, Andrew J., additional, Renouf, Daniel J., additional, Moore, Richard, additional, Jones, Steven J. M., additional, Marra, Marco A., additional, Laskin, Janessa J., additional, and Savage, Kerry J., additional

Published
2024
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31. New class of compounds - variators - are reprogramming substrate specificity of H4K12Ac, H4K16Ac and H4K20Ac epigenetic marks reading bromodomain of BPTF protein

Author

Yakovenko, Oleksandr Ya, Leelakumari, Sreeja, Vashchenko, Ganna, Badiong, Albert, and Jones, Steven J. M.

Subjects
Quantitative Biology - Biomolecules
Abstract

Previously reported [http://arxiv.org/abs/1506.06433] reprogramming of substrate specificity of H3K4Me3 epigenetic marks reading PHD domain of BPTF protein illustrates therapeutic potential of a new class of non-inhibitor small organic compounds - variators. Here we address the question about reproducibility of rational design of variators by reprogramming of the second epigenetic marks reading domain of BPTF protein - bromodomain. Bromodomain of BPTF binds to epigenetic marks in form of acetylated lysine of histone H4 (H4K12Ac, H4K16Ac and H4K20Ac), which physicochemical properties and binding mode differs considerably from those of methylated H3K4 marks. Thus, detailed description of computational approach for reprogramming of bromodomain substrate specificity illustrates both general and target specific attributes of computer aided variators design., Comment: 13 pages 1 figure. The paper is about the second example of developing of protein reprogramming compounds to illustrate systematic and reproducible approach for their rational design. arXiv admin note: substantial text overlap with arXiv:1506.06433

Published
2015

32. New class of compounds - variators - are reprogramming substrate specificity of H3K4me3 epigenetic marks reading PHD domain of BPTF protein

Author

Yakovenko, Oleksandr Ya, Leelakumari, Sreeja, Vashchenko, Ganna, Cheung, Pierre, Badiong, Albert, and Jones, Steven J. M.

Subjects
Quantitative Biology - Biomolecules
Abstract

In lymphoma, mutations in genes of histone modifying proteins are frequently observed. Notably, somatic mutations in the activatory histone modification writing protein MLL2 and the repressive modification writer EZH2 are the most frequent. Gain of function mutations are typically detected in EZH2 whilst MLL2 mutations are usually observed as conferring a homozygous loss of function. The gain-of-function mutations in EZH2 provide an obvious target for the development of inhibitors with therapeutic potential. To counter the loss of functional MLL2 protein, we computationally predicted compounds that are able to modulate the reader of the corresponding modifications, BPTF, to recognize other forms of the histone H3 lysine 4, instead of the tri-methylated form normally produced by MLL2. By forming a synthetic triple-complex of a compound, the histone H3 tail and BPTF we potentially circumvent the requirement for functional MLL2 methyl-transferase through the modulation of BPTF activity. Here we show a proof-of-principle that special compounds, named variators, can reprogram selectivity of protein binding and thus create artificial regulatory pathways which can have a potential therapeutic role. A therapeutic role of BPTF variators may extend to other diseases that involve loss of MLL2 function, such as Kabuki syndrome or the aberrant functioning of H3K4 modification as observed in Huntington disease and in memory formation., Comment: 11 pages, 3 figures. The paper describes rational design of new class of drug molecules - variators - that do not inhibit but modulate behaviour of proteins. With variators of PHD finger domain of BPTF protein we have compensated for loss-of-function mutations in MLL2 gene and the absence of H3K4me3 activating epigenetic marks which is frequently observed in lymphoma

Published
2015

33. Author Correction: Failure of human rhombic lip differentiation underlies medulloblastoma formation

Author

Hendrikse, Liam D., Haldipur, Parthiv, Saulnier, Olivier, Millman, Jake, Sjoboen, Alexandria H., Erickson, Anders W., Ong, Winnie, Gordon, Victor, Coudière-Morrison, Ludivine, Mercier, Audrey L., Shokouhian, Mohammad, Suárez, Raúl A., Ly, Michelle, Borlase, Stephanie, Scott, David S., Vladoiu, Maria C., Farooq, Hamza, Sirbu, Olga, Nakashima, Takuma, Nambu, Shohei, Funakoshi, Yusuke, Bahcheli, Alec, Diaz-Mejia, J. Javier, Golser, Joseph, Bach, Kathleen, Phuong-Bao, Tram, Skowron, Patryk, Wang, Evan Y., Kumar, Sachin A., Balin, Polina, Visvanathan, Abhirami, Lee, John J. Y., Ayoub, Ramy, Chen, Xin, Chen, Xiaodi, Mungall, Karen L., Luu, Betty, Bérubé, Pierre, Wang, Yu C., Pfister, Stefan M., Kim, Seung-Ki, Delattre, Olivier, Bourdeaut, Franck, Doz, François, Masliah-Planchon, Julien, Grajkowska, Wieslawa A., Loukides, James, Dirks, Peter, Fèvre-Montange, Michelle, Jouvet, Anne, French, Pim J., Kros, Johan M., Zitterbart, Karel, Bailey, Swneke D., Eberhart, Charles G., Rao, Amulya A. N., Giannini, Caterina, Olson, James M., Garami, Miklós, Hauser, Peter, Phillips, Joanna J., Ra, Young S., de Torres, Carmen, Mora, Jaume, Li, Kay K. W., Ng, Ho-Keung, Poon, Wai S., Pollack, Ian F., López-Aguilar, Enrique, Gillespie, G. Yancey, Van Meter, Timothy E., Shofuda, Tomoko, Vibhakar, Rajeev, Thompson, Reid C., Cooper, Michael K., Rubin, Joshua B., Kumabe, Toshihiro, Jung, Shin, Lach, Boleslaw, Iolascon, Achille, Ferrucci, Veronica, de Antonellis, Pasqualino, Zollo, Massimo, Cinalli, Giuseppe, Robinson, Shenandoah, Stearns, Duncan S., Van Meir, Erwin G., Porrati, Paola, Finocchiaro, Gaetano, Massimino, Maura, Carlotti, Carlos G., Faria, Claudia C., Roussel, Martine F., Boop, Frederick, Chan, Jennifer A., Aldinger, Kimberly A., Razavi, Ferechte, Silvestri, Evelina, McLendon, Roger E., Thompson, Eric M., Ansari, Marc, Garre, Maria L., Chico, Fernando, Eguía, Pilar, Pérezpeña, Mario, Morrissy, A. Sorana, Cavalli, Florence M. G., Wu, Xiaochong, Daniels, Craig, Rich, Jeremy N., Jones, Steven J. M., Moore, Richard A., Marra, Marco A., Huang, Xi, Reimand, Jüri, Sorensen, Poul H., Wechsler-Reya, Robert J., Weiss, William A., Pugh, Trevor J., Garzia, Livia, Kleinman, Claudia L., Stein, Lincoln D., Jabado, Nada, Malkin, David, Ayrault, Olivier, Golden, Jeffrey A., Ellison, David W., Doble, Brad, Ramaswamy, Vijay, Werbowetski-Ogilvie, Tamra E., Suzuki, Hiromichi, Millen, Kathleen J., and Taylor, Michael D.

Published
2022
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35. Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments

Author

Shen, Yaoqing, Grisdale, Cameron J., Islam, Sumaiya A., Bose, Pinaki, Lever, Jake, Zhao, Eric Y., Grinshtein, Natalie, Ma, Yussanne, Mungall, Andrew J., Moore, Richard A., Lun, Xueqing, Senger, Donna L., Robbins, Stephen M., Wang, Alice Yijun, MacIsaac, Julia L., Kobor, Michael S., Luchman, H. Artee, Weiss, Samuel, Chan, Jennifer A., Blough, Michael D., Kaplan, David R., Cairncross, J. Gregory, Marra, Marco A., and Jones, Steven J. M.

Published
2019

37. A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia

Author

Docking, T. Roderick, Parker, Jeremy D. K., Jädersten, Martin, Duns, Gerben, Chang, Linda, Jiang, Jihong, Pilsworth, Jessica A., Swanson, Lucas A., Chan, Simon K., Chiu, Readman, Nip, Ka Ming, Mar, Samantha, Mo, Angela, Wang, Xuan, Martinez-Høyer, Sergio, Stubbins, Ryan J., Mungall, Karen L., Mungall, Andrew J., Moore, Richard A., Jones, Steven J. M., Birol, İnanç, Marra, Marco A., Hogge, Donna, and Karsan, Aly

Published
2021
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38. Clinical response to nivolumab in an INI1-deficient pediatric chordoma correlates with immunogenic recognition of brachyury

Author

Williamson, Laura M., Rive, Craig M., Di Francesco, Daniela, Titmuss, Emma, Chun, Hye-Jung E., Brown, Scott D., Milne, Katy, Pleasance, Erin, Lee, Anna F., Yip, Stephen, Rosenbaum, Daniel G., Hasselblatt, Martin, Johann, Pascal D., Kool, Marcel, Harvey, Melissa, Dix, David, Renouf, Daniel J., Holt, Robert A., Nelson, Brad H., Hirst, Martin, Jones, Steven J. M., Laskin, Janessa, Rassekh, Shahrad R., Deyell, Rebecca J., and Marra, Marco A.

Published
2021
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39. Improved structural variant interpretation for hereditary cancer susceptibility using long-read sequencing

Author

Thibodeau, My Linh, O’Neill, Kieran, Dixon, Katherine, Reisle, Caralyn, Mungall, Karen L., Krzywinski, Martin, Shen, Yaoqing, Lim, Howard J., Cheng, Dean, Tse, Kane, Wong, Tina, Chuah, Eric, Fok, Alexandra, Sun, Sophie, Renouf, Daniel, Schaeffer, David F., Cremin, Carol, Chia, Stephen, Young, Sean, Pandoh, Pawan, Pleasance, Stephen, Pleasance, Erin, Mungall, Andrew J., Moore, Richard, Yip, Stephen, Karsan, Aly, Laskin, Janessa, Marra, Marco A., Schrader, Kasmintan A., and Jones, Steven J. M.

Published
2020
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41. Analysis of Ugandan cervical carcinomas identifies human papillomavirus clade–specific epigenome and transcriptome landscapes

Author

Gagliardi, Alessia, Porter, Vanessa L., Zong, Zusheng, Bowlby, Reanne, Titmuss, Emma, Namirembe, Constance, Griner, Nicholas B., Petrello, Hilary, Bowen, Jay, Chan, Simon K., Culibrk, Luka, Darragh, Teresa M., Stoler, Mark H., Wright, Thomas C., Gesuwan, Patee, Dyer, Maureen A., Ma, Yussanne, Mungall, Karen L., Jones, Steven J. M., Nakisige, Carolyn, Novik, Karen, Orem, Jackson, Origa, Martin, Gastier-Foster, Julie M., Yarchoan, Robert, Casper, Corey, Mills, Gordon B., Rader, Janet S., Ojesina, Akinyemi I., Gerhard, Daniela S., Mungall, Andrew J., and Marra, Marco A.

Published
2020
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42. RETRACTED ARTICLE: Tumor necrosis factor overcomes immune evasion in p53-mutant medulloblastoma

Author

Garancher, Alexandra, Suzuki, Hiromichi, Haricharan, Svasti, Chau, Lianne Q., Masihi, Meher Beigi, Rusert, Jessica M., Norris, Paula S., Carrette, Florent, Romero, Megan M., Morrissy, Sorana A., Skowron, Patryk, Cavalli, Florence M. G., Farooq, Hamza, Ramaswamy, Vijay, Jones, Steven J. M., Moore, Richard A., Mungall, Andrew J., Ma, Yussanne, Thiessen, Nina, Li, Yisu, Morcavallo, Alaide, Qi, Lin, Kogiso, Mari, Du, Yuchen, Baxter, Patricia, Henderson, Jacob J., Crawford, John R., Levy, Michael L., Olson, James M., Cho, Yoon-Jae, Deshpande, Aniruddha J., Li, Xiao-Nan, Chesler, Louis, Marra, Marco A., Wajant, Harald, Becher, Oren J., Bradley, Linda M., Ware, Carl F., Taylor, Michael D., and Wechsler-Reya, Robert J.

Published
2020
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43. KiWi: A Scalable Subspace Clustering Algorithm for Gene Expression Analysis

Author

Griffith, Obi L., Gao, Byron J., Bilenky, Mikhail, Prichyna, Yuliya, Ester, Martin, and Jones, Steven J. M.

Subjects
Computer Science - Databases, Computer Science - Artificial Intelligence, Quantitative Biology - Genomics
Abstract

Subspace clustering has gained increasing popularity in the analysis of gene expression data. Among subspace cluster models, the recently introduced order-preserving sub-matrix (OPSM) has demonstrated high promise. An OPSM, essentially a pattern-based subspace cluster, is a subset of rows and columns in a data matrix for which all the rows induce the same linear ordering of columns. Existing OPSM discovery methods do not scale well to increasingly large expression datasets. In particular, twig clusters having few genes and many experiments incur explosive computational costs and are completely pruned off by existing methods. However, it is of particular interest to determine small groups of genes that are tightly coregulated across many conditions. In this paper, we present KiWi, an OPSM subspace clustering algorithm that is scalable to massive datasets, capable of discovering twig clusters and identifying negative as well as positive correlations. We extensively validate KiWi using relevant biological datasets and show that KiWi correctly assigns redundant probes to the same cluster, groups experiments with common clinical annotations, differentiates real promoter sequences from negative control sequences, and shows good association with cis-regulatory motif predictions., Comment: International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2009

Published
2009

44. Canadian COVID-19 host genetics cohort replicates known severity associations.

Author

Garg, Elika, Arguello-Pascualli, Paola, Vishnyakova, Olga, Halevy, Anat R., Yoo, Samantha, Brooks, Jennifer D., Bull, Shelley B., Gagnon, France, Greenwood, Celia M. T., Hung, Rayjean J., Lawless, Jerald F., Lerner-Ellis, Jordan, Dennis, Jessica K., Abraham, Rohan J. S., Garant, Jean-Michel, Thiruvahindrapuram, Bhooma, Jones, Steven J. M., Strug, Lisa J., Paterson, Andrew D., and Sun, Lei

Abstract

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation. Author summary: Host genetics determine how human genetics contribute to the response to infectious disease. HostSeq is a Canada-wide effort to contribute to our understanding of host genetics for COVID-19. The HostSeq study involves genetic and clinical data from individuals who tested positive for SARS-CoV-2 across Canada. This work examines locations in the human genome that have been reported to be involved in severe COVID-19 worldwide and determines if we also see the involvement of those genomic locations in Canadians. This work also explores several 'genetic quantities' such as a determination of how much of COVID-19 severity is due to genetics in Canada. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Genomic structures and regulation patterns at HPV integration sites in cervical cancer

Author

Porter, Vanessa L., primary, O’Neill, Kieran, additional, MacLennan, Signe, additional, Corbett, Richard D., additional, Ng, Michelle, additional, Culibrk, Luka, additional, Hamadeh, Zeid, additional, Iden, Marissa, additional, Schmidt, Rachel, additional, Tsaih, Shirng-Wern, additional, Chang, Glenn, additional, Fan, Jeremy, additional, Nip, Ka Ming, additional, Akbari, Vahid, additional, Chan, Simon K., additional, Hopkins, James, additional, Moore, Richard A., additional, Chuah, Eric, additional, Mungall, Karen L., additional, Mungall, Andrew J., additional, Birol, Inanc, additional, Jones, Steven J. M., additional, Rader, Janet S., additional, and Marra, Marco A., additional

Published
2023
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46. Assembly and annotation of the black spruce genome provide insights on spruce phylogeny and evolution of stress response

Author

Lo, Theodora, primary, Coombe, Lauren, additional, Gagalova, Kristina K, additional, Marr, Alex, additional, Warren, René L, additional, Kirk, Heather, additional, Pandoh, Pawan, additional, Zhao, Yongjun, additional, Moore, Richard A, additional, Mungall, Andrew J, additional, Ritland, Carol, additional, Pavy, Nathalie, additional, Jones, Steven J M, additional, Bohlmann, Joerg, additional, Bousquet, Jean, additional, Birol, Inanç, additional, and Thomson, Ashley, additional

Published
2023
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48. Retraction Note: Tumor necrosis factor overcomes immune evasion in p53-mutant medulloblastoma

Author

Garancher, Alexandra, Suzuki, Hiromichi, Haricharan, Svasti, Chau, Lianne Q., Masihi, Meher Beigi, Rusert, Jessica M., Norris, Paula S., Carrette, Florent, Romero, Megan M., Morrissy, Sorana A., Skowron, Patryk, Cavalli, Florence M. G., Farooq, Hamza, Ramaswamy, Vijay, Jones, Steven J. M., Moore, Richard A., Mungall, Andrew J., Ma, Yussanne, Thiessen, Nina, Li, Yisu, Morcavallo, Alaide, Qi, Lin, Kogiso, Mari, Du, Yuchen, Baxter, Patricia, Henderson, Jacob J., Crawford, John R., Levy, Michael L., Olson, James M., Cho, Yoon-Jae, Deshpande, Aniruddha J., Li, Xiao-Nan, Chesler, Louis, Marra, Marco A., Wajant, Harald, Becher, Oren J., Bradley, Linda M., Ware, Carl F., Taylor, Michael D., and Wechsler-Reya, Robert J.

Published
2022
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49. Clonal expansion and epigenetic reprogramming following deletion or amplification of mutant IDH1

Author

Mazor, Tali, Chesnelong, Charles, Pankov, Aleksandr, Jalbert, Llewellyn E., Hong, Chibo, Hayes, Josie, Smirnov, Ivan V., Marshall, Roxanne, Souza, Camila F., Shen, Yaoqing, Viswanath, Pavithra, Noushmehr, Houtan, Ronen, Sabrina M., Jones, Steven J. M., Marra, Marco A., Cairncross, J. Gregory, Perry, Arie, Nelson, Sarah J., Chang, Susan M., Bollen, Andrew W., Molinaro, Annette M., Bengtsson, Henrik, Olshen, Adam B., Weiss, Samuel, Phillips, Joanna J., Luchman, H. Artee, and Costello, Joseph F.

Published
2017

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