Menu Close

Publications

Recent Publications

The list below displays 20 of our most recent publications.

  1. Bhola, PT, Marshall, AE, Liang, Y, Couse, M, Wang, X, Miller, E, Morel, CF, Boycott, KM, Kernohan, KD. RNA sequencing to support intronic variant interpretation: A case report of TRAPPC12-related disorder. Am J Med Genet A. 2023; :. doi: 10.1002/ajmg.a.63184.
  2. Deshwar, AR, Yuki, KE, Hou, H, Liang, Y, Khan, T, Celik, A, Ramani, A, Mendoza-Londono, R, Marshall, CR, Brudno, M, Shlien, A, Meyn, MS, Hayeems, RZ, McKinlay, BJ, Klentrou, P, Wilson, MD, Kyriakopoulou, L, Costain, G, Dowling, JJ. Trio RNA sequencing in a cohort of medically complex children. Am J Hum Genet. 2023; :. doi: 10.1016/j.ajhg.2023.03.006.
  3. Ivanics, T, So, D, Claasen, MPAW, Wallace, D, Patel, MS, Gravely, A, Choi, WJ, Shwaartz, C, Walker, K, Erdman, L, Sapisochin, G. Machine learning-based mortality prediction models using national liver transplantation registries are feasible but have limited utility across countries. Am J Transplant. 2023;23 (1):64-71. doi: 10.1016/j.ajt.2022.12.002.
  4. Sokolowski, DJ, Ahn, J, Erdman, L, Hou, H, Ellis, K, Wang, L, Goldenberg, A, Wilson, MD. Differential Expression Enrichment Tool (DEET): an interactive atlas of human differential gene expression. NAR Genom Bioinform. 2023;5 (1):lqad003. doi: 10.1093/nargab/lqad003.
  5. Christensen, E, Luo, P, Turinsky, A, Husić, M, Mahalanabis, A, Naidas, A, Diaz-Mejia, JJ, Brudno, M, Pugh, T, Ramani, A, Shooshtari, P. Evaluation of single-cell RNAseq labelling algorithms using cancer datasets. Brief Bioinform. 2023;24 (1):. doi: 10.1093/bib/bbac561.
  6. Villani, A, Davidson, S, Kanwar, N, Lo, WW, Li, Y, Cohen-Gogo, S, Fuligni, F, Edward, LM, Light, N, Layeghifard, M, Harripaul, R, Waldman, L, Gallinger, B, Comitani, F, Brunga, L, Hayes, R, Anderson, ND, Ramani, AK, Yuki, KE, Blay, S, Johnstone, B, Inglese, C, Hammad, R, Goudie, C, Shuen, A, Wasserman, JD, Venier, RE, Eliou, M, Lorenti, M, Ryan, CA, Braga, M, Gloven-Brown, M, Han, J, Montero, M, Spatare, F, Whitlock, JA, Scherer, SW, Chun, K, Somerville, MJ, Hawkins, C, Abdelhaleem, M, Ramaswamy, V, Somers, GR, Kyriakopoulou, L, Hitzler, J, Shago, M, Morgenstern, DA, Tabori, U, Meyn, S, Irwin, MS, Malkin, D, Shlien, A. The clinical utility of integrative genomics in childhood cancer extends beyond targetable mutations. Nat Cancer. 2023;4 (2):203-221. doi: 10.1038/s43018-022-00474-y.
  7. Mahalanabis, A, Turinsky, AL, Husić, M, Christensen, E, Luo, P, Naidas, A, Brudno, M, Pugh, T, Ramani, AK, Shooshtari, P. Evaluation of single-cell RNA-seq clustering algorithms on cancer tumor datasets. Comput Struct Biotechnol J. 2022;20 :6375-6387. doi: 10.1016/j.csbj.2022.10.029.
  8. Barraclough, M, Erdman, L, Diaz-Martinez, JP, Knight, A, Bingham, K, Su, J, Kakvan, M, Muñoz Grajales, C, Tartaglia, MC, Ruttan, L, Wither, J, Choi, MY, Bonilla, D, Appenzeller, S, Parker, B, Goldenberg, A, Katz, P, Beaton, D, Green, R, Bruce, IN, Touma, Z. Systemic lupus erythematosus phenotypes formed from machine learning with a specific focus on cognitive impairment. Rheumatology (Oxford). 2022; :. doi: 10.1093/rheumatology/keac653.
  9. Misztal, MC, Liao, F, Couse, M, Cao, J, Dominguez, D, Lau, L, Marshall, CR, Naumenko, S, Knight, AM, Levy, DM, Hiraki, LT. Genome-Wide Sequencing Identified Rare Genetic Variants for Childhood-Onset Monogenic Lupus. J Rheumatol. 2022; :. doi: 10.3899/jrheum.220513.
  10. Hung, L, Celik, A, Yin, X, Yu, K, Berenjy, A, Kothari, A, Obernolte, H, Upton, JEM, Lindholm Bøgh, K, Somers, GR, Siddiqui, I, Grealish, M, Quereshy, FA, Sewald, K, Chiu, PPL, Eiwegger, T. Precision cut intestinal slices, a novel model of acute food allergic reactions. Allergy. 2023;78 (2):500-511. doi: 10.1111/all.15579.
  11. Awamleh, Z, Goodman, S, Kallurkar, P, Wu, W, Lu, K, Choufani, S, Turinsky, AL, Weksberg, R. Generation of DNA Methylation Signatures and Classification of Variants in Rare Neurodevelopmental Disorders Using EpigenCentral. Curr Protoc. 2022;2 (11):e597. doi: 10.1002/cpz1.597.
  12. Hartley, T, Soubry, É, Acker, M, Osmond, M, Couse, M, Gillespie, MK, Ito, Y, Marshall, AE, Lemire, G, Huang, L, Chisholm, C, Eaton, AJ, Price, EM, Dowling, JJ, Ramani, AK, Mendoza-Londono, R, Costain, G, Axford, MM, Szuto, A, McNiven, V, Damseh, N, Jobling, R, de Kock, L, Mojarad, BA, Young, T, Shao, Z, Hayeems, RZ, Graham, ID, Tarnopolsky, M, Brady, L, Armour, CM, Geraghty, M, Richer, J, Sawyer, S, Lines, M, Mercimek-Andrews, S, Carter, MT, Graham, G, Kannu, P, Lazier, J, Li, C, Aul, RB, Balci, TB, Dlamini, N, Badalato, L, Guerin, A, Walia, J, Chitayat, D, Cohn, R, Faghfoury, H, Forster-Gibson, C, Gonorazky, H, Grunebaum, E, Inbar-Feigenberg, M, Karp, N, Morel, C, Rusnak, A, Sondheimer, N, Warman-Chardon, J, Bhola, PT, Bourque, DK, Chacon, IJ, Chad, L, Chakraborty, P, Chong, K, Doja, A, Goh, ES, Saleh, M, Care4Rare Canada, Potter, BK, Marshall, CR, Dyment, DA, Kernohan, K, Boycott, KM. Bridging clinical care and research in Ontario, Canada: Maximizing diagnoses from reanalysis of clinical exome sequencing data. Clin Genet. 2023;103 (3):288-300. doi: 10.1111/cge.14262.
  13. Piedimonte, S, Erdman, L, So, D, Bernardini, MQ, Ferguson, SE, Laframboise, S, Bouchard Fortier, G, Cybulska, P, May, T, Hogen, L. Using a machine learning algorithm to predict outcome of primary cytoreductive surgery in advanced ovarian cancer. J Surg Oncol. 2023;127 (3):465-472. doi: 10.1002/jso.27137.
  14. Celik, A, Somer, M, Kukreja, B, Wu, T, Kalish, BT. The Genomic Architecture of Pregnancy-Associated Plasticity in the Maternal Mouse Hippocampus. eNeuro. 2022;9 (5):. doi: 10.1523/ENEURO.0117-22.2022.
  15. Khondker, A, Kwong, JCC, Yadav, P, Chan, JYH, Singh, A, Skreta, M, Erdman, L, Keefe, DT, Fischer, K, Tasian, G, Hannick, JH, Papanikolaou, F, Cooper, BJ, Cooper, CS, Rickard, M, Lorenzo, AJ. Multi-institutional Validation of Improved Vesicoureteral Reflux Assessment With Simple and Machine Learning Approaches. J Urol. 2022;208 (6):1314-1322. doi: 10.1097/JU.0000000000002987.
  16. Kwong, JCC, Erdman, L, Khondker, A, Skreta, M, Goldenberg, A, McCradden, MD, Lorenzo, AJ, Rickard, M. The silent trial - the bridge between bench-to-bedside clinical AI applications. Front Digit Health. 2022;4 :929508. doi: 10.3389/fdgth.2022.929508.
  17. Ciftci Kavaklioglu, B, Erdman, L, Goldenberg, A, Kavaklioglu, C, Alexander, C, Oppermann, HM, Patel, A, Hossain, S, Berenbaum, T, Yau, O, Yea, C, Ly, M, Costello, F, Mah, JK, Reginald, A, Banwell, B, Longoni, G, Ann Yeh, E. Machine learning classification of multiple sclerosis in children using optical coherence tomography. Mult Scler. 2022;28 (14):2253-2262. doi: 10.1177/13524585221112605.
  18. Weaver, JK, Milford, K, Rickard, M, Logan, J, Erdman, L, Viteri, B, D'Souza, N, Cucchiara, A, Skreta, M, Keefe, D, Shah, S, Selman, A, Fischer, K, Weiss, DA, Long, CJ, Lorenzo, A, Fan, Y, Tasian, GE. Deep learning imaging features derived from kidney ultrasounds predict chronic kidney disease progression in children with posterior urethral valves. Pediatr Nephrol. 2023;38 (3):839-846. doi: 10.1007/s00467-022-05677-0.
  19. Volpatti, JR, Ghahramani-Seno, MM, Mansat, M, Sabha, N, Sarikaya, E, Goodman, SJ, Chater-Diehl, E, Celik, A, Pannia, E, Froment, C, Combes-Soia, L, Maani, N, Yuki, KE, Chicanne, G, Uusküla-Reimand, L, Monis, S, Alvi, SA, Genetti, CA, Payrastre, B, Beggs, AH, Bonnemann, CG, Muntoni, F, Wilson, MD, Weksberg, R, Viaud, J, Dowling, JJ. X-linked myotubular myopathy is associated with epigenetic alterations and is ameliorated by HDAC inhibition. Acta Neuropathol. 2022;144 (3):537-563. doi: 10.1007/s00401-022-02468-7.
  20. Mirchi, N, Warsi, NM, Zhang, F, Wong, SM, Suresh, H, Mithani, K, Erdman, L, Ibrahim, GM. Decoding Intracranial EEG With Machine Learning: A Systematic Review. Front Hum Neurosci. 2022;16 :913777. doi: 10.3389/fnhum.2022.913777.
Search PubMed