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  1. 1.   Sequencing-based functional assays for classification of BRCA2 variants in mouse ESCs
  2. Biswas,Kajal; Mitrophanov,Alex; Sahu,Sounak; Sullivan,Teresa; Southon,Eileen; Nousome,Darryl; Reid, Susan; Narula, Sakshi; Smolen, Julia; Sengupta, Trisha; Riedel-Topper, Maximilian; Kapoor, Medha; Babbar, Anav; Stauffer,Stacey; Cleveland, Linda; Tandon, Mayank; Malys,Tyler; Sharan,Shyam
  3. Cell Reports Methods. 2023, Nov 20; 3(11): 100628.
  1. 2.   Artificial Intelligence and Infectious Disease Imaging
  2. Chu, Winston T; Reza, Syed M S; Anibal, James T; Landa, Adam; Crozier,Ian; Bagci, Ulas; Wood, Bradford J; Solomon, Jeffrey
  3. The Journal of Infectious Diseases. 2023, Oct 03; 228(Supplement_4): S322-S336.
  1. 3.   Artificial Immune Cell, AI-cell, a New Tool to Predict Interferon Production by Peripheral Blood Monocytes in Response to Nucleic Acid Nanoparticles
  2. Chandler, Morgan; Jain, Sankalp; Halman, Justin; Hong, Enping; Dobrovolskaia,Marina; Zakharov, Alexey V; Afonin, Kirill A
  3. Small (Weinheim an der Bergstrasse, Germany). 2022, Oct 10; e2204941.
  1. 4.   Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation
  2. Stahlberg,Eric; Abdel-Rahman, Mohamed; Aguilar, Boris; Asadpoure, Alireza; Beckman, Robert A; Borkon,Lynn; Bryan, Jeffrey N; Cebulla, Colleen M; Chang, Young Hwan; Chatterjee, Ansu; Deng, Jun; Dolatshahi, Sepideh; Gevaert, Olivier; Greenspan, Emily J; Hao, Wenrui; Hernandez-Boussard, Tina; Jackson, Pamela R; Kuijjer, Marieke; Lee, Adrian; Macklin, Paul; Madhavan, Subha; McCoy, Matthew D; Mohammad Mirzaei, Navid; Razzaghi, Talayeh; Rocha, Heber L; Shahriyari, Leili; Shmulevich, Ilya; Stover, Daniel G; Sun, Yi; Syeda-Mahmood, Tanveer; Wang, Jinhua; Wang, Qi; Zervantonakis, Ioannis
  3. Frontiers in Digital Health. 2022, Oct 6; 4: 1007784.
  1. 5.   Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019
  2. Li, Zhang; Zhang, Jiehua; Tan, Tao; Teng, Xichao; Sun, Xiaoliang; Zhao, Hong; Liu, Lihong; Xiao, Yang; Lee, Byungjae; Li, Yilong; Zhang, Qianni; Sun, Shujiao; Zheng, Yushan; Yan, Junyu; Li, Ni; Hong, Yiyu; Ko, Junsu; Jung,Hyun; Liu,Yanling; Chen, Yu-cheng; Wang, Ching-wei; Yurovskiy, Vladimir; Maevskikh, Pavel; Khanagha, Vahid; Jiang, Yi; Yu, Li; Liu, Zhihong; Li, Daiqiang; Schueffler, Peter J.; Yu, Qifeng; Chen, Hui; Tang, Yuling; Litjens, Geert
  3. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS. 2021, Feb; 25(2): 429-440.
  1. 6.   Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model
  2. Sanford, Thomas H.; Zhang, Ling; Harmon,Stephanie; Sackett, Jonathan; Yang, Dong; Roth, Holger; Xu, Ziyue; Kesani, Deepak; Mehralivand, Sherif; Baroni, Ronaldo H.; Barrett, Tristan; Girometti, Rossano; Oto, Aytekin; Purysko, Andrei S.; Xu, Sheng; Pinto, Peter A.; Xu, Daguang; Wood, Bradford J.; Choyke, Peter L.; Turkbey, Baris
  3. AMERICAN JOURNAL OF ROENTGENOLOGY. 2020, DEC; 215(6): 1403-1410.
  1. 7.   Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI
  2. Mehralivand, Sherif; Harmon,Stephanie; Shih, Joanna H; Smith, Clayton P; Lay, Nathan; Argun, Burak; Bednarova, Sandra; Baroni, Ronaldo Hueb; Canda, Abdullah Erdem; Ercan, Karabekir; Girometti, Rossano; Karaarslan, Ercan; Kural, Ali Riza; Pursyko, Andrei S; Rais-Bahrami, Soroush; Tonso, Victor Martins; Magi-Galluzzi, Cristina; Gordetsky, Jennifer B; Macarenco, Ricardo Silvestre E Silva; Merino, Maria J; Gumuskaya, Berrak; Saglican, Yesim; Sioletic, Stefano; Warren, Anne Y; Barrett, Tristan; Bittencourt, Leonardo; Coskun, Mehmet; Knauss, Chris; Law, Yan Mee; Malayeri, Ashkan A; Margolis, Daniel J; Marko, Jamie; Yakar, Derya; Wood, Bradford J; Pinto, Peter A; Choyke, Peter L; Summers, Ronald M; Turkbey, Baris
  3. AJR. American journal of roentgenology. 2020, OCT; 215(4): 903-912.
  1. 8.   Accelerating Therapeutics for Opportunities in Medicine: A Paradigm Shift in Drug Discovery
  2. Hinkson, Izumi V; Madej,Benjamin; Stahlberg,Eric
  3. Frontiers in pharmacology. 2020, Jun 30; 11: 770.
  1. 9.   Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study
  2. Sanford, Thomas; Harmon,Stephanie; Turkbey, Evrim B; Kesani, Deepak; Tuncer, Sena; Madariaga, Manuel; Yang, Chris; Sackett, Jonathan; Mehralivand, Sherif; Yan, Pingkun; Xu, Sheng; Wood, Bradford J; Merino, Maria J; Pinto, Peter A; Choyke, Peter L; Turkbey, Baris
  3. Journal of magnetic resonance imaging : JMRI. 2020, Jun 01;
  1. 10.   Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology
  2. Turner, Oliver C; Aeffner, Famke; Bangari, Dinesh S; High, Wanda; Knight, Brian; Forest, Tom; Cossic, Brieuc; Himmel, Lauren E; Rudmann, Daniel G; Bawa, Bhupinder; Muthuswamy, Anantharaman; Aina, Olulanu H; Edmondson,Elijah; Saravanan, Chandrassegar; Brown, Danielle L; Sing, Tobias; Sebastian, Manu M
  3. Toxicologic pathology. 2019, Oct 23; 192623319881401.
  1. 11.   AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing
  2. Bhattacharya, Tanmoy; Brettin, Thomas; Doroshow, James H.; Evrard,Yvonne; Greenspan, Emily J.; Gryshuk, Amy L.; Hoang, Thuc T.; Lauzon, Carolyn B. Vea; Nissley,Dwight; Penberthy, Lynne; Stahlberg,Eric; Stevens, Rick; Streitz, Fred; Tourassi, Georgia; Xia, Fangfang; Zaki,George
  3. Frontiers in oncology. 2019, Oct 2; 9
  1. 12.   X Chromosome Evolution in Cetartiodactyla
  2. Proskuryakova, Anastasia A; Kulemzina, Anastasia I; Perelman, Polina L; Makunin, Alexey I; Larkin, Denis M; Farré, Marta; Kukekova, Anna V; Lynn Johnson, Jennifer; Lemskaya, Natalya A; Beklemisheva, Violetta R; Roelke-Parker, Melody; Bellizzi, June; Ryder, Oliver A; O'Brien, Stephen J; Graphodatsky, Alexander S
  3. Genes. 2017, Sep; 8(9): pii: E216.
  1. 13.   Probing Cellular Processes with Oligo-Mediated Recombination and Using the Knowledge Gained to Optimize Recombineering
  2. Sawitzke, J. A.; Costantino, N.; Li, X. T.; Thomason, L. C.; Bubunenko, M.; Court, C.; Court, D. L.
  3. Journal of Molecular Biology. 2011, Mar; 407(1): 45-59.
  1. 14.   Tumor antigen analysis in neuroblastoma by serological interrogation of bioinformatic data
  2. Kohler, M. E.; Johnson, B. D.; Palen, K.; Chen, Q. R.; Khan, J.; Orentas, R. J.
  3. Cancer Science. 2010, Nov; 101(11): 2316-2324.
  1. 15.   The molecular pathology of cancer
  2. Harris, T. J. R.; McCormick, F.
  3. Nature Reviews Clinical Oncology. 2010, May; 7(5): 251-265.
  1. 16.   Visualization and identification of IL-7 producing cells in reporter mice
  2. Mazzucchelli, R. I.; Warming, S.; Lawrence, S. M.; Ishii, M.; Abshari, M.; Washington, A. V.; Feigenbaum, L.; Warner, A. C.; Sims, D. J.; Li, W. Q.; Hixon, J. A.; Gray, D. H.; Rich, B. E.; Morrow, M.; Anver, M. R.; Cherry, J.; Naf, D.; Sternberg, L. R.; McVicar, D. W.; Farr, A. G.; Germain, R. N.; Rogers, K.; Jenkins, N. A.; Copeland, N. G.; Durum, S. K.
  3. Plos One. 2009 4(11): e7637.
  1. 17.   From wild animals to domestic pets, an evolutionary view of domestication
  2. Driscoll, C. A.; Macdonald, D. W.; O'Brien, S. J.
  3. Proceedings of the National Academy of Sciences of the United States of America. 2009 106: 9971-9978.
  1. 18.   microRNA Profiling Identifies Cancer-Specific and Prognostic Signatures in Pediatric Malignancies
  2. Wei, J. S.; Johansson, P.; Chen, Q. R.; Song, Y. K.; Durinck, S.; Wen, X. Y.; Cheuk, A.; Smith, M. A.; Houghton, P.; Morton, C.; Khan, J.
  3. Clinical Cancer Research. 2009 15(17): 5560-5568.
  1. 19.   Advantages of q-PCR as a method of screening for gene targeting in mammalian cells using conventional and whole BAC-based constructs
  2. Gomez-Rodriguez, J.; Washington, V.; Cheng, J.; Dutra, A.; Pak, E.; Liu, P. T.; McVicar, D. W.; Schwartzberg, P. L.
  3. Nucleic Acids Research. 2008 36(18): 1-9.
  1. 20.   Multicopy plasmid modification with phage lambda red recombineering
  2. Thomason, L. C.; Costantino, N.; Shaw, D. V.; Court, D. L.
  3. Plasmid. 2007, Sep; 58(2): 148-158.
  1. 21.   Diagnosis of the small round blue cell tumors using multiplex polymerase chain reaction
  2. Chen, Q. R.; Vansant, G.; Oades, K.; Pickering, M.; Wei, J. S.; Song, Y. K.; Monforte, J.; Khan, J.
  3. Journal of Molecular Diagnostics. 2007, Feb; 9(1): 80-88.
  1. 22.   Recombineering: In vivo genetic engineering in E-coli, S-enterica, and beyond
  2. Sawitzke, J. A.; Thomason, L. C.; Costantino, N.; Bubunenko, M.; Datta, S.; Court, D. L.
  3. Advanced Bacterial Genetics: Use of Transposons and Phage for Genomic Engieering. 2007; 421 : 171-199.
  1. 23.   Analysis of a new homozygous deletion in the tumor suppressor region at 3p12.3 reveals two novel intronic noncoding RNA genes
  2. Angeloni, D.; ter Elst, A.; Wei, M. H.; van der Veen, A. Y.; Braga, E. A.; Klimov, E. A.; Timmer, T.; Korobeinikova, L.; Lerman, M. I.; Buys, C.
  3. Genes Chromosomes & Cancer. 2006, Jul; 45(7): 676-691.
  1. 24.   Transgenic mice expressing Cre-recombinase specifically in retinal rod bipolar neurons
  2. Zhang, X. M.; Chen, B. Y.; Ng, A. H. L.; Tanner, J. A.; Tay, D.; So, K. F.; Rachel, R. A.; Copeland, N. G.; Jenkins, N. A.; Huang, J. D.
  3. Investigative Ophthalmology & Visual Science. 2005, OCT; 46(10): 3515-3520.
  1. 25.   The Ter mutation in the dead end gene causes germ cell loss and testicular germ cell tumours
  2. Youngren, K. K.; Coveney, D.; Peng, X. N.; Bhattacharya, C.; Schmidt, L. S.; Nickerson, M. L.; Lamb, B. T.; Deng, J. M.; Behringer, R. R.; Capel, B.; Rubin, E. M.; Nadeau, J. H.; Matin, A.
  3. Nature. 2005, MAY 19; 435(7040): 360-364.
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