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  1. 1.   Data imbalance in drug response prediction: multi-objective optimization approach in deep learning setting
  2. Narykov, Oleksandr; Zhu, Yitan; Brettin, Thomas; Evrard,Yvonne; Partin, Alexander; Xia, Fangfang; Shukla, Maulik; Vasanthakumari, Priyanka; Doroshow, James H; Stevens, Rick L
  3. Briefings in Bioinformatics. 2025, Mar 04; 26(2):
  1. 2.   A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening
  2. Vasanthakumari, Priyanka; Zhu, Yitan; Brettin, Thomas; Partin, Alexander; Shukla, Maulik; Xia, Fangfang; Narykov, Oleksandr; Weil,Michael; Stevens, Rick L
  3. Cancers. 2024, Jan 26; 16(3):
  1. 3.   Long-term survivors of glioblastoma: Tumor molecular, clinical, and imaging findings
  2. Briceno, Nicole; Vera, Elizabeth; Komlodi-Pasztor, Edina; Abdullaev, Zied; Choi, Anna; Grajkowska, Ewa; Kunst, Tricia; Levine, Jason; Lindsley, Matthew; Fernandez, Kelly; Reyes, Jennifer; Boris,Lisa; Burton, Eric; Panzer, Marissa; Polskin, Lily; Penas-Prado, Marta; Pillai, Tina; Theeler, Brett J; Wu, Jing; Wall, Kathleen; Papanicolau-Sengos, Antonios; Quezado, Martha; Smirniotopoulos, James; Aldape, Kenneth; Armstrong, Terri S; Gilbert, Mark R
  3. Neuro-Oncology Advances. 2024, Jan-Dec; 6(1): vdae019.
  1. 4.   Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models
  2. Narykov, Oleksandr; Zhu, Yitan; Brettin, Thomas; Evrard,Yvonne; Partin, Alexander; Shukla, Maulik; Xia, Fangfang; Clyde, Austin; Vasanthakumari, Priyanka; Doroshow, James H; Stevens, Rick L
  3. Cancers. 2023, Dec 21; 16(1):
  1. 5.   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. 6.   BETA: a comprehensive benchmark for computational drug-target prediction
  2. Zong, Nansu; Li,Ning; Wen, Andrew; Ngo, Victoria; Yu, Yue; Huang, Ming; Chowdhury, Shaika; Jiang, Chao; Fu, Sunyang; Weinshilboum, Richard; Jiang, Guoqian; Hunter, Lawrence; Liu, Hongfang
  3. Briefings in Bioinformatics. 2022, Jun 02;
  1. 7.   A practical guide to large-scale docking
  2. Bender, Brian J.; Gahbauer, Stefan; Luttens, Andreas; Lyu, Jiankun; Webb, Chase M.; Stein, Reed M.; Fink, Elissa A.; Balius,Trent; Carlsson, Jens; Irwin, John J.; Shoichet, Brian K.
  3. Nature protocols. 2021, Oct; 16(10): 4799-4832.
  1. 8.   A cross-study analysis of drug response prediction in cancer cell lines
  2. Xia, Fangfang; Allen, Jonathan; Balaprakash, Prasanna; Brettin, Thomas; Garcia-Cardona, Cristina; Clyde, Austin; Cohn, Judith; Doroshow,Jim; Duan, Xiaotian; Dubinkina, Veronika; Evrard,Yvonne; Fan, Ya Ju; Gans, Jason; He, Stewart; Lu,Pinyi; Maslov, Sergei; Partin, Alexander; Shukla, Maulik; Stahlberg,Eric; Wozniak, Justin M; Yoo, Hyunseung; Zaki,George; Zhu, Yitan; Stevens, Rick
  3. Briefings in Bioinformatics. 2021, Sep 14;
  1. 9.   Application of CHyMErA Cas9-Cas12a combinatorial genome-editing platform for genetic interaction mapping and gene fragment deletion screening
  2. Aregger,Michael; Xing, Kun; Gonatopoulos Pournatzis,Thomas
  3. Nature Protocols . 2021, Sep 10; 16(10): 4722-4765.
  1. 10.   Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs
  2. Weingarten-Gabbay, Shira; Klaeger, Susan; Sarkizova, Siranush; Pearlman, Leah R.; Chen, Da-Yuan; Gallagher, Kathleen M. E.; Bauer, Matthew R.; Taylor, Hannah B.; Dunn, W. Augustine; Tarr, Christina; Sidney, John; Rachimi, Suzanna; Conway, Hasahn L.; Katsis, Katelin; Wang, Yuntong; Leistritz-Edwards, Del; Durkin, Melissa R.; Tomkins-Tinch, Christopher H.; Finkel, Yaara; Nachshon, Aharon; Gentili, Matteo; Rivera, Keith D.; Carulli, Isabel P.; Chea, Vipheaviny A.; Chandrashekar, Abishek; Bozkus, Cansu Cimen; Carrington,Mary; Bhardwaj, Nina; Barouch, Dan H.; Sette, Alessandro; Maus, Marcela; Rice, Charles M.; Clauser, Karl R.; Keskin, Derin B.; Pregibon, Daniel C.; Hacohen, Nir; Carr, Steven A.; Abelin, Jennifer G.; Saeed, Mohsan; Sabeti, Pardis C.
  3. CELL. 2021, Jul 22; 184(15): 3962-3980.e17.
  1. 11.   Learning curves for drug response prediction in cancer cell lines
  2. Partin, Alexander; Brettin, Thomas; Evrard,Yvonne; Zhu, Yitan; Yoo, Hyunseung; Xia, Fangfang; Jiang, Songhao; Clyde, Austin; Shukla, Maulik; Fonstein, Michael; Doroshow, James H.; Stevens, Rick L.
  3. BMC bioinformatics. 2021, May 17; 22(1):
  1. 12.   Low-level variant calling for non-matched samples using a position-based and nucleotide-specific approach
  2. Dudley, Jeffrey N.; Hong, Celine S.; Hawari, Marwan A.; Shwetar, Jasmine; Sapp, Julie C.; Lack, Justin; Shiferaw, Henoke; Johnston, Jennifer J.; Biesecker, Leslie G.
  3. BMC Bioinformatics. 2021, Apr 8; 22(1):
  1. 13.   A new precision medicine initiative at the dawn of exascale computing
  2. Nussinov,Ruth; Jang,Hyunbum; Nir, Guy; Tsai,Chung-Jung; Cheng, Feixiong
  3. Signal transduction and targeted therapy. 2021, Jan 6; 6(1):
  1. 14.   SAVI, in silico generation of billions of easily synthesizable compounds through expert-system type rules
  2. Patel,Hitesh; Ihlenfeldt, Wolf-Dietrich; Judson, Philip N; Moroz, Yurii S; Pevzner, Yuri; Peach,Megan; Delannee,Victorien; Tarasova,Nadya; Nicklaus,Marc
  3. Scientific data. 2020, NOV 11; 7(1): 384.
  1. 15.   Use of human peripheral blood mononuclear cells to define immunological properties of nucleic acid nanoparticles
  2. Dobrovolskaia,Marina; Afonin, Kirill A
  3. Nature protocols. 2020, Oct 23; 15(11): 3678-3698.
  1. 16.   Inter-Institutional Partnerships to Develop Veterinarian-Investigators through the NIH Comparative Biomedical Scientist Training Program Benefit One Health Goals
  2. Simpson, R. Mark; Hoover, Shelley B.; Davis, Barbara J.; Hickerson, John; Miller, Margaret A.; Kiupel, Matti; Cullen, John M.; Dwyer, Jennifer E.; Wei,Bih; Rosol, Thomas J.; Kornegay, Joe N.; Samal, Siba K.
  3. JOURNAL OF VETERINARY MEDICAL EDUCATION. 2020, OCT; 47(5): 619-631.
  1. 17.   Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models
  2. Zhu, Yitan; Brettin, Thomas; Evrard,Yvonne; Xia, Fangfang; Partin, Alexander; Shukla, Maulik; Yoo, Hyunseung; Doroshow, James H; Stevens, Rick L
  3. Genes. 2020, Sep 11; 11(9): pii: E1070.
  1. 18.   Modeling ligand docking to RNA in the design of RNA-based nanostructures
  2. Kasprzak,Wojciech; Ahmed, Nour Ali; Shapiro,Bruce
  3. Current opinion in biotechnology. 2020, JUN; 63: 16-25.
  1. 19.   HMI-PRED: A Web Server for Structural Prediction of Host-Microbe Interactions Based on Interface Mimicry
  2. Guven Maiorov,Emine; Hakouz, Asma; Valjevac, Sukejna; Keskin, Ozlem; Tsai,Chung-Jung; Gursoy, Attila; Nussinov,Ruth
  3. Journal of molecular biology. 2020, MAY 15; 432(11): 3395-3403.
  1. 20.   Target identification among known drugs by deep learning from heterogeneous networks
  2. Zeng, Xiangxiang; Zhu, Siyi; Lu, Weiqiang; Liu, Zehui; Huang, Jin; Zhou, Yadi; Fang, Jiansong; Huang, Yin; Guo, Huimin; Li, Lang; Trapp, Bruce D.; Nussinov,Ruth; Eng, Charis; Loscalzo, Joseph; Cheng, Feixiong
  3. CHEMICAL SCIENCE. 2020, Feb 21; 11(7): 1775-1797.
  1. 21.   Why Are Some Driver Mutations Rare?
  2. Nussinov,Ruth; Tsai,Chung-Jung; Jang,Hyunbum
  3. Trends in pharmacological sciences. 2019, Dec; 40(12): 919-929.
  1. 22.   Oncoviruses Can Drive Cancer by Rewiring Signaling Pathways Through Interface Mimicry
  2. Guven Maiorov,Emine; Tsai,Chung-Jung; Nussinov,Ruth
  3. Frontiers in oncology. 2019, Nov 15; 9: 1236.
  1. 23.   Improving (Q)SAR predictions by examining bias in the selection of compounds for experimental testing
  2. Pogodin, P V; Lagunin, A A; Filimonov, D A; Nicklaus,Marc; Poroikov, V V
  3. SAR and QSAR in environmental research. 2019, OCT 3; 30(10): 759-773.
  1. 24.   Characterization by Empirical and Computational Methods of Dictyospiromide, an Intriguing Antioxidant Alkaloid from the Marine Alga Dictyota coriacea
  2. Yan, Pengcheng; Li, Ge; Wang, Chaojie; Wu, Jianzhang; Sun, Zhongmin; Martin, Gary E; Wang, Xiao; Reibarkh, Mikhail; Saurí, Josep; Gustafson,Kirk
  3. Organic letters. 2019, Sep 20; 21(18): 7577-7581.
  1. 25.   Assessing drug-induced long QT and proarrhythmic risk using human stem cell-derived cardiomyocytes in a Ca2+ imaging assay: Evaluation of 28 CiPA compounds at three test sites
  2. Lu, Hua Rong; Zeng, Haoyu; Kettenhofen, Ralf; Guo,Liang; Kopljar, Ivan; van Ammel, Karel; Tekle, Fetene; Teisman, Ard; Zhai, Jin; Clouse, Holly; Pierson, Jennifer; Furniss, Michael; Lagrutta, Armando; Sannajust, Frederick; Gallacher, David J
  3. Toxicological sciences : an official journal of the Society of Toxicology. 2019, AUG; 170(2): 345-356.
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