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1
Machine learning detects pan-cancer ras pathway activation in the cancer genome atlas
Machine learning detects pan-cancer ras pathway activation in the cancer genome atlas
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Machine learning detects pan-cancer ras pathway activation in the cancer genome atlas

Houtan Noushmehr Carlos Gilberto Carlotti Júnior; José Sebastião dos Santos; Rafael Kemp; Ajith Kumar Sankarankutty; Daniela Pretti da Cunha Tirapelli

Cell Reports Cambridge v. 23, n. 1, p. 172-180, 2018

Cambridge 2018

Localização: FMRP - Fac. Medicina de Ribeirão Preto    (pcd 2938459 Estantes Deslizantes )(Acessar)

2
Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images
Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images
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Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images

Joel Saltz Rajarsi Gupta; Le Hou; Tahsin Kurc; Pankaj Singh; Vu Nguyen; Dimitris Samaras; Kenneth R Shroyer; Tianhao Zhao; Rebecca Batiste; John Van Arnam; Ilya Shmulevich; Arvind Rao; Alexander J Lazar; Ashish Sharma; Vésteinn Thorsson; Houtan Noushmehr; Carlos Gilberto Carlotti Júnior; José Sebastião dos Santos; Rafael Kemp; Ajith Kumar Sankarankuty; Daniela Pretti da Cunha Tirapelli; The Cancer Genome Atlas Research Network

Cell Reports Cambridge v. 23, n. 1, p. 181-193, 2018

Cambridge 2018

Localização: FMRP - Fac. Medicina de Ribeirão Preto    (pcd 2938421 Estantes Deslizantes )(Acessar)

3
A study of high-grade serous ovarian cancer origins implicates the SOX18 transcription factor in tumor development
A study of high-grade serous ovarian cancer origins implicates the SOX18 transcription factor in tumor development
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A study of high-grade serous ovarian cancer origins implicates the SOX18 transcription factor in tumor development

Kate Lawrenson Marcos A. S Fonseca; Annie Y Liu; Felipe Segato Dezem; Janet M Lee; Xianzhi Lin; Rosario I Corona; Forough Abbasi; Kevin C Vavra; Huy Q Dinh; Navjot Kaur Gill; Houtan Noushmehr

Cell Reports Cambridge v. 29, n. 11, p. 3726-3735.e1-e4, 2019

Cambridge 2019

Localização: FMRP - Fac. Medicina de Ribeirão Preto    (pcd 3026806 Acervo Digital )(Acessar)

4
Predicting protein condensate formation using machine learning
Predicting protein condensate formation using machine learning
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Predicting protein condensate formation using machine learning

van Mierlo, Guido ; Jansen, Jurriaan R.G. ; Wang, Jie ; Poser, Ina ; van Heeringen, Simon J. ; Vermeulen, Michiel

Cell reports (Cambridge), 2021-02, Vol.34 (5), p.108705-108705, Article 108705 [Periódico revisado por pares]

United States: Elsevier Inc

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5
Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space
Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space
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Deep neural networks identify signaling mechanisms of ErbB-family drug resistance from a continuous cell morphology space

Longden, James ; Robin, Xavier ; Engel, Mathias ; Ferkinghoff-Borg, Jesper ; Kjær, Ida ; Horak, Ivan D. ; Pedersen, Mikkel W. ; Linding, Rune

Cell reports (Cambridge), 2021-01, Vol.34 (3), p.108657-108657, Article 108657 [Periódico revisado por pares]

United States: Elsevier Inc

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6
Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning
Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning
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Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning

Narykov, Oleksandr ; Johnson, Nathan T. ; Korkin, Dmitry

Cell reports (Cambridge), 2021-11, Vol.37 (8), p.110045-110045, Article 110045 [Periódico revisado por pares]

United States: Elsevier Inc

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7
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
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Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Kurc, Tahsin ; Demchok, John A. ; Ferguson, Martin L. ; Tarnuzzer, Roy ; Yang, Liming ; DeFreitas, Timothy ; Noble, Michael S. ; Voet, Doug ; Dhankani, Varsha ; Leinonen, Kalle ; Ju, Zhenlin ; Korkut, Anil ; Liu, Wenbin ; Abeshouse, Adam ; Chakravarty, Debyani ; Taylor, Barry S. ; Anur, Pavana ; Wong, Christopher K. ; Yau, Christina ; Ally, Adrian ; Kasaian, Katayoon ; Mayo, Michael ; Moore, Richard A. ; Berger, Ashton C. ; Gao, Galen F. ; Meyerson, Matthew ; Danilova, Ludmila ; Bootwalla, Moiz S. ; Hoadley, Katherine A. ; Jones, Corbin D. ; Mose, Lisle E. ; Tan, Donghui ; Hu, Jianhong ; Liu, Xiuping ; Sheth, Margi ; Bailey, Matthew ; Fronick, Catrina C. ; Kandoth, Cyriac ; Wilson, Richard K. ; Lau, Kevin ; Penny, Robert ; Thompson, Eric ; Fregnani, José H. ; McPherson, Christopher ; Berkowitz, Ross ; Barnholtz-Sloan, Jill S. ; Myers, Jerome ; Tucker, Kelinda ; Zelinka, Tomas ; Sepulveda, Antonia ; Desjardins, Laurence ; Lipp, Eric ; Sharp, Alexis ; Delman, Keith ; Owonikoko, Taofeek ; Oosterhuis, Wolter ; DiMeco, Francesco ; Finocchiaro, Gaetano ; Perin, Alessandro ; Wiznerowicz, Maciej ; Baudin, Eric ; Noushmehr, Houtan ; Scarpace, Lisa ; Dottino, Peter R. ; Breggia, Anne ; Bryce, Alan H. ; Copland, John A. ; Kocher, Jean-Pierre ; Petersen, Gloria ; Rivera, Michael ; Esmaeli, Bita ; Logothetis, Christopher ; Sood, Anil ; Kefford, Richard ; Shannon, Kerwin ; Ghossein, Ronald ; Smith, Jennifer ; Wentzensen, Nicolas ; Tcaciuc, Diana ; Engel, Jay ; Rassl, Doris M. ; Urba, Walter ; Merola, Roberta ; Cardinale, Vincenzo ; Carpino, Guido ; Cottingham, Sandra ; Janssen, Klaus-Peter ; Davis, Amy ; Lang, James ; Rai, Karan ; Kastl, Alison ; Waldmann, Jens ; Simon, Ronald ; Simko, Jeffry ; VandenBerg, Scott ; Unterberg, Andreas ; Beer, David ; Peterson, Lisa ; Ley, Timothy ; Thorsson, Vésteinn

Cell reports (Cambridge), 2018-04, Vol.23 (1), p.181-193.e7 [Periódico revisado por pares]

United States: Elsevier Inc

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8
Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas
Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas
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Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas

Knijnenburg, Theo A. ; Liu, Yuexin ; Kim, Pora ; Zhang, Shaojun ; Zhao, Zhongming ; Laird, Peter W. ; Ferguson, Martin L. ; Liu, Jia ; Lawrence, Michael S. ; Saksena, Gordon ; Voet, Doug ; Dhankani, Varsha ; Hegde, Apurva M. ; Ladanyi, Marc ; Sander, Chris ; Anur, Pavana ; Wong, Christopher K. ; Yau, Christina ; Ally, Adrian ; Kasaian, Katayoon ; Ma, Yussanne ; Shih, Juliann ; Maglinte, Dennis T. ; Drummond, Jennifer ; Hale, Walker ; Korchina, Viktoriya ; Morgan, Margaret ; Morton, Donna ; Sheth, Margi ; Wang, Linghua ; Wheeler, David A. ; Kandoth, Cyriac ; Lau, Kevin ; Thompson, Eric ; Leraas, Kristen M. ; Huntsman, David ; Horowitz, Neil ; Fulop, Jordonna ; Sloan, Andrew E. ; Tucker, Kelinda ; Zelinka, Tomas ; Iacocca, Mary ; Sepulveda, Antonia ; Roman-Roman, Sergio ; Stern, Marc-Henri ; Lipp, Eric ; Delman, Keith ; Gillis, Ad ; Korpershoek, Esther ; Looijenga, Leendert ; Perin, Alessandro ; Stoehr, Christine ; Stoehr, Robert ; Wach, Sven ; Kycler, Witold ; Chung, Ki ; Martin, Julie ; Bubley, Glenn ; De Rienzo, Assunta ; Richards, William G. ; Campo, Elias ; Evason, Kimberley ; Borad, Mitesh ; Kocher, Jean-Pierre ; Petersen, Gloria ; Que, Florencia ; Ajani, Jaffer A. ; Esmaeli, Bita ; Logothetis, Christopher ; Sood, Anil ; Mann, Graham ; Gopalan, Anuradha ; Zaren, Howard ; Yang, Hannah ; Caraman, Irina ; Mura, Sergiu ; Stancul, Irina ; Albert, Monique ; Arnaout, Angel ; Rassl, Doris M. ; Barnett, Gene ; Farver, Carol ; Raymond, Daniel ; Dinkin, Mikhail ; Kumar, Bahavna ; Waldmann, Jens ; Fassnacht, Martin ; Tennstedt, Pierre ; Glenn, Pat ; Kendler, Ady ; Steele, Ruth ; Campos, Benito ; Adebamowo, Sally N. ; Giordano, Thomas ; Mes-Masson, Anne-Marie ; Moxley, Katherine ; Pinero, Edna M. Mora ; Carey, Thomas ; Wolf, Gregory ; Ley, Timothy

Cell reports (Cambridge), 2018-04, Vol.23 (1), p.239-254.e6 [Periódico revisado por pares]

United States: Elsevier Inc

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9
CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues
CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues
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CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues

Stoltzfus, Caleb R. ; Filipek, Jakub ; Gern, Benjamin H. ; Olin, Brandy E. ; Leal, Joseph M. ; Wu, Yajun ; Lyons-Cohen, Miranda R. ; Huang, Jessica Y. ; Paz-Stoltzfus, Clarissa L. ; Plumlee, Courtney R. ; Pöschinger, Thomas ; Urdahl, Kevin B. ; Perro, Mario ; Gerner, Michael Y.

Cell reports (Cambridge), 2020-04, Vol.31 (3), p.107523-107523, Article 107523 [Periódico revisado por pares]

United States: Elsevier Inc

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10
A Deep Learning Framework for Predicting Response to Therapy in Cancer
A Deep Learning Framework for Predicting Response to Therapy in Cancer
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A Deep Learning Framework for Predicting Response to Therapy in Cancer

Sakellaropoulos, Theodore ; Vougas, Konstantinos ; Narang, Sonali ; Koinis, Filippos ; Kotsinas, Athanassios ; Polyzos, Alexander ; Moss, Tyler J. ; Piha-Paul, Sarina ; Zhou, Hua ; Kardala, Eleni ; Damianidou, Eleni ; Alexopoulos, Leonidas G. ; Aifantis, Iannis ; Townsend, Paul A. ; Panayiotidis, Mihalis I. ; Sfikakis, Petros ; Bartek, Jiri ; Fitzgerald, Rebecca C. ; Thanos, Dimitris ; Mills Shaw, Kenna R. ; Petty, Russell ; Tsirigos, Aristotelis ; Gorgoulis, Vassilis G.

Cell reports (Cambridge), 2019-12, Vol.29 (11), p.3367-3373.e4 [Periódico revisado por pares]

United States: Elsevier Inc

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Deste Autor:

  1. Noushmehr, H
  2. Santos, J
  3. Carlotti Júnior, C
  4. Kemp, R
  5. Tirapelli, D

Neste Assunto:

  1. Machine Learning
  2. Cell Biology
  3. Life Sciences & Biomedicine
  4. Science & Technology
  5. Humans

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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