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Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction.

O. Narykov, Y. Zhu, T. Brettin, Y. Evrard, A. Partin, M. Shukla, P. Vasanthakumari, J. Doroshow, and R. Stevens. SC Workshops, page 121-122. ACM, (2023)

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Michael Brettin

Thomas S Rau

Thomas S Eberle

Thomas S Mir

Thomas S Hoffmeister

Other publications of authors with the same name

RegPrecise web services interface: programmatic access to the transcriptional regulatory interactions in bacteria reconstructed by comparative genomics.P. Novichkov, T. Brettin, E. Novichkova, P. Dehal, A. Arkin, I. Dubchak, and D. Rodionov. Nucleic Acids Res., 40 (Web-Server-Issue): 604-608 (2012)PATRIC as a unique resource for studying antimicrobial resistance.D. Antonopoulos, R. Assaf, R. Aziz, T. Brettin, C. Bun, N. Conrad, J. Davis, E. Dietrich, T. Disz, S. Gerdes and 19 other author(s). Briefings Bioinform., 20 (4): 1094-1102 (2019)High-Throughput Virtual Screening and Validation of a SARS-CoV-2 Main Protease Noncovalent Inhibitor.A. Clyde, S. Galanie, D. Kneller, H. Ma, Y. Babuji, B. Blaiszik, A. Brace, T. Brettin, K. Chard, R. Chard and 20 other author(s). J. Chem. Inf. Model., 62 (1): 116-128 (2022)DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.S. Song, B. Kruft, M. Zhang, C. Li, S. Chen, C. Zhang, M. Tanaka, X. Wu, J. Rasley, A. Awan and 82 other author(s). CoRR, (2023)Leveraging Large-Scale Computing for Population Information Integration, Analysis, and Modeling.J. Boten, D. Rivera, M. Myneni, G. Tourassi, T. Bhattacharya, A. de Oliveira Sales, T. Brettin, P. Fearn, and L. Penberthy. AMIA, AMIA, (2017)Learning Curves for Drug Response Prediction in Cancer Cell Lines.A. Partin, T. Brettin, Y. Evrard, Y. Zhu, H. Yoo, F. Xia, S. Jiang, A. Clyde, M. Shukla, M. Fonstein and 2 other author(s). CoRR, (2020)Deep learning methods for drug response prediction in cancer: predominant and emerging trends.A. Partin, T. Brettin, Y. Zhu, O. Narykov, A. Clyde, J. Overbeek, and R. Stevens. CoRR, (2022)A cross-study analysis of drug response prediction in cancer cell lines.F. Xia, J. Allen, P. Balaprakash, T. Brettin, C. Garcia-Cardona, A. Clyde, J. Cohn, J. Doroshow, X. Duan, V. Dubinkina and 14 other author(s). Briefings Bioinform., (2022)Predicting tumor cell line response to drug pairs with deep learning.F. Xia, M. Shukla, T. Brettin, C. Garcia-Cardona, J. Cohn, J. Allen, S. Maslov, S. Holbeck, J. Doroshow, Y. Evrard and 2 other author(s). BMC Bioinform., 19-S (18): 71-79 (2018)A novel approach to high throughput microbial genome finishing: Incorporation of 454 sequence data for gap closure in low quality Sanger data.A. Kewalramani, R. Arnaudville, C. Han, O. Chertkov, and T. Brettin. BIOCOMP, page 169-174. CSREA Press, (2007)

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Disambiguation of "Brettin, Thomas S."

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Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction.

Please choose a person to relate this publication to

Michael Brettin

Thomas S Rau

Thomas S Eberle

Thomas S Mir

Thomas S Hoffmeister

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Brettin, Thomas S."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction.

Please choose a person to relate this publication to

Michael Brettin

Thomas S Rau

Thomas S Eberle

Thomas S Mir

Thomas S Hoffmeister

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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MSOffice XML

Entropy-Based Regularization on Deep Learning Models for Anti-Cancer Drug Response Prediction.