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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, J. Doroshow, and R. Stevens. CoRR, (2020)

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Lise Partin

Karl-Michael Partin

Alexander

Alexander Auch

A phylogenetic potpourri: computational methods for analysing genome scale dataA. Auch. Uni Tübingen, (2010)

Alexander Stadler

Messtechnische Bestimmung und Simulation der Kernverluste in weichmagnetischen MaterialienA. Stadler. Uni Erlangen-Nürnberg, (2009)

Other publications of authors with the same name

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads.A. Saadi, D. Alfè, Y. Babuji, A. Bhati, B. Blaiszik, T. Brettin, K. Chard, R. Chard, P. Coveney, A. Trifan and 26 other author(s). CoRR, (2020)An Automation Framework for Comparison of Cancer Response Models Across Configurations.J. Wozniak, R. Jain, A. Wilke, R. Weaver, A. Partin, T. Brettin, and R. Stevens. e-Science, page 1-10. IEEE, (2023)A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning.A. Clyde, T. Brettin, A. Partin, M. Shaulik, H. Yoo, Y. Evrard, Y. Zhu, F. Xia, and R. Stevens. 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)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)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)Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response.Y. Zhu, T. Brettin, Y. Evrard, A. Partin, F. Xia, M. Shukla, H. Yoo, J. Doroshow, and R. Stevens. CoRR, (2020)Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers.A. Bhati, S. Wan, D. Alfè, A. Clyde, M. Bode, L. Tan, M. Titov, A. Merzky, M. Turilli, S. Jha and 19 other author(s). CoRR, (2021)IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads.A. Saadi, D. Alfè, Y. Babuji, A. Bhati, B. Blaiszik, A. Brace, T. Brettin, K. Chard, R. Chard, A. Clyde and 26 other author(s). ICPP, page 40:1-40:12. ACM, (2021)Protein-Ligand Docking Surrogate Models: A SARS-CoV-2 Benchmark for Deep Learning Accelerated Virtual Screening.A. Clyde, T. Brettin, A. Partin, H. Yoo, Y. Babuji, B. Blaiszik, A. Merzky, M. Turilli, S. Jha, A. Ramanathan and 1 other author(s). CoRR, (2021)

BibSonomy

Disambiguation of "Partin, Alexander"

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Learning Curves for Drug Response Prediction in Cancer Cell Lines.

Please choose a person to relate this publication to

Lise Partin

Karl-Michael Partin

Alexander

Alexander Auch

Alexander Stadler

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Partin, Alexander"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Learning Curves for Drug Response Prediction in Cancer Cell Lines.

Please choose a person to relate this publication to

Lise Partin

Karl-Michael Partin

Alexander

Alexander Auch

Alexander Stadler

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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Learning Curves for Drug Response Prediction in Cancer Cell Lines.