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Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data

A. Smith, J. Walsh, J. Long, C. Davis, P. Henstock, M. Hodge, M. Maciejewski, X. Mu, S. Ra, S. Zhao, and others. BMC Bioinformatics, 21 (1): 1--18 (2020)

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Bernd Maciejewski

Mateusz Laszczkowski

Mateusz Putyrski

Mateusz Majer

Mateusz Jochym

Other publications of authors with the same name

Public Domain HTS Fingerprints: Design and Evaluation of Compound Bioactivity Profiles from PubChem's Bioassay Repository.K. Helal, M. Maciejewski, E. Gregori-Puigjané, M. Glick, and A. Wassermann. Journal of Chemical Information and Modeling, 56 (2): 390-398 (2016)New analogs of the clinical complement inhibitor compstatin with subnanomolar affinity and enhanced pharmacokinetic propertiesH. Qu, D. Ricklin, H. Bai, H. Chen, E. Reis, M. Maciejewski, A. Tzekou, R. DeAngelis, R. Resuello, F. Lupu and 2 other author(s). Immunobiology, 218 (4): 496--505 (April 2013)A probabilistic pathway score (PROPS) for classification with applications to inflammatory bowel disease.L. Han, M. Maciejewski, C. Brockel, W. Gordon, S. Snapper, J. Korzenik, L. Afzelius, and R. Altman. Bioinform., 34 (6): 985-993 (2018)Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics dataA. Smith, J. Walsh, J. Long, C. Davis, P. Henstock, M. Hodge, M. Maciejewski, X. Mu, S. Ra, S. Zhao and 1 other author(s). BMC Bioinformatics, 21 (1): 1--18 (2020)Multiple positive solutions of parabolic systems with nonlinear, nonlocal initial conditions.G. Infante, and M. Maciejewski. J. Lond. Math. Soc., 94 (3): 859-882 (2016)A branch hash function as a method of message synchronization in anonymous P2P conversations.A. Kobusinska, J. Brzezinski, M. Boron, L. Inatlewski, M. Jabczynski, and M. Maciejewski. Int. J. Appl. Math. Comput. Sci., 26 (2): 479-493 (2016)Decoding the components of dynamics in three-domain proteins.M. Maciejewski, P. Barlow, and N. Tjandra. J. Comput. Chem., 35 (7): 518-525 (2014)Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.A. Smith, J. Walsh, J. Long, C. Davis, P. Henstock, M. Hodge, M. Maciejewski, X. Mu, S. Ra, S. Zhao and 2 other author(s). BMC Bioinform., 21 (1): 119 (2020)

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Disambiguation of "Maciejewski, Mateusz"

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Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data

Please choose a person to relate this publication to

Bernd Maciejewski

Mateusz Laszczkowski

Mateusz Putyrski

Mateusz Majer

Mateusz Jochym

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Maciejewski, Mateusz"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data

Please choose a person to relate this publication to

Bernd Maciejewski

Mateusz Laszczkowski

Mateusz Putyrski

Mateusz Majer

Mateusz Jochym

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
Harvard
MSOffice XML

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data