Ladislav Rampášek
Ladislav Rampášek
Postdoctoral Fellow at Mila - Quebec AI Institute and Université de Montréal
Bestätigte E-Mail-Adresse bei cs.toronto.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Intertumoral heterogeneity within medulloblastoma subgroups
FMG Cavalli, M Remke, L Rampasek, J Peacock, DJH Shih, B Luu, ...
Cancer cell 31 (6), 737-754. e6, 2017
5182017
TensorFlow: biology’s gateway to deep learning?
L Rampasek, A Goldenberg
Cell systems 2 (1), 12-14, 2016
1932016
Dr. VAE: improving drug response prediction via modeling of drug perturbation effects
L Rampášek, D Hidru, P Smirnov, B Haibe-Kains, A Goldenberg
Bioinformatics 35 (19), 3743-3751, 2019
472019
Machine learning approaches to drug response prediction: challenges and recent progress
G Adam, L Rampášek, Z Safikhani, P Smirnov, B Haibe-Kains, ...
NPJ precision oncology 4 (1), 1-10, 2020
262020
Dr. vae: Drug response variational autoencoder
L Rampasek, D Hidru, P Smirnov, B Haibe-Kains, A Goldenberg
arXiv preprint arXiv:1706.08203, 2017
252017
Learning from everyday images enables expert-like diagnosis of retinal diseases
L Rampasek, A Goldenberg
Cell 172 (5), 893-895, 2018
202018
Probabilistic method for detecting copy number variation in a fetal genome using maternal plasma sequencing
L Rampášek, A Arbabi, M Brudno
Bioinformatics 30 (12), i212-i218, 2014
162014
Dropout feature ranking for deep learning models
CH Chang, L Rampasek, A Goldenberg
arXiv preprint arXiv:1712.08645, 2017
132017
Discovery of RNA motifs using a computational pipeline that allows insertions in paired regions and filtering of candidate sequences
RM Jimenez, L Rampášek, B Brejová, T Vinař, A Lupták
Ribozymes, 145-158, 2012
92012
Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction
A Arbabi, L Rampášek, M Brudno
Bioinformatics 32 (11), 1662-1669, 2016
72016
RNA motif search with data-driven element ordering
L Rampášek, RM Jimenez, A Lupták, T Vinař, B Brejová
BMC bioinformatics 17 (1), 1-10, 2016
52016
TensorFlow: Biology’s Gateway to Deep Learning? Cell Systems, 2 (1), 12–14
L Rampasek, A Goldenberg
52016
KuLGaP: A Selective Measure for Assessing Therapy Response in Patient-Derived Xenografts
J Ortmann, L Rampášek, E Tai, AS Mer, R Shi, C Mascaux, A Fares, ...
bioRxiv, 2020
22020
Latent-variable models for drug response prediction and genetic testing
L Rampášek
University of Toronto, 2020
22020
Modeling post-treatment gene expression change with a deep generative model
L Rampasek, D Hidru, P Smirnov, B Haibe-Kains, A Goldenberg
12017
Pose prediction using 3D deep convolutional neural networks
I Wallach, M Dzamba, S Schrodl, L Rampasek
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 254, 2017
2017
Breaking Advances
FMG Cavalli, M Remke, L Rampasek, J Peacock, DJH Shih, B Luu
cancer 77, 2964-75, 2017
2017
MB-87INTEGRATED GENOMICS REVEALS NOVEL SUBTYPES OF MEDULLOBLASTOMA SUBGROUPS
FMG Cavalli, M Remke, J Reimand, L Rampasek, A Goldenberg, M Taylor, ...
Neuro-Oncology 18 (Suppl 3), iii116, 2016
2016
RNA motif search in genomic sequences
L Rampášek
Bachelor thesis, Faculty of Mathematics, Physics and Informatics, Comenius …, 2010
2010
RNA Motif Search With Data-Driven Element Ordering Supplementary Online Material
L Rampášek, RM Jimenez, A Lupták, T Vinar, B Brejová
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