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Hannes Bretschneider
Hannes Bretschneider
Donnelly Centre and Department of Molecular Genetics, University of Toronto
Dirección de correo verificada de utoronto.ca
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The human splicing code reveals new insights into the genetic determinants of disease
HY Xiong, B Alipanahi, LJ Lee, H Bretschneider, D Merico, RKC Yuen, ...
Science 347 (6218), 1254806, 2015
13902015
Critical Assessment of Automated Flow-Cytometry Analysis Techniques
N Aghaeepour, G Finak, the FlowCAP Consortium, the Dream Consortium, ...
Nature Methods 10, 228–238, 2013
6442013
Systems and methods for classifying, prioritizing and interpreting genetic variants and therapies using a deep neural network
B Frey, MKK Leung, AT Delong, HY Xiong, B Alipanahi, LJ Lee, ...
US Patent 10,185,803, 2019
952019
COSSMO: predicting competitive alternative splice site selection using deep learning
H Bretschneider, S Gandhi, AG Deshwar, K Zuberi, BJ Frey
Bioinformatics 34 (13), i429-i437, 2018
552018
Probabilistic estimation of short sequence expression using RNA-Seq data and the “positional bootstrap”
HY Xiong, LJ Lee, H Bretschneider, J Gao, N Jojic, BJ Frey
bioRxiv, 046474, 2016
42016
Systems and Methods for Determining Effects of Genetic Variation of Splice Site Selection
B Frey, H Bretschneider
US Patent App. 16/571,335, 2020
12020
Systems and methods for classifying, prioritizing and interpreting genetic variants and therapies using a deep neural network
B Frey, MKK Leung, AT Delong, HY Xiong, B Alipanahi, LJ Lee, ...
US Patent 11,887,696, 2024
2024
Systems and methods for classifying, prioritizing and interpreting genetic variants and therapies using a deep neural network
B Frey, MKK Leung, AT Delong, HY Xiong, B Alipanahi, LJ Lee, ...
US Patent App. 17/369,499, 2021
2021
Alternative Splice Site Prediction with Deep Learning
H Bretschneider
University of Toronto (Canada), 2019
2019
Automatic determination of the number of mixture components in Flow Cytometry with Variational Bayes
H Bretschneider, A Roth
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