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Institute for Machine Learning
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Publications 2016

Journals

IBD Sharing between Africans, Neandertals, and Denisovans Genome Biol. Evol. Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery J. Bioinform. Comput. Biol. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development Stat. Appl. Genet. Mol. Biol. Transcriptome profiling of antimicrobial resistance in Pseudomonas aeruginosa Antimicrob. Agents Chemother.
Author(s): Ariane Khaledi, Monika Schniederjans, Sarah Pohl, Roman Rainer, Ulrich Bodenhofer, Boyang Xia, Frank Klawonn, Sebastian Bruchmann, Matthias Preusse, Denitsa Eckweiler, Andreas Dötsch, Susanne Häussler
Published: Antimicrob. Agents Chemother., 60(8):4722-4733, 2016 doi:10.1128/AAC.00075-16, opens an external URL in a new window
Hsa-miR-375 is a predictor of local control in early stage breast cancer Clin. Epigenetics DeepTox: Toxicity Prediction using Deep Learning Front. Environ. Sci.

Conferences

Long Short-Term Memory For Autonomous Driving Cars NIPS
Author(s): Michael Treml, José Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, Felix Friedmann, Peter Schuberth, Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, Ulrich Bodenhofer, Bernhard Nessler, Sepp Hochreiter
Published: Workshop on Machine Learning for Intelligent Transport Systems, Conference Neural Information Processing Systems Foundation (NIPS 2016), December 5-10, 2016
Download: PDF, opens an external URL in a new window
Deep Learning for predicting synergy effects of drug combinations NIPS
Author(s): Kristina Preuer, Günter Klambauer, Sepp Hochreiter
Published: Women in Machine Learning Workshop, Conference Neural Information Processing Systems Foundation (NIPS 2016), December 5-10, 2016
HapRFN: a deep learning method for identifying short IBD segments NIPS
Author(s): Gundula Povysil, Djork-Arné Clevert, Sepp Hochreiter
Published: Women in Machine Learning Workshop, Conference Neural Information Processing Systems Foundation (NIPS 2016), December 5-10, 2016
Speeding up Semantic Segmentation for Autonomous Driving NIPS
Author(s): Michael Treml, José Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, Felix Friedmann, Peter Schuberth, Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, Ulrich Bodenhofer, Bernhard Nessler, Sepp Hochreiter
Published: Workshop on Machine Learning for Intelligent Transport Systems, Conference Neural Information Processing Systems Foundation (NIPS 2016), December 5-10, 2016
Download: PDF, opens an external URL in a new window
panelcn.MOPS: CNV detection in targeted panel sequencing data for diagnostic use ASGH
Author(s): Gundula Povysil, Antigoni Tzika, Julia Vogt, Verena Haunschmid, Ludwine Messiaen, Katharina Wimmer, Günter Klambauer, Sepp Hochreiter
Published: Poster at Annual Meeting of the American Society of Human Genetics (ASHG 2016), Vancouver, Canada, October 18-22, 2016
Download: PDF, opens an external URL in a new window
HapRNF: a deep learning method to identify short IBD segments ASHG
Author(s): Gundula Povysil, Djork-Arné Clevert, Sepp Hochreiter
Published: Poster at Annual Meeting of the American Society of Human Genetics (ASHG 2016), Vancouver, Canada, October 18-22, 2016
Download: PDF, opens an external URL in a new window
Deep Learning for Drug Target Prediction GTC Europe
Author(s): Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter
Published: Poster at GPU Technology Conference Europe (GTC Europe), September 26-29, 2016
Best-Paper Award
Long Short-Term Memory For Autonomous Driving Cars GTC Europe
Author(s): Michael Treml
Published: Poster at GPU Technology Conference Europe (GTC Europe), September 26-29, 2016
Rectified Factor Networks for Biclustering ICLR
Author(s): Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter
Published: Workshop Paper at International Conference on Learning Representations (ICLR 2016), San Juan, Puerto Rico, May 2-4, 2016
Download: PDF, opens an external URL in a new window
Understanding Very Deep Networks via Volume Conservation ICLR
Author(s): Thomas Unterthiner, Sepp Hochreiter
Published: Workshop Paper at International Conference on Learning Representations (ICLR 2016), San Juan, Puerto Rico, May 2-4, 2016
Download: PDF, opens an external URL in a new window
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) ICLR

Books/Book Chapters

Applied Biclustering Methods for Big and High-Dimensional Data Using R Taylor & Francis Group Introduction Applied Biclustering Methods for Big and High-Dimensional Data Using R
Author(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 1-10, 2016
δ-biclustering and FLOC Algorithm Applied Biclustering Methods for Big and High-Dimensional Data Using R The Plaid Model Applied Biclustering Methods for Big and High-Dimensional Data Using R
Author(s): Ziv Shkedy, Ewoud De Troyer, Adetayo Kasim, Sepp Hochreiter, Heather Turner
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 73-88, 2016
FABIA Applied Biclustering Methods for Big and High-Dimensional Data Using R Gene Expression Experiments in Drug Discovery Applied Biclustering Methods for Big and High-Dimensional Data Using R
Author(s): Willem Talloen, Hinrich W.H. Göhlmann, Bie Verbist, Nolen Joy Perualila, Ziv Shkedy, Adetayo Kasim, QSTAR Consortium
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 159-174, 2016
Biclustering Methods in Chemoinformatics and Molecular Modeling Applied Biclustering Methods for Big and High-Dimensional Data Using 
Author(s): Nolen Joy Perualila, Ziv Shkedy, Aakash Chavan Ravindranath, Georgios Drakakis, Sonia Liggi, Andreas Bender, Adetayo Kasim, QSTAR Consortium, Willem Talloen, Hinrich W.H. Göhlmann
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 175-202, 2016
Ranking of Biclusters in Drug Discovery Experiments Applied Biclustering Methods for Big and High-Dimensional Data Using R
Author(s): Nolen Joy Perualila, Ziv Shkedy, Sepp Hochreiter, Djork-Arné Clevert
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 223-238, 2016
HapFABIA: Biclustering for Detecting Identity by Descent Applied Biclustering Methods for Big and High-Dimensional Data Using R The BiclustGUI Package Applied Biclustering Methods for Big and High-Dimensional Data Using R
Author(s): Ewoud De Troyer, Martin Otava, Jitao David Zhang, Setia Pramana, Tatsiana Khamiakova, Sebastian Kaiser, Martin Sill, Aedin Culhane, Daniel Gusenleitner,Pierre Gestraud, Gabor Csardi, Mengsteab Aregay, Sepp Hochreiter, Gunter Klambauer, Djork-Arné Clevert, Tobias Verbeke, Nolen Joy Perualila, Adetayo Kasim, Ziv Shkedy
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 321-348, 2016
biclustGUI Shiny App Applied Biclustering Methods for Big and High-Dimensional Data Using R
Author(s): Ewoud De Troyer, Rudradev Sengupta, Martin Otava, Jitao David Zhang, Sebastian Kaiser, Aedin Culhane, Daniel Gusenleitner, Pierre Gestraud, Gabor Csardi, Sepp Hochreiter, Gunter Klambauer, Djork-Arné Clevert, Nolen Joy Perualila, Adetayo Kasim, Ziv Shkedy
Editor(s): Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
Published: Applied Biclustering Methods for Big and High-Dimensional Data Using R, Taylor & Francis Group, Chapman & Hall/CRC Biostatistics Series, opens an external URL in a new window, ISBN 9781482208238, pp. 373-383, 2016

Theses

Multi-Target Deep Neural Networks for Toxicity Prediction Master Thesis
Published: Master Thesis, 2016
Author(s): Thomas Unterthiner
Long Short-Term Memory and convolutional neural networks for SNV-based phenotype prediction Master Thesis
Published: Master Thesis, 2016
Author(s): Michael Widrich
The Maximum Common Subgraph Kernel For Predicting Kinase Inhibitors Master Thesis
Published: Master Thesis, 2016
Author(s): Sabine Schwandegger
Multiple Sequence Alignment with R Master Thesis
Published: Master Thesis, 2016
Author(s): Enrico Bonatesta, Christoph Kainrath
Parallel Long Short Term Memory LSTM Master Thesis
Published: Master Thesis, 2016
Author(s): Martin Moser
Deep Learning for Drug Combination Synergy Prediction Master Thesis
Published: Master Thesis, 2016
Author(s): Kristina Preuer
Classification of (alternatively) spliced exons using state-of-the-art sequence kernels Master Thesis
Published: Master Thesis, 2016
Author(s): Alexander Kogler
Accurate detection of tumor copy number variations in high-throughput sequencing data Master Thesis
Published: Master Thesis, 2016
Author(s): Patrick Praher
panelcn.MOPS reaches clinical standards as a copy number variation detection tool for targeted panel sequencing Master Thesis
Published: Master Thesis, 2016
Author(s): Verena Haunschmid