Stefan Maetschke

According to our database, Stefan Maetschke authored at least 22 papers between 2005 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Understanding in Artificial Intelligence.

Stefan Maetschke, David Martinez Iraola, Pieter Barnard, Elaheh ShafieiBavani, Peter Zhong, Ying Xu, Antonio Jimeno-Yepes

CoRR, 2021

2020

Using Satellite and Aerial Imagery for Identification of Solar PV: State of the Art and Research Opportunities.

Julian de Hoog, Stefan Maetschke, Peter Ilfrich, Ramachandra Rao Kolluri

Proceedings of the e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems, 2020

2019

Inference of visual field test performance from OCT volumes using deep learning.

Stefan Maetschke, Bhavna Josephine Antony, Hiroshi Ishikawa, Gadi Wollstein, Joel S. Schuman, Rahil Garnavi

CoRR, 2019

Alignment-free inference of hierarchical and reticulate phylogenomic relationships.

Guillaume Bernard, Cheong Xin Chan, Yao-ban Chan, Xin-Yi Chua, Yingnan Cong, James M. Hogan, Stefan R. Maetschke, Mark A. Ragan

Briefings Bioinform., 2019

2018

A feature agnostic approach for glaucoma detection in OCT volumes.

Stefan Maetschke, Bhavna Josephine Antony, Hiroshi Ishikawa, Rahil Garvani

CoRR, 2018

2017

nuts-flow/ml: data pre-processing for deep learning.

Stefan Maetschke, Ruwan Bandara Tennakoon, Christian Vecchiola, Rahil Garnavi

CoRR, 2017

Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoder.

Suman Sedai, Dwarikanath Mahapatra, Sajini Hewavitharanage, Stefan Maetschke, Rahil Garnavi

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

A novel hybrid approach for severity assessment of Diabetic Retinopathy in colour fundus images.

Pallab Kanti Roy, Ruwan B. Tennakoon, Khoa Cao, Suman Sedai, Dwarikanath Mahapatra, Stefan Maetschke, Rahil Garnavi

Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

2014

Characterizing cancer subtypes as attractors of Hopfield networks.

Stefan Maetschke, Mark A. Ragan

Bioinform., 2014

Supervised, semi-supervised and unsupervised inference of gene regulatory networks.

Stefan Maetschke, Piyush B. Madhamshettiwar, Melissa J. Davis, Mark A. Ragan

Briefings Bioinform., 2014

2013

RMaNI: Regulatory Module Network Inference framework.

Piyush B. Madhamshettiwar, Stefan Maetschke, Melissa J. Davis, Mark A. Ragan

BMC Bioinform., 2013

2012

mCOPA: analysis of heterogeneous features in cancer expression data.

Chenwei Wang, Alperen Taciroglu, Stefan Maetschke, Colleen C. Nelson, Mark A. Ragan, Melissa J. Davis

J. Clin. Bioinform., 2012

Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling.

Martin Simonsen, Stefan Maetschke, Mark A. Ragan

Bioinform., 2012

Gene Ontology-driven inference of protein-protein interactions using inducers.

Stefan Maetschke, Martin Simonsen, Melissa J. Davis, Mark A. Ragan

Bioinform., 2012

2010

A visual framework for sequence analysis using <i>n</i>-grams and spectral rearrangement.

Stefan Maetschke, Karin S. Kassahn, Jasmyn A. Dunn, Siew-Ping Han, Eva Z. Curley, Katryn J. Stacey, Mark A. Ragan

Bioinform., 2010

2009

It's about time: Signal recognition in staged models of protein translocation.

Fabian A. Buske, Stefan Maetschke, Mikael Bodén

Pattern Recognit., 2009

Exploiting structural and topological information to improve prediction of RNA-protein binding sites.

Stefan Maetschke, Zheng Yuan

BMC Bioinform., 2009

Detecting sequence and structure homology via an integrative kernel: A case-study in recognizing enzymes.

Isye Arieshanti, Mikael Bodén, Stefan Maetschke, Fabian A. Buske

Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2009

2007

Topological models of transmembrane proteins for subcellular localization prediction

Stefan R. Maetschke

PhD thesis, 2007

A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins.

Stefan Maetschke, Marcus Gallagher, Mikael Bodén

Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2007

2005

Exploiting Sequence Dependencies in the Prediction of Peroxisomal Proteins.

Mark Wakabayashi, John Hawkins, Stefan Maetschke, Mikael Bodén

Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

BLOMAP: An encoding of amino acids which improves signal peptide cleavage site prediction.

Stefan Maetschke, Michael Towsey, Mikael Bodén

Proceedings of 3rd Asia-Pacific Bioinformatics Conference, 17-21 January 2005, Singapore, 2005