BLOMAP: An encoding of amino acids which improves signal peptide cleavage site prediction. - Stefan Maetschke; Michael Towsey; Mikael Bodén (APBC, 2005)

Exploiting Sequence Dependencies in the Prediction of Peroxisomal Proteins. - Mark Wakabayashi; John Hawkins; Stefan Maetschke; Mikael Bodén (IDEAL, 2005)

A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins. - Stefan Maetschke; Marcus Gallagher; Mikael Bodén (CIBCB, 2007)

Topological models of transmembrane proteins for subcellular localization prediction - Stefan R. Maetschke (2007)

Detecting sequence and structure homology via an integrative kernel: A case-study in recognizing enzymes. - Isye Arieshanti; Mikael Bodén; Stefan Maetschke; Fabian A. Buske (CIBCB, 2009)

Exploiting structural and topological information to improve prediction of RNA-protein binding sites. - Stefan Maetschke; Zheng Yuan (BMC Bioinform., 2009)

It's about time: Signal recognition in staged models of protein translocation. - Fabian A. Buske; Stefan Maetschke; Mikael Bodén (Pattern Recognit., 2009)

A visual framework for sequence analysis using n-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)

Gene Ontology-driven inference of protein-protein interactions using inducers. - Stefan Maetschke; Martin Simonsen; Melissa J. Davis; Mark A. Ragan (Bioinform., 2012)

Automatic selection of reference taxa for protein-protein interaction prediction with phylogenetic profiling. - Martin Simonsen; Stefan Maetschke; Mark A. Ragan (Bioinform., 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)

RMaNI: Regulatory Module Network Inference framework. - Piyush B. Madhamshettiwar; Stefan Maetschke; Melissa J. Davis; Mark A. Ragan (BMC Bioinform., 2013)

Supervised, semi-supervised and unsupervised inference of gene regulatory networks. - Stefan Maetschke; Piyush B. Madhamshettiwar; Melissa J. Davis; Mark A. Ragan (Briefings Bioinform., 2014)

Characterizing cancer subtypes as attractors of Hopfield networks. - Stefan Maetschke; Mark A. Ragan (Bioinform., 2014)

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 (ISBI, 2017)

Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoder. - Suman Sedai; Dwarikanath Mahapatra; Sajini Hewavitharanage; Stefan Maetschke; Rahil Garnavi (MICCAI (2), 2017)

nuts-flow/ml: data pre-processing for deep learning. - Stefan Maetschke; Ruwan Bandara Tennakoon; Christian Vecchiola; Rahil Garnavi (CoRR, 2017)

A feature agnostic approach for glaucoma detection in OCT volumes. - Stefan Maetschke; Bhavna Josephine Antony; Hiroshi Ishikawa 005; Rahil Garvani (CoRR, 2018)

Alignment-free inference of hierarchical and reticulate phylogenomic relationships. - Guillaume Bernard 003; Cheong Xin Chan; Yao-ban Chan; Xin-Yi Chua; Yingnan Cong; James M. Hogan; Stefan R. Maetschke; Mark A. Ragan (Briefings Bioinform., 2019)

Inference of visual field test performance from OCT volumes using deep learning. - Stefan Maetschke; Bhavna Josephine Antony; Hiroshi Ishikawa 005; Gadi Wollstein; Joel S. Schuman; Rahil Garnavi (CoRR, 2019)

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 (e-Energy, 2020)

Understanding in Artificial Intelligence. - Stefan Maetschke; David Martinez Iraola; Pieter Barnard; Elaheh ShafieiBavani; Peter Zhong; Ying Xu; Antonio Jimeno-Yepes (CoRR, 2021)