Andreas Leha

发表

Frontmatter, Table of Contents, Preface, Conference Organization

Martin Kollmar, Edgar Wingender, Tim Beißbarth, 2013, German Conference on Bioinformatics.

Statistical Methods to Enhance Clinical Prediction with High-Dimensional Data and Ordinal Response

Andreas Leha, A. Leha, 2015 .

Accelerating Simulations in R using Automatically Generated GPGPU-Code

Frank Kramer, Andreas Leha, Tim Beissbarth, 2011 .

Sequential interim analyses of survival data in DNA microarray experiments

Tim Beißbarth, Andreas Leha, Klaus Jung, 2011, BMC Bioinformatics.

Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer

Tim Beißbarth, Frank Kramer, Andreas Leha, 2020, Genome Medicine.

Parallelizing scientific code with invasive interactive parallelization: a case study with reuseware

Andreas Leha, Mikhail Chalabine, Christoph Kessler, 2008, CBHPC '08.

Utilizing Molecular Network Information via Graph Convolutional Neural Networks to Predict Metastatic Event in Breast Cancer

Frank Kramer, Andreas Leha, Tim Beissbarth, 2019, GMDS.

Optimization of simulated production process performance using machine learning

Dejan Pangercic, Thomas Rühr, Michael Beetz, 2009, 2009 IEEE Conference on Emerging Technologies & Factory Automation.

Utilization of ordinal response structures in classification with high-dimensional expression data

Tim Beißbarth, Andreas Leha, Klaus Jung, 2013, GCB.

Bioinformatic Methods and Resources for Biomarker Discovery, Validation, Development, and Integration

Tim Beißbarth, Andreas Leha, Júlia Perera-Bel, 2018, Predictive Biomarkers in Oncology.

A machine learning approach for the prediction of pulmonary hypertension

Ajay Shah, Andreas Leha, Tim Seidler, 2019, PloS one.

Epidermal Growth Factor Signaling Promotes Sleep through a Combined Series and Parallel Neural Circuit

Andreas Leha, Wagner Steuer Costa, Alexander Gottschalk, 2019, Current Biology.

Identifying the genetic basis of variation in cell behaviour in human iPS cell lines from healthy donors

Nicholas M. Luscombe, Anna Laddach, Franca Fraternali, 2018, bioRxiv.

Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression

John C. Marioni, Ewan Birney, Daniel D. Seaton, 2020, Nature Communications.