13 citations · 22 across the 7 of their papers we have counts for
8 papers
Multi-center Medical Data Mining with FL-Net - A One-stop Shop for Federated Learning
Simon Süwer, Julian Klemm, Elisa Acitelli +39
Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations. Based on five requirements derived from the literature, w…
Biomedical systems biology workflow orchestration and execution with PoSyMed
Simon Süwer, Zoe Chervontseva, Kester Bagemihl +3
The rapid growth of scientific software has created practical barriers for bioinformatics research. Although powerful statistical, artificial intelligence (AI)-based methods are no…
Conversational No-code, Multi-agentic Disease Module Identification and Drug Repurposing Prediction with ChatDRex
Simon Süwer, Kester Bagemihl, Sylvie Baier +5
Repurposing approved drugs offers a time-efficient and cost-effective alternative to traditional drug development. However, in silico prediction of repurposing candidates is challe…
A Privacy-Preserving Ecosystem for Developing Machine Learning Algorithms Using Patient Data: Insights from the TUM.ai Makeathon
Simon Süwer, Mai Khanh Mai, Christoph Klein +4
The integration of clinical data offers significant potential for the development of personalized medicine. However, its use is severely restricted by the General Data Protection R…
UnPaSt: unsupervised patient stratification by biclustering of omics data
Michael Hartung, Andreas Maier, Yuliya Burankova +25
Unsupervised patient stratification is essential for disease subtype discovery, yet, despite growing evidence of molecular heterogeneity of non-oncological diseases, popular method…
Drugst.One -- A plug-and-play solution for online systems medicine and network-based drug repurposing
Andreas Maier, Michael Hartung, Mark Abovsky +36
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In…
A Platform for the Biomedical Application of Large Language Models
Sebastian Lobentanzer, Shaohong Feng, The BioChatter Consortium +6
Current-generation Large Language Models (LLMs) have stirred enormous interest in recent months, yielding great potential for accessibility and automation, while simultaneously pos…
Democratising Knowledge Representation with BioCypher
Sebastian Lobentanzer, Patrick Aloy, Jan Baumbach +26
Standardising the representation of biomedical knowledge among all researchers is an insurmountable task, hindering the effectiveness of many computational methods. To facilitate h…