Data Mining mit Prozessdaten (Data Mining with Process Data). - Andreas Schuppert; Rainer Perne (Autom., 2005)

An elastic network model to identify characteristic stress response genes. - Sebastian Schneckener; Linus Görlitz; Heidrun Ellinger-Ziegelbauer; Hans-Jürgen Ahr; Andreas Schuppert (Comput. Biol. Chem., 2010)

Robust PBPK/PD-Based Model Predictive Control of Blood Glucose. - Stephan Schaller; Jörg Lippert; Lukas Schaupp; Thomas R. Pieber; Andreas Schuppert; Thomas Eissing (IEEE Trans. Biomed. Eng., 2016)

The SYMBIONT project: symbolic methods for biological networks. - François Boulier; François Fages; Ovidiu Radulescu; Satya Swarup Samal; Andreas Schuppert; Werner M. Seiler; Thomas Sturm 001; Sebastian Walcher; Andreas Weber 004 (ACM Commun. Comput. Algebra, 2018)

Markov-Chain Monte-Carlo methods and non-identifiabilities. - Christian Müller; Fabian Weysser; Thomas Mrziglod; Andreas Schuppert (Monte Carlo Methods Appl., 2018)

A systematic atlas of chaperome deregulation topologies across the human cancer landscape. - Ali Hadizadeh Esfahani; Angelina Sverchkova; Julio Saez-Rodriguez; Andreas Schuppert; Marc Brehme (PLoS Comput. Biol., 2018)

FORESEE: a tool for the systematic comparison of translational drug response modeling pipelines. - Lisa-Katrin Turnhoff; Ali Hadizadeh Esfahani; Maryam Montazeri; Nina Kusch; Andreas Schuppert (Bioinform., 2019)

Critical Transitions in Intensive Care Units: A Sepsis Case Study. - Pejman Farhadi Ghalati; Satya Swarup Samal; Jayesh Sudhir Bhat; Robert Deisz; Gernot Marx; Andreas Schuppert (CoRR, 2019)

Quality-targeting dynamic optimization of monoclonal antibody production. - Chrysoula Dimitra Kappatou; Alireza Ehsani; Sebastian Niedenführ; Adel Mhamdi; Andreas Schuppert; Alexander Mitsos (Comput. Chem. Eng., 2020)

A neural network assisted Metropolis adjusted Langevin algorithm. - Christian Müller; Holger Diedam; Thomas Mrziglod; Andreas Schuppert (Monte Carlo Methods Appl., 2020)

Methodological challenges in translational drug response modeling in cancer: A systematic analysis with FORESEE. - Lisa-Katrin Turnhoff; Ali Hadizadeh Esfahani; Andreas Schuppert (PLoS Comput. Biol., 2020)

Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care. - Arne Peine; Ahmed Hallawa; Johannes Bickenbach; Guido Dartmann; Lejla Begic Fazlic; Anke Schmeink; Gerd Ascheid; Christoph Thiemermann; Andreas Schuppert; Ryan Kindle; Leo A. Celi; Gernot Marx; et al. (npj Digit. Medicine, 2021)

Lessons learned on using High-Performance Computing and Data Science Methods towards understanding the Acute Respiratory Distress Syndrome (ARDS). - Chadi Barakat; Sebastian Johannes Fritsch; Konstantin Sharafutdinov; G. Ingólfsson; Andreas Schuppert; Sigurður Brynjólfsson; Morris Riedel (MIPRO, 2022)

HybridML: Open source platform for hybrid modeling. - Kilian Merkelbach; Artur M. Schweidtmann; Younes Müller; Patrick Schwoebel; Adel Mhamdi; Alexander Mitsos; Andreas Schuppert; Thomas Mrziglod; Sebastian Schneckener (Comput. Chem. Eng., 2022)

Application of convex hull analysis for the evaluation of data heterogeneity between patient populations of different origin and implications of hospital bias in downstream machine-learning-based data processing: A comparison of 4 critical-care patient datasets. - Konstantin Sharafutdinov; Jayesh Sudhir Bhat; Sebastian Johannes Fritsch; Kateryna Nikulina; Moein E. Samadi; Richard Polzin; Hannah Mayer; Gernot Marx; Johannes Bickenbach; Andreas Schuppert (Frontiers Big Data, 2022)

Enabling Hyperparameter-Tuning of AI Models for Healthcare using the CoE RAISE Unique AI Framework for HPC. - Morris Riedel; Chadi Barakat; Sebastian Johannes Fritsch; Marcel Aach; J. Busch; Andreas Lintermann; Andreas Schuppert; Sigurður Brynjólfsson; Helmut Neukirchen; Matthias Book (MIPRO, 2023)

Tree-Based Learning on Amperometric Time Series Data Demonstrates High Accuracy for Classification. - Jeyashree Krishnan; Zeyu Lian; Pieter E. Oomen; Xiulan He; Soodabeh Majdi; Andreas Schuppert; Andrew Ewing (CoRR, 2023)

CMDA: a tool for Continuous Monitoring Data Analysis. - Pejman Farhadi Ghalati; Andreas Schuppert (CoRR, 2023)

Neural network input feature selection using structured l2 - norm penalization. - Nathaniel Egwu; Thomas Mrziglod; Andreas Schuppert (Appl. Intell., 2023)

Diagnostic Expert Advisor: A platform for developing machine learning models on medical time-series data. - Richard Polzin; Sebastian Johannes Fritsch; Konstantin Sharafutdinov; Gernot Marx; Andreas Schuppert (SoftwareX, 2023)

Smooth Kolmogorov Arnold networks enabling structural knowledge representation. - Moein E. Samadi; Younes Müller; Andreas Schuppert (CoRR, 2024)

Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions. - Moein E. Samadi; Hedieh Mirzaieazar; Alexander Mitsos; Andreas Schuppert (BMC Bioinform., 2024)