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Identification of kidney cell types in scRNA-seq and snRNA-seq data using machine learning algorithms2024 Heliyon article Biochemistry, Genetics and Molecular Biology Single-cell and spatial transcriptomics Open access
Adam Tisch, Siddharth Madapoosi, Stephen R. Blough, Jan Rosa, Sean F. Eddy, Laura H. Mariani, +9 more
3citations -
NS-Forest: A machine learning method for the objective identification of minimum marker gene combinations for cell type determination from single cell RNA sequencing2020 bioRxiv (Cold Spring Harbor Laboratory) preprint Biochemistry, Genetics and Molecular Biology Single-cell and spatial transcriptomics Open access
Brian D. Aevermann, Yun Zhang, Mark A. Novotny, Trygve E. Bakken, Jeremy A. Miller, Rebecca D. Hodge, +3 more
12citations -
Identification of Kidney Cell Types in scRNA-seq and snRNA-seq Data Using Machine Learning Algorithms2024 Research Square preprint Biochemistry, Genetics and Molecular Biology Single-cell and spatial transcriptomics Open access
Adam Tisch, Siddharth Madapoosi, Jan Rosa, Sean F. Eddy, Laura H. Mariani, Abhijit S. Naik, +8 more
2citations -
Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types
Chiara Maria Lavinia Loeffler, Omar S. M. El Nahhas, Hannah Sophie Muti, Zunamys Itzell Carrero, Tobias Seibel, Marko van Treeck, +10 more
22citations -
Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study
Chiara Maria Lavinia Loeffler, Omar S. M. El Nahhas, Hannah Sophie Muti, Tobias Seibel, Didem Çifçi, Marko van Treeck, +9 more
12citations -
A combination of immune cell types identified through ensemble machine learning strategy detects altered profile in recurrent pregnancy loss: a pilot study
Marilen Benner, Dorien Feyaerts, Alejandro Lopez‐Rincon, Olivier W.H. van der Heijden, Marie‐Louise van der Hoorn, Irma Joosten, +2 more
11citations -
Predicting Mutational Status of Driver and Suppressor Genes Directly from Histopathology With Deep Learning: A Systematic Study Across 23 Solid Tumor Types
Chiara Maria Lavinia Loeffler, Nadine Therese Gaisa, Hannah Sophie Muti, Marko van Treeck, Amelie Echle, Narmin Ghaffari Laleh, +5 more
26citations -
Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn2022 Frontiers in Computational Neuroscience article Neuroscience Neural dynamics and brain function Open access
Alper Yegenoglu, Anand Subramoney, Thorsten Hater, Cristian Jimenez-Romero, Wouter Klijn, Aarón Pérez Martín, +4 more
9citations -
A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes2025 Frontiers in Nutrition article Health Professions Artificial Intelligence in Healthcare Open access
Shuheng Yang, Ralf Weiskirchen, Wenjing Zheng, Xiaobo Hu, Zhiguo Liu, Hualin Wang
5citations -
A machine learning method for the discovery of minimum marker gene combinations for cell type identification from single-cell RNA sequencing2021 Genome Research preprint Biochemistry, Genetics and Molecular Biology Single-cell and spatial transcriptomics Open access
Brian D. Aevermann, Yun Zhang, Mark A. Novotny, Mohamed Keshk, Trygve E. Bakken, Jeremy A. Miller, +4 more
96citations -
Supervised machine learning versus expert assessment of ultrastructural changes in wild-type and OGT knockout macrophages2026 bioRxiv (Cold Spring Harbor Laboratory) preprint Biochemistry, Genetics and Molecular Biology Cell Image Analysis Techniques Open access
Thijs van der Meer, Graham A. Heieis, Bart Everts, Frank G. A. Faas, Roman I. Koning
0citations -
Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models2023 Nature Biotechnology article Biochemistry, Genetics and Molecular Biology Bioinformatics and Genomic Networks Open access
Rosa Lundbye Allesøe, Agnete Troen Lundgaard, Ricardo Hernández Medina, Alejandro Aguayo‐Orozco, Joachim Johansen, Jakob Nybo Nissen, +94 more
109citations -
16:10-16:20 A combination of immune cell types identified through ensemble machine learning strategy detects altered profile in recurrent pregnancy loss2023 Journal of Reproductive Immunology article Immunology and Microbiology Reproductive System and Pregnancy Open access
Marilen Benner, Dorien Feyaerts, Alejandro Lopez‐Rincon, Olivier W.H. van der Heijden, Marie‐Louise van der Hoorn, Irma Joosten, +2 more
0citations -
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, +4 more
12citations