Neural Networks and Cellular Automata Complexity. - Jan Gorodkin; Allan Sørensen; Ole Winther (Complex Syst., 1993)

A Quantitative Study Of Pruning By Optimal Brain Damage. - Jan Gorodkin; Lars Kai Hansen; Anders Krogh; Claus Svarer; Ole Winther (Int. J. Neural Syst., 1993)

The Effect of Correlated Input Data on the Dynamics of Learning. - Søren Halkjær; Ole Winther (NIPS, 1996)

A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks. - Manfred Opper; Ole Winther (NIPS, 1996)

Bayesian online learning in the perceptron. - Ole Winther; Sara A. Solla (ESANN, 1997)

Mean Field Methods for Classification with Gaussian Processes. - Manfred Opper; Ole Winther (NIPS, 1998)

Efficient Approaches to Gaussian Process Classification. - Lehel Csató; Ernest Fokoué; Manfred Opper; Bernhard Schottky; Ole Winther (NIPS, 1999)

Ensemble Learning and Linear Response Theory for ICA. - Pedro A. d. F. R. Højen-Sørensen; Ole Winther; Lars Kai Hansen (NIPS, 2000)

Computing with Finite and Infinite Networks. - Ole Winther (NIPS, 2000)

Gaussian Processes for Classification: Mean-Field Algorithms. - Manfred Opper; Ole Winther (Neural Comput., 2000)

TAP Gibbs Free Energy, Belief Propagation and Sparsity. - Lehel Csató; Manfred Opper; Ole Winther (NIPS, 2001)

Incremental Gaussian Processes. - Joaquin Quiñonero Candela; Ole Winther (NIPS, 2002)

Independent component analysis for understanding multimedia content. - Thomas Kolenda; Lars Kai Hansen; Jan Larsen; Ole Winther (NNSP, 2002)

Analysis of functional neuroimages using ICA with adaptive binary sources. - Pedro A. d. F. R. Højen-Sørensen; Ole Winther; Lars Kai Hansen (Neurocomputing, 2002)

Mean-Field Approaches to Independent Component Analysis. - Pedro A. d. F. R. Højen-Sørensen; Ole Winther; Lars Kai Hansen (Neural Comput., 2002)

Variational Linear Response. - Manfred Opper; Ole Winther (NIPS, 2003)

Tractable inference for probabilistic data models. - Lehel Csató; Manfred Opper; Ole Winther (Complex., 2003)

Approximate Inference in Probabilistic Models. - Manfred Opper; Ole Winther (ALT, 2004)

Low complexity Bayesian single channel source separation. - Thomas Beierholm; Brian Dam Pedersen; Ole Winther (ICASSP (5), 2004)

Expectation Consistent Free Energies for Approximate Inference. - Manfred Opper; Ole Winther (NIPS, 2004)

The EM algorithm in independent component analysis. - Kaare Brandt Petersen; Ole Winther (ICASSP (5), 2005)

Expectation Consistent Approximate Inference. - Manfred Opper; Ole Winther (J. Mach. Learn. Res., 2005)

On the Slow Convergence of EM and VBEM in Low-Noise Linear Models. - Kaare Brandt Petersen; Ole Winther; Lars Kai Hansen (Neural Comput., 2005)

Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm. - Thomas Grotkjær; Ole Winther; Birgitte Regenberg; Jens Nielsen; Lars Kai Hansen (Bioinform., 2006)

On Sphere Detection and Minimum-Phase Prefiltered Reduced-State Sequence Estimation. - Morten Hansen; Ole Winther; Lars P. B. Christensen (GLOBECOM, 2007)

Bayesian independent component analysis: Variational methods and non-negative decompositions. - Ole Winther; Kaare Brandt Petersen (Digit. Signal Process., 2007)

Flexible and efficient implementations of Bayesian independent component analysis. - Ole Winther; Kaare Brandt Petersen (Neurocomputing, 2007)

Semi-Supervised Mean Fields. - Fei Wang 001; Shijun Wang; Changshui Zhang; Ole Winther (AISTATS, 2007)

Particle Filter Inference in an Articulatory-Based Speech Model. - Thomas Beierholm; Ole Winther (IEEE Signal Process. Lett., 2007)

Improving on Expectation Propagation. - Manfred Opper; Ulrich Paquet; Ole Winther (NIPS, 2008)

BayesMD: Flexible Biological Modeling for Motif Discovery. - Man-Hung Eric Tang; Anders Krogh; Ole Winther (J. Comput. Biol., 2008)

JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update. - Jan Christian Bryne; Eivind Valen; Man-Hung Eric Tang; Troels Torben Marstrand; Ole Winther; Isabelle da Piedade; Anders Krogh; Boris Lenhard; Albin Sandelin (Nucleic Acids Res., 2008)

Bayesian Non-negative Matrix Factorization. - Mikkel N. Schmidt; Ole Winther; Lars Kai Hansen (ICA, 2009)

Sofomore: Combined EEG Source and Forward Model Reconstruction. - Carsten Stahlhut; Morten Mørup; Ole Winther; Lars Kai Hansen (ISBI, 2009)

Bayesian Sparse Factor Models and DAGs Inference and Comparison. - Ricardo Henao; Ole Winther (NIPS, 2009)

Perturbation Corrections in Approximate Inference: Mixture Modelling Applications. - Ulrich Paquet; Ole Winther; Manfred Opper (J. Mach. Learn. Res., 2009)

Discovery of Regulatory Elements is Improved by a Discriminatory Approach. - Eivind Valen; Albin Sandelin; Ole Winther; Anders Krogh (PLoS Comput. Biol., 2009)

Multivariate Hawkes process models of the occurrence of regulatory elements. - Lisbeth Carstensen; Albin Sandelin; Ole Winther; Niels Richard Hansen (BMC Bioinform., 2010)

Computing the minimum-phase filter using the QL-factorization. - Morten Hansen; Lars P. B. Christensen; Ole Winther (IEEE Trans. Signal Process., 2010)

Rare Disease Diagnosis as an Information Retrieval Task. - Radu Dragusin; Paula Petcu; Christina Lioma; Birger Larsen; Henrik Jørgensen; Ole Winther (ICTIR, 2011)

Sparse Linear Identifiable Multivariate Modeling. - Ricardo Henao; Ole Winther (J. Mach. Learn. Res., 2011)

Simultaneous EEG Source and Forward Model Reconstruction (SOFOMORE) Using a Hierarchical Bayesian Approach. - Carsten Stahlhut; Morten Mørup; Ole Winther; Lars Kai Hansen (J. Signal Process. Syst., 2011)

Predictive active set selection methods for Gaussian processes. - Ricardo Henao; Ole Winther (Neurocomputing, 2012)

A hierarchical model for ordinal matrix factorization. - Ulrich Paquet; Blaise Thomson; Ole Winther (Stat. Comput., 2012)

FindZebra: A search engine for rare diseases. - Radu Dragusin; Paula Petcu; Christina Lioma; Birger Larsen; Henrik Jørgensen; Ingemar J. Cox; Lars Kai Hansen; Peter Ingwersen; Ole Winther (Int. J. Medical Informatics, 2013)

Perturbative corrections for approximate inference in Gaussian latent variable models. - Manfred Opper; Ulrich Paquet; Ole Winther (J. Mach. Learn. Res., 2013)

HemaExplorer: a database of mRNA expression profiles in normal and malignant haematopoiesis. - Frederik Otzen Bagger; Nicolas Rapin; Kim Theilgaard-Mönch; Bogumil Kaczkowski; Lina A. Thoren; Johan Jendholm; Ole Winther; Bo T. Porse (Nucleic Acids Res., 2013)

Model Selection in Data Analysis Competitions. - David Kofoed Wind; Ole Winther (MetaSel@ECAI, 2014)

Applications of expectation maximization algorithm for coherent optical communication. - Darko Zibar; Ole Winther; Robert Borkowski; Idelfonso Tafur Monroy; Luis Henrique Hecker de Carvalho; Júlio Oliveira (EUSIPCO, 2014)

S-AMP: Approximate message passing for general matrix ensembles. - Burak Çakmak; Ole Winther; Bernard H. Fleury (ITW, 2014)

Bayesian Inference for Structured Spike and Slab Priors. - Michael Riis Andersen; Ole Winther; Lars Kai Hansen (NIPS, 2014)

Protein Secondary Structure Prediction with Long Short Term Memory Networks. - Søren Kaae Sønderby; Ole Winther (CoRR, 2014)

Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures. - Niels H. Christiansen; Per Erlend Torbergsen Voie; Ole Winther; Jan Høgsberg (J. Appl. Math., 2014)

Convolutional LSTM Networks for Subcellular Localization of Proteins. - Søren Kaae Sønderby; Casper Kaae Sønderby; Henrik Nielsen; Ole Winther (AlCoB, 2015)

S-AMP for non-linear observation models. - Burak Çakmak; Ole Winther; Bernard H. Fleury (ISIT, 2015)

Autoencoding beyond pixels using a learned similarity metric. - Anders Boesen Lindbo Larsen; Søren Kaae Sønderby; Ole Winther (CoRR, 2015)

Deep Belief Nets for Topic Modeling. - Lars Maaloe; Morten Arngren; Ole Winther (CoRR, 2015)

A Theory of Solving TAP Equations for Ising Models with General Invariant Random Matrices. - Manfred Opper; Burak Çakmak; Ole Winther (CoRR, 2015)

Recurrent Spatial Transformer Networks. - Søren Kaae Sønderby; Casper Kaae Sønderby; Lars Maaløe; Ole Winther (CoRR, 2015)

Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search. - Marco Fraccaro; Ulrich Paquet; Ole Winther (AAAI, 2016)

Bayesian Generalised Ensemble Markov Chain Monte Carlo. - Jes Frellsen; Ole Winther; Zoubin Ghahramani; Jesper Ferkinghoff-Borg (AISTATS, 2016)

Autoencoding beyond pixels using a learned similarity metric. - Anders Boesen Lindbo Larsen; Søren Kaae Sønderby; Hugo Larochelle; Ole Winther (ICML, 2016)

Auxiliary Deep Generative Models. - Lars Maaløe; Casper Kaae Sønderby; Søren Kaae Sønderby; Ole Winther (ICML, 2016)

Sequential Neural Models with Stochastic Layers. - Marco Fraccaro; Søren Kaae Sønderby; Ulrich Paquet; Ole Winther (NIPS, 2016)

Ladder Variational Autoencoders. - Casper Kaae Sønderby; Tapani Raiko; Lars Maaløe; Søren Kaae Sønderby; Ole Winther (NIPS, 2016)

Self-Averaging Expectation Propagation. - Burak Çakmak; Manfred Opper; Bernard H. Fleury; Ole Winther (CoRR, 2016)

Neural Machine Translation with Characters and Hierarchical Encoding. - Alexander Rosenberg Johansen; Jonas Meinertz Hansen; Elias Khazen Obeid; Casper Kaae Sønderby; Ole Winther (CoRR, 2016)

How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks. - Casper Kaae Sønderby; Tapani Raiko; Lars Maaløe; Søren Kaae Sønderby; Ole Winther (CoRR, 2016)

Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models. - Aki Vehtari; Tommi Mononen; Ville Tolvanen; Tuomas Sivula; Ole Winther (J. Mach. Learn. Res., 2016)

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis. - Frederik Otzen Bagger; Damir Sasivarevic; Sina Hadi Sohi; Linea Gøricke Laursen; Sachin Pundhir; Casper Kaae Sønderby; Ole Winther; Nicolas Rapin; Bo T. Porse (Nucleic Acids Res., 2016)

Deep Recurrent Conditional Random Field Network for Protein Secondary Prediction. - Alexander Rosenberg Johansen; Casper Kaae Sønderby; Søren Kaae Sønderby; Ole Winther (BCB, 2017)

End-to-End Information Extraction without Token-Level Supervision. - Rasmus Berg Palm; Dirk Hovy; Florian Laws; Ole Winther (SCNLP@EMNLP 2017, 2017)

CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks. - Rasmus Berg Palm; Ole Winther; Florian Laws (ICDAR, 2017)

Dynamical functional theory for compressed sensing. - Burak Çakmak; Manfred Opper; Ole Winther; Bernard H. Fleury (ISIT, 2017)

A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning. - Marco Fraccaro; Simon Kamronn; Ulrich Paquet; Ole Winther (NIPS, 2017)

Hash Embeddings for Efficient Word Representations. - Dan Svenstrup; Jonas Meinertz Hansen; Ole Winther (NIPS, 2017)

DeepLoc: prediction of protein subcellular localization using deep learning. - José Juan Almagro Armenteros; Casper Kaae Sønderby; Søren Kaae Sønderby; Henrik Nielsen; Ole Winther (Bioinform., 2017)

An introduction to deep learning on biological sequence data: examples and solutions. - Vanessa Isabell Jurtz; Alexander Rosenberg Johansen; Morten Nielsen 001; José Juan Almagro Armenteros; Henrik Nielsen; Casper Kaae Sønderby; Ole Winther; Søren Kaae Sønderby (Bioinform., 2017)

Semi-Supervised Generation with Cluster-aware Generative Models. - Lars Maaløe; Marco Fraccaro; Ole Winther (CoRR, 2017)

Recurrent Relational Networks for Complex Relational Reasoning. - Rasmus Berg Palm; Ulrich Paquet; Ole Winther (CoRR, 2017)

Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. - Michael Riis Andersen; Aki Vehtari; Ole Winther; Lars Kai Hansen (J. Mach. Learn. Res., 2017)

Gaussian process based independent analysis for temporal source separation in fMRI. - Ditte Høvenhoff Hald; Ricardo Henao; Ole Winther (NeuroImage, 2017)

Bayesian Structure Learning for Dynamic Brain Connectivity. - Michael Riis Andersen; Ole Winther; Lars Kai Hansen; Russell A. Poldrack; Oluwasanmi Koyejo (AISTATS, 2018)

Learning to Plan from Raw Data in Grid-based Games. - Andrea Dittadi; Thomas Bolander; Ole Winther (GCAI, 2018)

Recurrent Relational Networks. - Rasmus Berg Palm; Ulrich Paquet; Ole Winther (NeurIPS, 2018)

Attend, Copy, Parse End-to-end Information Extraction from Documents. - Rasmus Berg Palm; Florian Laws; Ole Winther (ICDAR, 2019)

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling. - Lars Maaløe; Marco Fraccaro; Valentin Liévin; Ole Winther (NeurIPS, 2019)

Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data. - Savvas Kinalis; Finn Cilius Nielsen; Ole Winther; Frederik Otzen Bagger (BMC Bioinform., 2019)

LAVAE: Disentangling Location and Appearance. - Andrea Dittadi; Ole Winther (CoRR, 2019)

Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted Bounds. - Valentin Liévin; Andrea Dittadi; Anders Christensen; Ole Winther (NeurIPS, 2020)

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows. - Didrik Nielsen; Priyank Jaini; Emiel Hoogeboom; Ole Winther; Max Welling (NeurIPS, 2020)

Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow. - Didrik Nielsen; Ole Winther (NeurIPS, 2020)

scVAE: variational auto-encoders for single-cell gene expression data. - Christopher Heje Grønbech; Maximillian Fornitz Vording; Pascal N. Timshel; Casper Kaae Sønderby; Tune H. Pers; Ole Winther; Bonnie Berger (Bioinform., 2020)

On the Transfer of Disentangled Representations in Realistic Settings. - Andrea Dittadi; Frederik Träuble; Francesco Locatello; Manuel Wuthrich; Vaibhav Agrawal; Ole Winther; Stefan Bauer; Bernhard Schölkopf (ICLR, 2021)

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning. - Andrea Dittadi; Frederik Träuble; Manuel Wüthrich; Felix Widmaier; Peter V. Gehler; Ole Winther; Francesco Locatello; Olivier Bachem; Bernhard Schölkopf; Stefan Bauer (CoRR, 2021)

Hierarchical Few-Shot Generative Models. - Giorgio Giannone; Ole Winther (CoRR, 2021)

Image Super-Resolution with Deep Variational Autoencoders. - Darius Chira; Ilian Haralampiev; Ole Winther; Andrea Dittadi; Valentin Liévin (ECCV Workshops (2), 2022)

The Role of Pretrained Representations for the OOD Generalization of RL Agents. - Frederik Träuble; Andrea Dittadi; Manuel Wuthrich; Felix Widmaier; Peter Vincent Gehler; Ole Winther; Francesco Locatello; Olivier Bachem; Bernhard Schölkopf; Stefan Bauer (ICLR, 2022)

Generalization and Robustness Implications in Object-Centric Learning. - Andrea Dittadi; Samuele S. Papa; Michele De Vita; Bernhard Schölkopf; Ole Winther; Francesco Locatello (ICML, 2022)

SCHA-VAE: Hierarchical Context Aggregation for Few-Shot Generation. - Giorgio Giannone; Ole Winther (ICML, 2022)

Inductive Biases for Object-Centric Representations in the Presence of Complex Textures. - Samuele Papa; Ole Winther; Andrea Dittadi (CoRR, 2022)

Few-Shot Diffusion Models. - Giorgio Giannone; Didrik Nielsen; Ole Winther (CoRR, 2022)

NeuralNEB - Neural Networks can find Reaction Paths Fast. - Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Ole Winther (CoRR, 2022)

Transition1x - a Dataset for Building Generalizable Reactive Machine Learning Potentials. - Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Jonas Busk; Ole Winther (CoRR, 2022)

Explainable Image Quality Assessments in Teledermatological Photography. - Raluca Jalaboi; Ole Winther; Alfiia Galimzianova (CoRR, 2022)

Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks. - Jonas Busk; Peter Bjørn Jørgensen; Arghya Bhowmik; Mikkel N. Schmidt; Ole Winther; Tejs Vegge (Mach. Learn. Sci. Technol., 2022)

NetSurfP-3.0: accurate and fast prediction of protein structural features by protein language models and deep learning. - Magnus Haraldson Høie; Erik Nicolas Kiehl; Bent Petersen; Morten Nielsen 001; Ole Winther; Henrik Nielsen; Jeppe Hallgren; Paolo Marcatili (Nucleic Acids Res., 2022)

DeepLoc 2.0: multi-label subcellular localization prediction using protein language models. - Vineet Thumuluri; José Juan Almagro Armenteros; Alexander Rosenberg Johansen; Henrik Nielsen; Ole Winther (Nucleic Acids Res., 2022)

NeuralNEB - neural networks can find reaction paths fast. - Mathias Schreiner; Arghya Bhowmik; Tejs Vegge; Peter Bjørn Jørgensen; Ole Winther (Mach. Learn. Sci. Technol., 2022)

Image-free Classifier Injection for Zero-Shot Classification. - Anders Christensen; Massimiliano Mancini; A. Sophia Koepke; Ole Winther; Zeynep Akata (ICCV, 2023)

Unifying Molecular and Textual Representations via Multi-task Language Modelling. - Dimitrios Christofidellis; Giorgio Giannone; Jannis Born; Ole Winther; Teodoro Laino; Matteo Manica (ICML, 2023)

Variational Open-Domain Question Answering. - Valentin Liévin; Andreas Geert Motzfeldt; Ida Riis Jensen; Ole Winther (ICML, 2023)

Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation. - Giorgio Giannone; Akash Srivastava; Ole Winther; Faez Ahmed (NeurIPS, 2023)

Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics. - Mathias Schreiner; Ole Winther; Simon Olsson (NeurIPS, 2023)

ThoughtSource: A central hub for large language model reasoning data. - Simon Ott; Konstantin Hebenstreit; Valentin Liévin; Christoffer Egeberg Hother; Milad Moradi; Maximilian Mayrhauser; Robert Praas; Ole Winther; Matthias Samwald (CoRR, 2023)

Dermatological Diagnosis Explainability Benchmark for Convolutional Neural Networks. - Raluca Jalaboi; Ole Winther; Alfiia Galimzianova (CoRR, 2023)

Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces. - Jonas Busk; Mikkel N. Schmidt; Ole Winther; Tejs Vegge; Peter Bjørn Jørgensen (CoRR, 2023)

Coherent energy and force uncertainty in deep learning force fields. - Peter Bjørn Jørgensen; Jonas Busk; Ole Winther; Mikkel N. Schmidt (CoRR, 2023)

DermX: An end-to-end framework for explainable automated dermatological diagnosis. - Raluca Jalaboi; Frederik Faye; Mauricio Orbes-Arteaga; Dan Richter Jørgensen; Ole Winther; Alfiia Galimzianova (Medical Image Anal., 2023)

Addressing caveats of neural persistence with deep graph persistence. - Leander Girrbach; Anders Christensen; Ole Winther; Zeynep Akata; A. Sophia Koepke (Trans. Mach. Learn. Res., 2023)

Deorphanizing Peptides Using Structure Prediction. - Felix Teufel; Jan C. Refsgaard; Marina A. Kasimova; Kristine K. Deibler; Christian T. Madsen; Carsten Stahlhut; Mads Grønborg; Ole Winther; Dennis Madsen (J. Chem. Inf. Model., 2023)

RNA trafficking and subcellular localization - a review of mechanisms, experimental and predictive methodologies. - Jun Wang 161; Marc Horlacher; Lixin Cheng; Ole Winther (Briefings Bioinform., 2023)

DeepPeptide predicts cleaved peptides in proteins using conditional random fields. - Felix Teufel; Jan C. Refsgaard; Christian T. Madsen; Carsten Stahlhut; Mads Grønborg; Ole Winther; Dennis Madsen (Bioinform., 2023)

Geometry Fidelity for Spherical Images. - Anders Christensen; Nooshin Mojab; Khushman Patel; Karan Ahuja; Zeynep Akata; Ole Winther; Mar González-Franco; Andrea Colaco (ECCV (80), 2024)

BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks. - Frederikke Isa Marin; Felix Teufel; Marc Horlacher; Dennis Madsen; Dennis Pultz; Ole Winther; Wouter Boomsma (ICLR, 2024)

DiffEnc: Variational Diffusion with a Learned Encoder. - Beatrix Miranda Ginn Nielsen; Anders Christensen; Andrea Dittadi; Ole Winther (ICLR, 2024)

Generative Diffusion Models for Sequential Recommendations. - Sharare Zolghadr; Ole Winther; Paul Jeha (CoRR, 2024)

DeepLocRNA: an interpretable deep learning model for predicting RNA subcellular localization with domain-specific transfer-learning. - Jun Wang 161; Marc Horlacher; Lixin Cheng; Ole Winther (Bioinform., 2024)

Can large language models reason about medical questions? - Valentin Liévin; Christoffer Egeberg Hother; Andreas Geert Motzfeldt; Ole Winther (Patterns, 2024)

Temporal Variational Implicit Neural Representations. - Batuhan Koyuncu; Rachael DeVries; Ole Winther; Isabel Valera (CoRR, 2025)

Bi-Axial Transformers: Addressing the Increasing Complexity of EHR Classification. - Rachael DeVries; Casper Christensen; Marie Lisandra Zepeda Mendoza; Ole Winther (CoRR, 2025)

NetStart 2.0: prediction of eukaryotic translation initiation sites using a protein language model. - Line Sandvad Nielsen; Anders Gorm Pedersen; Ole Winther; Henrik Nielsen (BMC Bioinform., 2025)