J. Tanevski

发表

Spatial multi-omic map of human myocardial infarction

Junedh M. Amrute, M. Morshuis, L. V. Van Laake, 2020, Nature.

Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data

Christian H. Holland, Brian A. Joughin, D. Lauffenburger, 2020, Genome Biology.

Combinatorial search for selecting the structure of models of dynamical systems with equation discovery

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2020, Eng. Appl. Artif. Intell..

Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data

R. Krause, N. Rajewsky, P. Qiu, 2020, Life Science Alliance.

SUMO-Supermodeling by combining imperfect models Year 2 Report-Workpackage 7

P. Panov, L. Todorovski, J. Tanevski, 2012 .

Explainable multi-view framework for dissecting intercellular signaling from highly multiplexed spatial data

Julio Saez-Rodriguez, Jovan Tanevski, Attila Gabor, 2020, bioRxiv.

Deep Spatial Profiling of COVID-19 Brains Reveals Neuroinflammation by Compartmentalized Local Immune Cell Interactions and Targets for Intervention

J. Sáez-Rodríguez, K. Knobeloch, M. Prinz, 2020, SSRN Electronic Journal.

DOT: Fast Cell Type Decomposition of Spatial Omics by Optimal Transport

J. Sáez-Rodríguez, J. Tanevski, L. Vale-Silva, 2023, ArXiv.

Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data

Christian H. Holland, D. Lauffenburger, O. Stegle, 2020, Genome Biology.

Robustness and applicability of functional genomics tools on scRNA-seq data

Douglas A. Lauffenburger, Julio Saez-Rodriguez, Oliver Stegle, 2019, bioRxiv.

Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data

Ke Xu, Thomas Yu, Julio Saez-Rodriguez, 2019, bioRxiv.

Explainable multiview framework for dissecting spatial relationships from highly multiplexed data

J. Sáez-Rodríguez, J. Tanevski, A. Gábor, 2022, Genome Biology.

Deep spatial profiling of human COVID-19 brains reveals neuroinflammation with distinct microanatomical microglia-T-cell interactions

J. Saez-Rodriguez, K. Knobeloch, C. Stadelmann, 2021, Immunity.

Explainable multi-view framework for dissecting intercellular signaling from highly multiplexed spatial data

J. Saez-Rodriguez, J. Tanevski, A. Gábor, 2020, bioRxiv.

APPROXIMATE BAYESIAN PARAMETER INFERENCE FOR DYNAMICAL SYSTEMS IN SYSTEMS BIOLOGY

Sašo Džeroski, Jovan Tanevski, Ljupčo Kocarev, 2017 .

Decoupling approximation robustly reconstructs directed dynamical networks pdf

Zoran Levnajic, Bernard Zenko, Saso Dzeroski, 2017, New Journal of Physics.

Multi-level information fusion for learning a blood pressure predictive model using sensor data

Gregor Papa, Jovan Tanevski, Tome Eftimov, 2020, Inf. Fusion.

Process-Based Modeling and Design of Dynamical Systems

Saso Dzeroski, Nikola Simidjievski, Jovan Tanevski, 2017, ECML/PKDD.

Process-based design of dynamical biological systems

Sašo Džeroski, Jovan Tanevski, Ljupčo Todorovski, 2016, Scientific Reports.

Learning stochastic process-based models of dynamical systems from knowledge and data

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2016, BMC Systems Biology.

Domain-specific model selection for structural identification of the Rab5-Rab7 dynamics in endocytosis

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2015, BMC Systems Biology.

Inductive Process Modeling of Rab5-Rab7 Conversion in Endocytosis

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2013, Discovery Science.

Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations

S. Džeroski, Jennifer Adams, J. Tanevski, 2022, Machine Learning.

DOT: A flexible multi-objective optimization framework for transferring features across single-cell and spatial omics

J. Sáez-Rodríguez, J. Tanevski, L. Vale-Silva, 2023, 2301.01682.

Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2019, IEEE Access.

General Meta-Model Framework for Surrogate-Based Numerical Optimization

Saso Dzeroski, Jovan Tanevski, Ljupco Todorovski, 2017, DS.

LIANA+: an all-in-one cell-cell communication framework

J. Saez-Rodriguez, J. Tanevski, Aurélien Dugourd, 2023, bioRxiv.

Predictive model for the quantitative analysis of human skin using photothermal radiometry and diffuse reflectance spectroscopy.

Boris Majaron, Sašo Džeroski, Jovan Tanevski, 2020, Biomedical optics express.

Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results

J. Saez-Rodriguez, J. Tanevski, A. Gábor, 2023, bioRxiv.

DOT: A flexible multi-objective optimization framework for transferring features across single-cell and spatial omics

J. Sáez-Rodríguez, J. Tanevski, L. Vale-Silva, 2023, 2301.01682.

Hybrid technique for characterization of human skin using a combined machine learning and inverse Monte Carlo approach

Boris Majaron, Jovan Tanevski, Sašo Džeroski, 2019, European Conference on Biomedical Optics.

A machine-learning model for quantitative characterization of human skin using photothermal radiometry and diffuse reflectance spectroscopy

Boris Majaron, Jovan Tanevski, Nina Verdel, 2019, BiOS.

Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite

Saso Dzeroski, Jovan Tanevski, Jennifer Adams, 2020, DS.

Spatial omics of acute myocardial infarction reveals a novel mode of immune cell infiltration

Miguel A. Ibarra-Arellano, J. Tanevski, J. Amrute, 2024, bioRxiv.