Author

Daniel Moreno-Andrés

RWTH Aachen UniversityORCID 0000-0003-2160-448XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 2 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:imaging· 2 Approach:machine learning (classical)· 2 Research Focus:trajectory inference· 2 Research Focus:cell signaling & trafficking· 1

Frequent Co-Authors

Abin JoseiD· 2 shared Johannes StegmaieriD· 2 shared Rijo RoyiD· 2 shared Anja Scheufen· 1 shared Dennis EschweileriD· 1 shared Hideki YokoyamaiD· 1 shared Ina Laube· 1 shared Jian Ma· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Abin JoseORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Cell BiologyJournal of Biological ChemistryPeer-reviewedMay 2, 2025

SART1 localizes to spindle poles forming a SART1 cap and promotes spindle pole assembly

Hideki Yokoyama, Daniel Moreno-Andrés, Kaoru Takizawa…·Yoshikazu Haramoto

This study identifies SART1 as a mitosis-specific microtubule-associated protein that localizes to spindle poles and recruits PCM proteins for spindle assembly.

1 citation

humanmultiple species

𝕏 PostBluesky

BioinformaticsPLoS ONEPeer-reviewedMar 11, 2024

Automatic Detection of Cell-cycle Stages using Recurrent Neural Networks

Abin Jose, Rijo Roy, Daniel Moreno-Andrés, Johannes Stegmaier

This paper proposes an RNN-based method to automatically detect mitosis stages from cell division videos, showing improved performance over traditional classifiers.

8 citations

imagingdeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintNov 1, 2022

END-TO-END CLASSIFICATION OF CELL-CYCLE STAGES WITH CENTER-CELL FOCUS TRACKER USING RECURRENT NEURAL NETWORKS

Abin Jose, Rijo Roy, Dennis Eschweiler…·Johannes Stegmaier

This paper proposes an RNN-based method for automatic cell-cycle stage classification using time-lapse microscopy images, achieving superior performance over a classifier baseline.

2 citations

imagingdeep learning

𝕏 PostBluesky