Daniel Marcato

Karlsruhe Institute of Technology

Papers

2

Total Citations

12

H-Index

2

About

Daniel Marcato is a researcher at the forefront of high-throughput behavioral phenotyping in zebrafish, a key model organism for vertebrate biology and drug discovery. His work centers on developing automated, imaging-based platforms to replace manual experimentation, dramatically improving the accuracy, reproducibility, and scalability of behavioral assays. Marcato’s major contributions include the design of an automated system for quantifying touch-response in zebrafish larvae, a critical behavior linking genetics to drug effects. This system, detailed in his most-cited 2021 paper (9 citations), addresses the bottleneck of low-throughput manual testing, enabling more reliable genetic and pharmacological screens. His earlier 2018 work on imaging platforms for early zebrafish phenotypic characterization (3 citations) laid the groundwork for these advancements, focusing on automated image analysis to capture subtle morphological and behavioral traits. By integrating robotics, computer vision, and behavioral science, Marcato is helping to transform zebrafish research into a high-throughput, reproducible discipline, accelerating discoveries in neurobiology, toxicology, and drug development. His innovations promise to deepen our understanding of vertebrate biology and improve the efficiency of preclinical therapeutic testing.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
An Automated Experimentation System for the Touch-Response Quantification of Zebrafish Larvae
9 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Karlsruhe Institute of Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago