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Robert M. Hamilton

dblp:156/1710 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-5344-1278ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 50% Bioinformatics and computational biology · 50%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cell-cell communication
0.212014
Automated microrobotic characterization of cell-cell communication · ICRA 2014
Robotics › Robot manipulation
micromanipulation
0.112014
Automated microrobotic characterization of cell-cell communication · ICRA 2014

Methods — techniques the papers use, named apart from their topics

vision-based control · 0.4gap junction quantification · 0.4
YearPublicationVenuePosition
2014 Automated microrobotic characterization of cell-cell communication
abstract
Most mammalian cells (e.g., cancer cells and cardiomyocytes) adhere to a culturing surface. Compared to robotic injection of suspended cells (e.g., embryos and oocytes), fewer attempts were made to automate the injection of adherent cells due to their smaller size, highly irregular morphology, small thickness (a few micrometers thick), and large variations in thickness across cells. This paper presents a recently developed robotic system for automated microinjection of adherent cells. The system is embedded with several new capabilities: automatically locating micropipette tips; robustly detecting the contact of micropipette tip with cell culturing surface and directly with cell membrane; and precisely compensating for accumulative positioning errors. These new capabilities make it practical to perform adherent cell microinjection truly via computer mouse clicking in front of a computer monitor, on hundreds and thousands of cells per experiment (vs. a few to tens of cells as state-of-the-art). System operation speed, success rate, and cell viability rate were quantitatively evaluated based on robotic microinjection of over 4,000 cells. This paper also reports the use of the new robotic system to perform cell-cell communication studies using large sample sizes. The gap junction function in a cardiac muscle cell line (HL-1 cells), for the first time, was quantified with the system.
Jun Liu 0007, Vinayakumar Siragam, Clement Leung, Zhe Lu, Changhai Ru, Shaorong Xie, Jun Luo 0006, Robert M. Hamilton, Yu Sun 0001
ICRA10