Automated Experimentation


Automated Experimentation

Publisher: BioMed Central

Automated Experimentation is an open access journal that encompasses
high-quality research on all aspects of the automation of clusters of
experiments for high throughput, particularly (but not exclusively) in
the fields of biomedicine and biomedical informatics.

Automated Experimentation aims to provide a platform for biomedical
and informatics researchers to develop, execute, reuse, share, revise,
and recombine their automated experimentation processes or protocols.
There is no substitute for scientific experimentation in discovering
new reliable knowledge however experimentation is highly expensive.
Therefore it is desirable to automate the execution of a cluster of
experiments according to pre-specified computational protocols. With
recent and ongoing developments in engineering (e.g. Labs-on-a-chip),
laboratory robotics, and informatics, automated experimentation is
crucial for expediting large-scale research like systems biology and
translational medicine.

Automated Experimentation features the methodology, protocols, and
significant results of automated experiments for easy sharing among
laboratories worldwide.

Automated Experimentation covers all fields that are related to high-
throughput and automated experimentation. Topical areas include (but
are not limited to):

* Use of experiment protocols and scientific workflows
* Representing experiment protocols, apparatus and data in domain-
specific languages
* Verification and validation methods
* Instrument, apparatus or robotic setups
* Robot scientists and intelligent experimentation systems
* Web-based and computational experimentation
* Software for automating the experiment process
* Biomedical and clinical experimentation
* Scientific findings obtained by automated experiments
* Knowledge sharing infrastructures applied to experimentation
* eScience and eResearch
* Philosophy, theories and formalisms
* Methods of hypothesis generation
* Capturing the process of arguments in automated experiments

ISSN: 1759-4499

Manuscript submission via online system.


Dr Siu-wai Leung, PhD
Assistant Professor
University of Macau


Professor David Robertson, PhD
University of Edinburgh
United Kingdom


Dr Dietlind Gerloff, PhD
Assistant Professor
University of California, Santa Cruz
Santa Cruz
United States


Abstracts available online. Articles available in HTML and PDF format.

Current Issue: Volume 1:4 (29 October 2009)

Date: 2 November 2009

Open Access: 
Original posting date: 
Monday, November 2, 2009
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