Authors:
Gennady Denisov
;
Tomoko Ohyama
;
Tihana Jovanic
and
Marta Zlatic
Affiliation:
Howard Hughes Medical Institute, United States
Keyword(s):
Animal Behavior, Automated Tracking, High-throughput Detection, Model, Algorithm, Software, Signal Processing, Statistical Analysis, Feature Extraction, Hit Detection.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Signal Processing
;
Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics
Abstract:
Analysis of behaviors of model organisms has a number of applications, particularly to determination of the
function of genes and neurons. Drosophila larva is an especially convenient model system for this kind of
study because of availability of powerful genetic analysis tools and of automated tracking software that allows
high-throughput recording of animal’s shape and position characteristics as time-dependent signals. We have
developed an open source software that allows a high-throughput detection and analysis of a comprehensive set
of meaningful behaviors of this species. Using the recorded signals as input variables and a set of processing
thresholds as parameters, the software employs model-based algorithms to detect the behavioral actions with
high accuracy, typically 1-5%. For each detected action it extracts and stores meaningful quantitative features
that allow statistical discrimination of mutants from wild type animals and set stage for subsequent application
of machine
learning techniques to classification of the mutants.
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