The fruit fly Drosophila Melanogaster has become a model organism in the study of neurobiology and behavior patterns. The analysis of the way the fly moves and its behavior is of great scientific interest for research on aspects such as drug tolerance, aggression or ageing in humans. In this article, a procedure for detecting, identifying and tracking numerous specimens of Drosophila by means of computer vision-based sensing systems is presented. This procedure allows dynamic information about each specimen to be collected at each moment, and then for its behavior to be quantitatively characterized. The proposed algorithm operates in three main steps: a pre-processing step, a detection and segmentation step, and tracking shape. The pre-processing and segmentation steps allow some limits of the image acquisition system and some visual artifacts (such as shadows and reflections) to be dealt with. The improvements introduced in the tracking step allow the problems corresponding to identity loss and swaps, caused by the interaction between individual flies, to be solved efficiently. Thus, a robust method that compares favorably to other existing methods is obtained.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570375 | PMC |
| http://dx.doi.org/10.3390/s150819369 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
for an automated quantitative analysis of fibers orientation and organization in biological fibrous tissues.
Front Bioeng Biotechnol
January 2025
Department of Biomedical Engineering, The City College of New York, New York, NY, United States.
Many biological fibrous tissues exhibit distinctive mechanical properties arising from their highly organized fibrous structure. In disease conditions, alterations in the primary components of these fibers, such as type I collagen molecules in bone, tendons, and ligaments, assembly into a disorganized fibers architecture generating a weak and/or brittle material. Being able to quantitatively assess the fibers orientation and organization in biological tissue may help improve our understanding of their contribution to the tissue and organ mechanical integrity, and assess disease progress and therapy effect.
View Article and Find Full Text PDFBIOTIC: a Bayesian framework to integrate single-cell multi-omics for transcription factor activity inference and improve identity characterization of cells.
Brief Bioinform
November 2024
Department of Automation, Xiamen University, Xiang'an South Road, Xiang'an, 361102, Xiamen, Fujian, China.
Understanding cell destiny requires unraveling the intricate mechanism of gene regulation, where transcription factors (TFs) play a pivotal role. However, the actual contribution of TFs, that is TF activity, is not only determined by TF expression, but also accessibility of corresponding chromatin regions. Therefore, we introduce BIOTIC, an advanced Bayesian model with a well-established gene regulation structure that harnesses the power of single-cell multi-omics data to model the gene expression process under the control of regulatory elements, thereby defining the regulatory activity of TFs with variational inference.
View Article and Find Full Text PDFEstimating Wingbeat Frequency of Hummingbirds using a No-labeling Learning Computer Vision Approach.
Integr Comp Biol
January 2025
Centro de investigación Colibrí Gorriazul, Cundinamarca, Colombia.
Wingbeat frequency estimation is an important aspect for the study of avian flight, energetics, and behavioral patterns, among others. Hummingbirds, in particular, are ideal subjects to test a method for this estimation due to their fast wing motions and unique aerodynamics, which results from their ecological diversification, adaptation to high-altitude environments, and sexually selected displays. Traditionally, wingbeat frequency measurements have been done via "manual" image/sound processing.
View Article and Find Full Text PDFEvaluating GPT Models for Automated Literature Screening in Wastewater-Based Epidemiology.
ACS Environ Au
January 2025
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States.
Methods to quantitatively synthesize findings across multiple studies is an emerging need in wastewater-based epidemiology (WBE), where disease tracking through wastewater analysis is performed at broad geographical locations using various techniques to facilitate public health responses. Meta-analysis provides a rigorous statistical procedure for research synthesis, yet the manual process of screening large volumes of literature remains a hurdle for its application in timely evidence-based public health responses. Here, we evaluated the performance of GPT-3, GPT-3.
View Article and Find Full Text PDFA review of large language models and autonomous agents in chemistry.
Chem Sci
December 2024
FutureHouse Inc. San Francisco CA USA
Large language models (LLMs) have emerged as powerful tools in chemistry, significantly impacting molecule design, property prediction, and synthesis optimization. This review highlights LLM capabilities in these domains and their potential to accelerate scientific discovery through automation. We also review LLM-based autonomous agents: LLMs with a broader set of tools to interact with their surrounding environment.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!