AIMC Topic: Zebrafish

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Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Scientific reports
Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular...

Emergence of spontaneous assembly activity in developing neural networks without afferent input.

PLoS computational biology
Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in...

A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters.

Nature chemical biology
We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing prote...

How mimetic should a robotic fish be to socially integrate into zebrafish groups?

Bioinspiration & biomimetics
Biomimetic robots are promising tools in animal behavioural studies. If they are socially integrated in a group of animals, they can produce calibrated social stimuli to test the animal responses. However, the design of such social robots is challeng...

Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection.

Sensors (Basel, Switzerland)
Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlyin...

Effect of abiotic and biotic stress factors analysis using machine learning methods in zebrafish.

Comparative biochemistry and physiology. Part D, Genomics & proteomics
In order to understand the mechanisms underlying stress responses, meta-analysis of transcriptome is made to identify differentially expressed genes (DEGs) and their biological, molecular and cellular mechanisms in response to stressors. The present ...

Fuzzy-based propagation of prior knowledge to improve large-scale image analysis pipelines.

PloS one
Many automatically analyzable scientific questions are well-posed and a variety of information about expected outcomes is available a priori. Although often neglected, this prior knowledge can be systematically exploited to make automated analysis op...

A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts.

BMC genomics
BACKGROUND: In recent years, a rapidly increasing number of RNA transcripts has been generated by thousands of sequencing projects around the world, creating enormous volumes of transcript data to be analyzed. An important problem to be addressed whe...

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

Zebrafish
Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in r...

A new cyclic lipopeptide isolated from Bacillus amyloliquefaciens HAB-2 and safety evaluation.

Pesticide biochemistry and physiology
Bacillus is the most widely studied biocontrol agent and has been extensively used in the development of biopesticides and fungicides. In this study, a new cyclic lipopeptide was isolated from Bacillus amyloliquefaciens HAB-2 by column chromatography...