AIMC Topic: Drosophila melanogaster

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Neurodynamic modeling of the fruit fly Drosophila melanogaster.

Bioinspiration & biomimetics Sep 14, 2020
This manuscript describes neuromechanical modeling of the fruit fly Drosophila melanogaster in the form of a hexapod robot, Drosophibot, and an accompanying dynamic simulation. Drosophibot is a testbed for real-time dynamical neural controllers model...
Foot Movement Feedback, Sensory Computer Simulation Animals Robotics Walking Biomimetics Insecta Drosophila melanogaster Joints Neural Networks, Computer
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Accurate prediction of DNA N-methylcytosine sites via boost-learning various types of sequence features.

BMC genomics Sep 11, 2020
BACKGROUND: DNA N4-methylcytosine (4mC) is a critical epigenetic modification and has various roles in the restriction-modification system. Due to the high cost of experimental laboratory detection, computational methods using sequence characteristic...
Machine Learning Software Animals Escherichia coli Drosophila melanogaster Caenorhabditis elegans Arabidopsis Cytosine Sequence Analysis, DNA DNA Methylation DNA Epigenome
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EDeepSSP: Explainable deep neural networks for exact splice sites prediction.

Journal of bioinformatics and computational biology Jul 22, 2020
Splice site prediction is crucial for understanding underlying gene regulation, gene function for better genome annotation. Many computational methods exist for recognizing the splice sites. Although most of the methods achieve a competent performanc...
Neural Networks, Computer Animals Deep Learning ROC Curve Humans RNA Splice Sites Arabidopsis Data Visualization Computational Biology Databases, Genetic Drosophila melanogaster
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CytoCensus, mapping cell identity and division in tissues and organs using machine learning.

eLife May 19, 2020
A major challenge in cell and developmental biology is the automated identification and quantitation of cells in complex multilayered tissues. We developed CytoCensus: an easily deployed implementation of supervised machine learning that extends conv...
Automation Drosophila melanogaster Cell Division Tissue Culture Techniques Zebrafish Embryo, Mammalian Animals, Genetically Modified Time-Lapse Imaging Microscopy, Video Organoids Animals Male Larva Time Factors Image Processing, Computer-Assisted Mice Mutation Retina Phenotype Brain Female Reproducibility of Results Machine Learning
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MMPdb and MitoPredictor: Tools for facilitating comparative analysis of animal mitochondrial proteomes.

Mitochondrion Jan 20, 2020
Data on experimentally-characterized animal mitochondrial proteomes (mt-proteomes) are limited to a few model organisms and are scattered across multiple databases, impeding a comparative analysis. We developed two resources to address these problems...
Caenorhabditis elegans Mitochondrial Proteins Mice Proteome Databases, Protein Mitochondria Energy Metabolism Humans Saccharomyces cerevisiae Machine Learning Acanthamoeba castellanii Animals Drosophila melanogaster
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An improved catalogue of putative synaptic genes defined exclusively by temporal transcription profiles through an ensemble machine learning approach.

BMC genomics Dec 23, 2019
BACKGROUND: Assembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Previously, we had trained an ensemble machine learning model to assign a probability of having synaptic function to every p...
Machine Learning Animals Gene Expression Profiling Gene Ontology Synapses Drosophila melanogaster Transcription, Genetic
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A Deep Learning Approach for Detecting Copy Number Variation in Next-Generation Sequencing Data.

G3 (Bethesda, Md.) Nov 5, 2019
Copy number variants (CNV) are associated with phenotypic variation in several species. However, properly detecting changes in copy numbers of sequences remains a difficult problem, especially in lower quality or lower coverage next-generation sequen...
High-Throughput Nucleotide Sequencing Genome, Viral Drosophila melanogaster Genome, Insect Nudiviridae Animals Deep Learning Genomics DNA Copy Number Variations
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DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning.

eLife Oct 1, 2019
Quantitative behavioral measurements are important for answering questions across scientific disciplines-from neuroscience to ecology. State-of-the-art deep-learning methods offer major advances in data quality and detail by allowing researchers to a...
Drosophila melanogaster Grasshoppers Equidae Deep Learning Software Computational Biology Algorithms Behavior, Animal Animals Locomotion
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A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features.

BMC bioinformatics Jun 10, 2019
BACKGROUND: It is of great clinical significance to develop an accurate computer aided system to accurately diagnose the breast cancer. In this study, an enhanced machine learning framework is established to diagnose the breast cancer. The core of th...
Reproducibility of Results Drosophila melanogaster Breast Neoplasms Humans Animals Neural Networks, Computer Support Vector Machine Female
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Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Nature methods May 27, 2019
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impair...
Databases, Protein HEK293 Cells Animals Humans Peptide Fragments Saccharomyces cerevisiae Deep Learning Neural Networks, Computer Tandem Mass Spectrometry Drosophila melanogaster Peptide Library Software Caenorhabditis elegans Proteome
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