AIMC Topic: Animals

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Functional parcellation of mouse visual cortex using statistical techniques reveals response-dependent clustering of cortical processing areas.

PLoS computational biology
The visual cortex of the mouse brain can be divided into ten or more areas that each contain complete or partial retinotopic maps of the contralateral visual field. It is generally assumed that these areas represent discrete processing regions. In co...

Robotic soft swim bladder using liquid-vapor phase transition.

Materials horizons
The swim bladder is crucial to underwater robots to enhance their overall performance and to expand their range of motion. However, previous attempts to incorporate this function have failed or have adopted mechanical swim bladders with high-disturba...

Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration.

Analytical chemistry
An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occasionally overlapping information at different length scales and spatial resolutions. It is important...

Reconstructing Undersampled Photoacoustic Microscopy Images Using Deep Learning.

IEEE transactions on medical imaging
One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed. In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM imag...

Protein2Vec: Aligning Multiple PPI Networks with Representation Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Research of Protein-Protein Interaction (PPI) Network Alignment is playing an important role in understanding the crucial underlying biological knowledge such as functionally homologous proteins and conserved evolutionary pathways across different sp...

FlyIT: Drosophila Embryogenesis Image Annotation based on Image Tiling and Convolutional Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
With the rise of image-based transcriptomics, spatial gene expression data has become increasingly important for understanding gene regulations from the tissue level down to the cell level. Especially, the gene expression images of Drosophila embryos...

Automatic rat brain image segmentation using triple cascaded convolutional neural networks in a clinical PET/MR.

Physics in medicine and biology
The purpose of this work was to develop and evaluate a deep learning approach for automatic rat brain image segmentation of magnetic resonance imaging (MRI) images in a clinical PET/MR, providing a useful tool for analyzing studies of the pathology a...

Weakly Supervised Deep Learning-Based Optical Coherence Tomography Angiography.

IEEE transactions on medical imaging
Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Deep learning networks have been widely applied in the field of OCTA reconstruction, benefiting from its powerful mapping capability among i...

Autonomous Robot for Removing Superficial Traumatic Blood.

IEEE journal of translational engineering in health and medicine
: To remove blood from an incision and find the incision spot is a key task during surgery, or else over discharge of blood will endanger a patient's life. However, the repetitive manual blood removal involves plenty of workload contributing fatigue ...

Computational identification of ubiquitination sites in Arabidopsis thaliana using convolutional neural networks.

Plant molecular biology
We developed two CNNs for predicting ubiquitination sites in Arabidopsis thaliana, demonstrated their competitive performance, analyzed amino acid physicochemical properties and the CNN structures, and predicted ubiquitination sites in Arabidopsis. A...