AIMC Topic: Species Specificity

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Cross-species behavior analysis with attention-based domain-adversarial deep neural networks.

Nature communications
Since the variables inherent to various diseases cannot be controlled directly in humans, behavioral dysfunctions have been examined in model organisms, leading to better understanding their underlying mechanisms. However, because the spatial and tem...

Misic, a general deep learning-based method for the high-throughput cell segmentation of complex bacterial communities.

eLife
Studies of bacterial communities, biofilms and microbiomes, are multiplying due to their impact on health and ecology. Live imaging of microbial communities requires new tools for the robust identification of bacterial cells in dense and often inter-...

Organization of areal connectivity in the monkey frontoparietal network.

NeuroImage
Activity observed in biological neural networks is determined by anatomical connectivity between cortical areas. The monkey frontoparietal network facilitates cognitive functions, but the organization of its connectivity is unknown. Here, a new conne...

SPASOS 1.1: a program for the inference of ancestral shape ontogenies.

Cladistics : the international journal of the Willi Hennig Society
We recently published a method to infer ancestral landmark-based shape ontogenies that takes into account the possible existence of changes in developmental timing. Here we describe SPASOS, a software to perform that analysis. SPASOS is an open-sourc...

Spine dynamics in the brain, mental disorders and artificial neural networks.

Nature reviews. Neuroscience
In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability ...

Assessing the potential for deep learning and computer vision to identify bumble bee species from images.

Scientific reports
Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and compute...

Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species.

PLoS computational biology
N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA's biological functions. However, the existing ...

Cross-species Data Classification by Domain Adaptation via Discriminative Heterogeneous Maximum Mean Discrepancy.

IEEE/ACM transactions on computational biology and bioinformatics
Cross-species or Cross-platform data classification is a challenging problem in the field of bioinformatics, which aims to classify data samples in one species/platform by using labeled data samples in another species/platform. Traditional classifica...

Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning.

Journal of pharmaceutical sciences
Research into pharmacokinetics plays an important role in the development process of new drugs. Accurately predicting human pharmacokinetic parameters from preclinical data can increase the success rate of clinical trials. Since clearance (CL) which ...

iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.

Computational and mathematical methods in medicine
A promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recognition of promoters has great significance for a better understanding of the transcriptional regulati...