AIMC Topic: Animals

Clear Filters Showing 6001 to 6010 of 8866 articles

SeqSVM: A Sequence-Based Support Vector Machine Method for Identifying Antioxidant Proteins.

International journal of molecular sciences
Antioxidant proteins can be beneficial in disease prevention. More attention has been paid to the functionality of antioxidant proteins. Therefore, identifying antioxidant proteins is important for the study. In our work, we propose a computational m...

Robotic bees for crop pollination: Why drones cannot replace biodiversity.

The Science of the total environment
The notion that robotic crop pollination will solve the decline in pollinators has gained wide popularity recently (Fig. 1), and in March 2018 Walmart filed a patent for autonomous robot bees. However, w present six arguments showing that this is a t...

Deep learning and conditional random fields-based depth estimation and topographical reconstruction from conventional endoscopy.

Medical image analysis
Colorectal cancer is the fourth leading cause of cancer deaths worldwide and the second leading cause in the United States. The risk of colorectal cancer can be mitigated by the identification and removal of premalignant lesions through optical colon...

Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Neuron
The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both lea...

Sum Rate of MISO Neuro-Spike Communication Channel With Constant Spiking Threshold.

IEEE transactions on nanobioscience
Communication among neurons, known as neuro-spike communication, is the most promising technique for realization of a bio-inspired nanoscale communication paradigm to achieve biocompatible nanonetworks. In neuro-spike communication, the information, ...

A deep learning framework to discern and count microscopic nematode eggs.

Scientific reports
In order to identify and control the menace of destructive pests via microscopic image-based identification state-of-the art deep learning architecture is demonstrated on the parasitic worm, the soybean cyst nematode (SCN), Heterodera glycines. Soybe...

Unsupervised, Statistically Based Systems Biology Approach for Unraveling the Genetics of Complex Traits: A Demonstration with Ethanol Metabolism.

Alcoholism, clinical and experimental research
BACKGROUND: A statistical pipeline was developed and used for determining candidate genes and candidate gene coexpression networks involved in 2 alcohol (i.e., ethanol [EtOH]) metabolism phenotypes, namely alcohol clearance and acetate area under the...

PrESOgenesis: A two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach.

Scientific reports
Successful spermatogenesis and oogenesis are the two genetically independent processes preceding embryo development. To date, several fertility-related proteins have been described in mammalian species. Nevertheless, further studies are required to d...

Evidence of Rentian Scaling of Functional Modules in Diverse Biological Networks.

Neural computation
Biological networks have long been known to be modular, containing sets of nodes that are highly connected internally. Less emphasis, however, has been placed on understanding how intermodule connections are distributed within a network. Here, we bor...

A Dynamic Neural Gradient Model of Two-Item and Intermediate Transposition.

Neural computation
Transposition is a tendency for organisms to generalize relationships between stimuli in situations where training does not objectively reward relationships over absolute, static associations. Transposition has most commonly been explained as either ...