AIMC Topic: Models, Biological

Clear Filters Showing 561 to 570 of 1371 articles

The damage response framework and infection prevention: From concept to bedside.

Infection control and hospital epidemiology
Hospital-acquired infections remain a common cause of morbidity and mortality despite advances in infection prevention through use of bundles, environmental cleaning, antimicrobial stewardship, and other best practices. Current prevention strategies ...

Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data.

Communications biology
Single-molecule research techniques such as patch-clamp electrophysiology deliver unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysi...

A practical model for the identification of congenital cataracts using machine learning.

EBioMedicine
BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood ...

Reinforcement Learning for Bioretrosynthesis.

ACS synthetic biology
Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process is still long and costly, and efficient computational design tools are requi...

Prediction and optimization of slaughter weight in meat-type quails using artificial neural network modeling.

Poultry science
Carcass yield of meat-type quails is strongly correlated with the weight of the birds at slaughter (slaughter weight [SW]; body weight at 45 D of age). Moreover, prediction of superior animals for SW at the earlier stages of the rearing period is fav...

A novel machine learning based approach for iPS progenitor cell identification.

PLoS computational biology
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult ...

JCDB: a comprehensive knowledge base for Jatropha curcas, an emerging model for woody energy plants.

BMC genomics
BACKGROUND: Jatropha curcas is an oil-bearing plant, and has seeds with high oil content (~ 40%). Several advantages, such as easy genetic transformation and short generation duration, have led to the emergence of J. curcas as a model for woody energ...

Evaluation of the effect of Lactobacillus sakei strain L115 on Listeria monocytogenes at different conditions of temperature by using predictive interaction models.

Food research international (Ottawa, Ont.)
In this study, the inhibitory capacity of Lactobacillus sakei strain L115 against Listeria monocytogenes has been assayed at 4, 8, 11, 15 and 20 °C in broth culture. Besides, the use of predictive microbiology models for describing growth of both mic...

Ultrasonic liver steatosis quantification by a learning-based acoustic model from a novel shear wave sequence.

Biomedical engineering online
BACKGROUND: An efficient and accurate approach to quantify the steatosis extent of liver is important for clinical practice. For the purpose, we propose a specific designed ultrasound shear wave sequence to estimate ultrasonic and shear wave physical...

StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis.

BMC genomics
BACKGROUND: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the ...