AIMC Topic: Models, Biological

Clear Filters Showing 461 to 470 of 1371 articles

Measuring and Preventing COVID-19 Using the SIR Model and Machine Learning in Smart Health Care.

Journal of healthcare engineering
COVID-19 presents an urgent global challenge because of its contagious nature, frequently changing characteristics, and the lack of a vaccine or effective medicines. A model for measuring and preventing the continued spread of COVID-19 is urgently re...

Automatic Gene Function Prediction in the 2020's.

Genes
The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active...

Spatiotemporal identification of druggable binding sites using deep learning.

Communications biology
Identification of novel protein binding sites expands druggable genome and opens new opportunities for drug discovery. Generally, presence or absence of a binding site depends on the three-dimensional conformation of a protein, making binding site id...

A novel approach for personalized response model: deep learning with individual dropout feature ranking.

Journal of pharmacokinetics and pharmacodynamics
Deep learning is the fastest growing field in artificial intelligence and has led to many transformative innovations in various domains. However, lack of interpretability sometimes hinders its application in hypothesis-driven domains such as biology ...

A permutation method for network assembly.

PloS one
We present a method for assembling directed networks given a prescribed bi-degree (in- and out-degree) sequence. This method utilises permutations of initial adjacency matrix assemblies that conform to the prescribed in-degree sequence, yet violate t...

Ensemble transfer learning for the prediction of anti-cancer drug response.

Scientific reports
Transfer learning, which transfers patterns learned on a source dataset to a related target dataset for constructing prediction models, has been shown effective in many applications. In this paper, we investigate whether transfer learning can be used...

Machine learning analysis of DNA methylation in a hypoxia-immune model of oral squamous cell carcinoma.

International immunopharmacology
BACKGROUND: Hypoxia status and immunity are related with the development and prognosis of oral squamous cell carcinoma (OSCC). Here, we constructed a hypoxia-immune model to explore its upstream mechanism and identify potential CpG sites.

An attempt at estrus detection in cattle by continuous measurements of ventral tail base surface temperature with supervised machine learning.

The Journal of reproduction and development
We aimed to determine the effectiveness of estrus detection based on continuous measurements of the ventral tail base surface temperature (ST) with supervised machine learning in cattle. ST data were obtained through 51 estrus cycles on 11 female cat...

Machine learning to predict mesenchymal stem cell efficacy for cartilage repair.

PLoS computational biology
Inconsistent therapeutic efficacy of mesenchymal stem cells (MSCs) in regenerative medicine has been documented in many clinical trials. Precise prediction on the therapeutic outcome of a MSC therapy based on the patient's conditions would provide va...