Latest AI and machine learning research in genetics for healthcare professionals.
Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small ...
There has been remarkable progress in identifying the causes of genetic conditions as well as understanding how changes in specific genes cause disease. Though difficult (and often superficial) to parse, an interesting tension involves emphasis on basic research aimed to dissect normal and abnormal biology versus more clearly clinical and therapeutic investigations. To examine one facet of this qu...
Stroke is one of the most common causes of death, only second to heart disease. Molecular investigations about stroke are in acute shortage nowadays. ...
Normal iron levels are required to prevent thrombocytosis by inhibiting thrombopoiesis. Thrombocytosis is usually associated with a mild iron deficien...
A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the...
Materials science is undergoing a revolution, generating valuable new materials such as flexible solar panels, biomaterials and printable tissues, new...
In recent years, sequencing technologies have enabled the identification of a wide range of non-coding RNAs (ncRNAs). Unfortunately, annotation and in...
Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of t...
OBJECTIVE: Identifying disease-mutation relationships is a significant challenge in the advancement of precision medicine. The aim of this work is to ...
In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integrat...
The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. Howe...
Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and...
Chromosomal inversions are important structural changes that may facilitate divergent selection when they capture co-adaptive loci in the face of gene...
Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly...
The number of published articles describing associations between mutations and diseases is increasing at a fast pace. There is a pressing need to gath...
BACKGROUND: To address the lack of standard terminology to describe extracellular RNA (exRNA) data/metadata, we have launched an inter-community effor...
Vascular smooth muscle cell (VSMC) migration and proliferation is central to neointima formation in vein graft failure following coronary artery bypas...
Dynamic force spectroscopy (DFS) measurements on biomolecules typically require classifying thousands of repeated force spectra prior to data analysis...
The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognit...
Recombination is crucial for biological evolution, which provides many new combinations of genetic diversity. Accurate identification of recombination...