Latest AI and machine learning research in genetics for healthcare professionals.
The SARS-CoV-2 pandemic has resulted in shortages of both critical reagents for nucleic acid purification and highly trained staff as supply chains are strained by high demand, public health measures and frequent quarantining and isolation of staff. This created the need for alternate workflows with limited reliance on specialised reagents, equipment and staff. We present here the validation and i...
Heterologous expression is the main approach for recombinant protein production ingenetic synthesis, for which codon optimization is necessary. The existing optimization methods are based on biological indexes. In this paper, we propose a novel codon optimization method based on deep learning. First, we introduce the concept of codon boxes, via which DNA sequences can be recoded into codon box seq...
A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence ...
In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such as premature maturity, low convergence path qualit...
Coronavirus disease 2019 (COVID-19) is a novel disease resulting from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whi...
Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Comp...
Animal models of human disease provide an system that can reveal molecular mechanisms by which mutations cause pathology, and, moreover, have the pot...
BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of h...
Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ...
Algorithms and information processing, fundamental to biological system, are an essential aspect of many elementary physical phenomena, such as molecu...
The use of human induced pluripotent stem cells (iPSCs), used as an alternative to human embryonic stem cells (ESCs), is a potential solution to chall...
Next-generation sequencing (NGS) methods lie at the heart of large parts of biological and medical research. Their fundamental importance has created ...
Predicting the impact of noncoding genetic variation requires interpreting it in the context of three-dimensional genome architecture. We have develop...
In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Cohesin and CTCF (CCCTC-bin...
Human activity recognition has become an important research topic within the field of pervasive computing, ambient assistive living (AAL), robotics, h...
Investigations of spatial cellular composition of tissue architectures revealed by multiplexed in situ RNA detection often rely on inaccurate cell seg...
In recent years, deep learning has been widely used in diverse fields of research, such as speech recognition, image classification, autonomous drivin...
Single-cell protein abundance is a fundamental type of information to characterize cell states. Due to high cost and technical barriers, however, dire...
The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimen...
BACKGROUND: To use clinical and MRI radiomic features coupled with machine learning to assess HER2 expression level and predict pathologic response (p...