Latest AI and machine learning research in genetics for healthcare professionals.
Oxidative stress (OXS) is closely related to tumor prognosis and immune response, while TP53 integrated with NRF2 is closely associated with the regulation of cancer-related OXS. Hence, constructing a TP53-NRF2 integrated OXS signature of pan-cancer is essential in predicting survival prognosis and facilitating cancer drug treatment. The pan-cancer analysis acquired the Cancer Genome Atlas (TCGA) ...
Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the prod...
In India, newborn screening (NBS) is essential for detecting health problems in infants. Despite significant progress, significant gaps and challenges...
OBJECTIVE: Artificial intelligence (AI) holds enormous potential for noninvasively identifying patients with rectal cancer who could achieve pathologi...
INTRODUCTION: Accumulating evidence demonstrates that aberrant methylation of enhancers is crucial in gene expression profiles across several cancers....
RNA nanotechnology aims to use RNA as a programmable material to create self-assembling nanodevices for application in medicine and synthetic biology....
Proteins are used in various biotechnological applications, often requiring the optimization of protein properties by introducing specific amino-acid ...
Protein missense mutations and resulting protein stability changes are important causes for many human genetic diseases. However, the accurate predict...
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could aid the diagnosis of acute respiratory infections (A...
Protein-DNA and protein-RNA interactions are involved in many biological processes and regulate many cellular functions. Moreover, they are related to...
This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung adenocarcinoma (LUAD) based on its histopathological...
Deep convolutional neural networks have shown advanced performance in accurately segmenting images. In this paper, an SNP-like convolutional neuron st...
Stochastic and robust optimization approaches often result in sub-optimal solutions for the uncertain p-hub median problem when continuous design para...
Unlike proteins, which have a wealth of validated structural data, experimentally or computationally validated DNA origami datasets are limited. Here ...
The specific genetic subtypes that gliomas exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists...
Using the CRISPR-Cas9 system to perform base substitutions at the target site is a typical technique for genome editing with the potential for applica...
Ovarian cancer (OC), known for its pronounced heterogeneity, has long evaded a unified classification system despite extensive research efforts. This ...
Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development a...
N6-methyladenosine (m6A) is the most prevalent, abundant, and conserved internal modification in the eukaryotic messenger RNA (mRNAs) and plays a cruc...
Clinicopathological presentations are critical for establishing a postoperative treatment regimen in Colorectal Cancer (CRC), although the prognostic ...