Latest AI and machine learning research in genetics for healthcare professionals.
Pyrazinamide is an important first-line antibiotic for treating tuberculosis and resistance is primarily caused by mutations in the pncA gene. Traditional machine learning models have been shown to be able to predict pyrazinamide resistance with some success, but are limited in their ability to incorporate three-dimensional protein structural information. Graph neural networks offer the potential ...
Spot-based spatial transcriptomics (ST) technologies like 10x Visium quantify genome-wide gene expression and preserve spatial tissue organization. However, their coarse spot-level resolution aggregates signals from multiple cells, preventing accurate single-cell analysis and detailed cellular characterization. Here, we present DeepSpot2Cell, a novel DeepSet neural network that leverages pretraine...
Most widely used methods for evaluating RNA 3D structure models require experimental reference structures, which restricts their use for novel RNAs. T...
DNA:protein interactions involving large structural deformations of DNA underpin essential biological processes. Although correlative evidence suggest...
Gene regulatory networks (GRNs), involving interactions between large numbers of genes, govern expression levels of mRNA and their resulting proteins ...
Functional genetic screens have uncovered dependencies in many cancers, but experimentally screened models for most cancers are far outnumbered by mol...
Bioscience encompasses studies on living organisms, their components, and their interactions, with the main aim of translating research into useful ap...
Alterations in metabolism, stress response, sleep, circadian rhythms, and neuroendocrine processes are key features of aging and neurodegeneration. Th...
Millions of human genomes have been genotyped by national biobanks worldwide. Training large language models (LLM) with this data may lead to a univer...
Hemoglobin (Hb), a well-characterized protein central to oxygen transport and molecular medicine, serves as a model for studying how sequence variatio...
Predicting the transcriptional effects of genetic perturbations across diverse contexts is a central challenge in functional genomics. While single-ce...
Large rare copy number variants (CNVs) are a main source of genetic variation in the genome and are important in both evolution and disease risk. CNVs...
Although we now have a rich toolset for genome editing, an equivalent framework for manipulating the proteome with a comparable flexibility and specif...
Deciphering the regulatory syntax of the genome is essential to understand the genetic and molecular architecture of complex traits, as most trait-ass...
The spatial folding of the genome shapes gene regulation by controlling which loci interact, yet inferring the mechanisms behind these 3D structures f...
Protein language models (PLMs) have gained increasing acceptance in tasks ranging from variant effect prediction in disease to optimization and de nov...
Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly f...
Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell bur...
In this work, we present a highly efficient machine learning method for identifying DNA sequences that code for genes. The learning process is based o...
Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities across colonic regions (ascending, transverse, descending colon) a...