Latest AI and machine learning research in genetics for healthcare professionals.
The gene signatures of Alzheimer's Disease (AD) brains reflect an output of a complex interplay of genetic, epigenetic, epi-transcriptomic, and post-transcriptional regulation., yet the dominant factor shaping these signatures remains unclear. To identify the most significant factor that shapes the AD brain signatures, we integrated cellular and molecular features with differential gene expression...
Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences. Widely used models of TF-DNA binding, such as position weight matrices (PWMs) and position-specific affinity matrices (PSAMs), assume binding free energy is the sum of independent base contributions. However, there is ample evidence that non-additive effects significantly influence TF binding. Here, we utili...
SCN2A-related disorders result from pathogenic variants in the gene encoding for the voltage-gated sodium channel Nav1.2. Collectively, these disorder...
Whether individual transcripts carry intrinsic features that predetermine their response to external perturbations is unknown. Here we used nanopore d...
Background: DNA lesions arise from endogenous metabolism and environmental exposure and are the major drivers of mutagenesis, aging, and cancer develo...
Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), is the most common primary lung cancer worldwide. Despite advancements in...
The promise of Rectified Flow rests on producing self-generated couplings whose trajectories are straight, or nearly so. In practice, trajectories gen...
Query-based Vision Transformer segmentation models typically reconstruct dense spatial feature maps to predict masks, inheriting design patterns from ...
Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor contin...
Achieving high-throughput and precise phenotypic quantification and imaging modalities of stomatal and epidermal cells across diverse species remains ...
Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based mo...
Haemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening hyperinflammatory syndrome characterised by uncontrolled immune activation. Redu...
Background: Although advances in next-generation sequencing have accelerated the identification of genetic variants in cardiomyopathy, interpreting va...
Pre-trained genomic language model (gLM) representations have been anticipated to enable enhanced deep learning predictions on several genomics tasks,...
Nanopore sequencing holds great potential for the direct detection of non-canonical DNA bases from electrical signals, yet current approaches remain l...
Background and Objectives Patients with peripheral neuropathies (PN) commonly exhibit balance impairment. In clinical practice, balance is typically a...
Conformational plasticity of RNAs plays important roles in recognizing RNA-binding proteins, and is often modulated by their binding partners. Here, w...
Copy number variations (CNVs) are major structural genomic variants that contribute to a wide range of human diseases. Accurate detection of CNVs from...
Aptamers are single stranded DNA or RNA molecules selected for their high affinity and specificity to bind target molecules, similar to antibodies. Th...
Glioblastoma multiforme (GBM) is characterised by profound genomic heterogeneity and heavy-tailed gene-expression distributions that challenge convent...