Latest AI and machine learning research in genetics for healthcare professionals.
Cross-view object geo-localization (CVOGL) aims to locate a target object from a query view (e.g., ground or drone) within a geo-tagged reference image (e.g., satellite). Existing approaches heavily rely on 2D appearance matching and are constrained by limited datasets lacking geometric metadata, diverse prompts, and standard field-of-view imagery. To address these intertwined challenges, we first...
We present APRIL-MedSeg, a YAML-driven modular framework for 2D medical image segmentation. It provides a unified and extensible ecosystem that decomposes segmentation networks into reusable components. Also, the framework integrates a broad spectrum of advanced paradigms, including semi-supervised learning, domain adaptation, knowledge distillation, weakly supervised learning, and text-guided seg...
Multimodal Large Language Models (MLLMs) inherit rich relational priors from their language backbones, yet often fail when asked to apply these relati...
Rett syndrome is a severe neurodevelopmental disorder primarily caused by mutations in the MECP2 gene. A significant subset of severe cases are driven...
Background: Large language model (LLM) agents increasingly automate bioinformatics analyses, but most existing bioinformatics tools were built for sta...
Enhancer-derived RNAs (eRNAs) are critical regulators of gene transcription, yet their genome-wide annotation remains challenging. Here, we present eR...
The leading cause of mortality and morbidity in children under the age of 5 is preterm birth. The timing of birth is influenced by both genetic and en...
High-quality plant genome assemblies are rapidly increasing, but accurate structural annotation remains reliant on transcript and homology evidence, l...
Gene regulation emerges from coordinated interactions among dispersed cis-regulatory elements, yet how these elements integrate into functional regula...
Immune checkpoint inhibitors (ICI) are central to the treatment of metastatic clear cell renal cell carcinoma (ccRCC), yet only a subset of patients d...
Biosynthetic gene clusters (BGCs) encode enzymatic pathways for natural products with pharmaceutical potential, yet prioritizing candidates from fragm...
Long-term memory (LTM) formation typically requires extensive training. While operant conditioning is expected to produce stronger LTM than classical ...
The softmax activation in multihead attention (MHA) is the de facto standard for attention-based models in visual perception tasks. However, standard ...
Isothermal nucleic acid amplification tests enable rapid and decentralized molecular diagnostics but often lack robust quantitative readouts compared ...
Public bulk RNA-seq repositories contain hundreds of thousands of samples, creating opportunities for large-scale representation learning, but integra...
While WGS-based AMR prediction has reached high accuracy, existing models lack a mechanism to ground neural attributions in established biological pat...
Multimodal large language models (MLLMs) extend large language models (LLMs) with visual perception, enabling joint reasoning over images and text. De...
Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including socia...
Deep neural networks are increasingly deployed in safety-critical domains such as autonomous driving and medical diagnosis, yet their opaque, high-dim...
Predicting how mutations alter antibody-antigen binding affinity is essential for antibody engineering and vaccine design, yet current methods general...