Intact Adenovirus

Intact adenovirus research focuses on efficiently processing and analyzing large datasets, particularly within the context of large language models (LLMs) and image analysis of viral particles. Current efforts center on optimizing memory management techniques, such as developing novel key-value (KV) cache strategies (e.g., LayerKV, PyramidKV) and garbage collection algorithms (e.g., DumpKV), to improve LLM performance and reduce computational costs. Furthermore, research utilizes convolutional neural networks to automate the detection and classification of intact adenoviruses in transmission electron microscopy (TEM) images, improving the efficiency and accuracy of quality control in viral vector production for gene therapy.