Latest AI and machine learning research in genetics for healthcare professionals.
While cancer has traditionally been considered a genetic disease, mounting evidence indicates an important role for non-genetic (epigenetic) mechanisms. Common anti-cancer drugs have recently been observed to induce the adoption of reversible drug-tolerant cell states, thereby accelerating the evolution of drug resistance. Determining how to optimally balance the competing goals of killing the t...
Gene silencing via small interfering RNA (siRNA) represents a transformative tool in cancer therapy, offering specificity and reduced off-target effects compared to conventional treatments. A crucial step in siRNA-based therapies is endosomal escape, the release of siRNA from endosomes into the cytoplasm. Quantifying endosomal escape is challenging due to the dynamic nature of the process and li...
DNA data storage is rapidly gaining traction as a long-term data archival solution, primarily due to its exceptional durability. Retrieving stored d...
The integration of multi-omic data is pivotal for understanding complex diseases, but its high dimensionality and noise present significant challeng...
The availability of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus data post-COVID has reached exponentially to an enormous magn...
Generative AI has the potential to transform knowledge work, but further research is needed to understand how knowledge workers envision using and i...
The intuitive nature of drag-based interaction has led to its growing adoption for controlling object trajectories in image-to-video synthesis. Stil...
An adult human body is made up of some 30 to 40 trillion cells, all of which stem from a single fertilized egg cell. The process by which the right ...
Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in...
Foundation models have made significant strides in understanding the genomic language of DNA sequences. However, previous models typically adopt the...
With the rapid development of high-throughput sequencing platforms, an increasing number of omics technologies, such as genomics, metabolomics, and ...
Historical documents encompass a wealth of cultural treasures but suffer from severe damages including character missing, paper damage, and ink eros...
Liver cancer is a leading cause of cancer-related mortality worldwide, with its high genetic heterogeneity complicating diagnosis and treatment. Thi...
With the increased popularity of Deep Neural Networks (DNNs), increases also the need for tools to assist developers in the DNN implementation, test...
DNA barcodes are crucial in biodiversity analysis for building automatic identification systems that recognize known species and discover unseen spe...
Molecular dynamics simulations are crucial for understanding the structural and dynamical behavior of biomolecular systems, including the impact of th...
As key elements within the central dogma, DNA, RNA, and proteins play crucial roles in maintaining life by guaranteeing accurate genetic expression ...
Post-training quantization (PTQ) reduces excessive hardware cost by quantizing full-precision models into lower bit representations on a tiny calibr...
As one of the most successful generative models, diffusion models have demonstrated remarkable efficacy in synthesizing high-quality images. These m...
Gaussian processes (GPs) and Gaussian random fields (GRFs) are essential for modelling spatially varying stochastic phenomena. Yet, the efficient ge...