Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …

Uncovering the cis-regulatory code that governs when and how much each gene is
transcribed in a given genome and cellular state remains a central goal of biology. Here, we …

The advent of large language models (LLMs) and their adoption by the legal community has
given rise to the question: what types of legal reasoning can LLMs perform? To enable …

Background The growing application of artificial intelligence (AI) in healthcare has brought
technological breakthroughs to traditional diagnosis and treatment, but it is accompanied by …

Biomedical data are becoming increasingly multimodal and thereby capture the underlying
complex relationships among biological processes. Deep learning (DL)-based data fusion …

The expanding scale and inherent complexity of biological data have encouraged a growing
use of machine learning in biology to build informative and predictive models of the …

Proteomics plays a vital role in biomedical research in the post-genomic era. With the
technological revolution and emerging computational and statistic models, proteomic …

In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges
as a transformative force, bridging the realms of biology and technology. This paper …

Digital pathology (DP) is being increasingly employed in cancer diagnostics, providing
additional tools for faster, higher-quality, accurate diagnosis. The practice of diagnostic …

Learning decent representations from unlabeled time-series data with temporal dynamics is
a very challenging task. In this paper, we propose an unsupervised Time-Series …