Recently, attention mechanism and derived models have gained significant traction in drug
development due to their outstanding performance and interpretability in handling complex …

Cell biology is fundamentally limited in its ability to collect complete data on cellular
phenotypes and the wide range of responses to perturbation. Areas such as computer vision …

Motivation Deciphering the language of non-coding DNA is one of the fundamental
problems in genome research. Gene regulatory code is highly complex due to the existence …

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking
technologies, developed over the past 20 years, have enormously accelerated the …

Although remarkable advances have been reported in high-throughput sequencing, the
ability to aptly analyze a substantial amount of rapidly generated biological …

With Artificial Intelligence (AI) increasingly permeating various aspects of society, including
healthcare, the adoption of the Transformers neural network architecture is rapidly changing …

In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

The effectiveness of deep learning methods can be largely attributed to the automated
extraction of relevant features from raw data. In the field of functional genomics, this …

Over the past few decades, the number of health and 'omics-related data'generated and
stored has grown exponentially. Patient information can be collected in real time and …

Deep neural networks (DNN) have fundamentally revolutionized the artificial intelligence
(AI) field. The transformer model is a type of DNN that was originally used for the natural …