The rapid increase in the number of proteins in sequence databases and the diversity of their
functions challenge computational approaches for automated function prediction. Here, we …

Rapid technological advances have led to the production of different types of biological data
and enabled construction of complex networks with various types of interactions between …

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global,
community-driven effort to evaluate and improve the computational annotation of protein …

Motivation The prevalence of high-throughput experimental methods has resulted in an
abundance of large-scale molecular and functional interaction networks. The connectivity of …

We provide an overview of recent developments in big data analyses in the context of precision
medicine and health informatics. With the advance in technologies capturing molecular …

Exploiting sequence–structure–function relationships in biotechnology requires improved
methods for aligning proteins that have low sequence similarity to previously annotated …

For the past half-century, structural biologists relied on the notion that similar protein sequences
give rise to similar structures and functions. While this assumption has driven research …

Protein design is challenging because it requires searching through a vast combinatorial
space that is only sparsely functional. Self-supervised learning approaches offer the potential …

Motivation T cells use T cell receptors (TCRs) to recognize small parts of antigens, called
epitopes, presented by major histocompatibility complexes. Once an epitope is recognized, an …

Designing proteins to achieve specific functions often requires in silico modeling of their
properties at high throughput scale and can significantly benefit from fast and accurate protein …