Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …

Language models have recently emerged as a powerful machine-learning approach for
distilling information from massive protein sequence databases. From readily available …

Characterizing the three-dimensional structure of macromolecules is central to
understanding their function. Traditionally, structures of proteins and their complexes have …

Background Predicting protein function and structure from sequence is one important
challenge for computational biology. For 26 years, most state-of-the-art approaches …

Motivation: Accurately predicting protein secondary structure and relative solvent
accessibility is important for the study of protein evolution, structure and function and as a …

Protein structures change during evolution in response to mutations. Here, we analyze the
mapping between sequence and structure in a set of structurally aligned protein domains …

DNA binding specificities of transcription factors (TFs) are a key component of gene
regulatory processes. Underlying mechanisms that explain the highly specific binding of TFs …

Sequence comparison and alignment has had an enormous impact on our understanding of
evolution, biology and disease. Comparison and alignment of biological networks will …

Introduction to Proteins provides a comprehensive and state-of-the-art introduction to the
structure, function, and motion of proteins for students, faculty, and researchers at all levels …

Important biological information is encoded in the topology of biological networks.
Comparative analyses of biological networks are proving to be valuable, as they can lead to …