Phylogenetic tree inference is a classic fundamental task in evolutionary biology that entails inferring the evolutionary relationship of targets based on multiple sequence alignment (MSA). Maximum likelihood (ML) and Bayesian inference (BI) methods ...
Fungal taxonomy is a complex and rapidly changing subject, which makes proper naming of fungi challenging for taxonomists. A registration platform with a standardized and information-integrated database is a powerful tool for efficient research on fu...
Protein science : a publication of the Protein Society
Jan 1, 2023
The availability of accurate and fast artificial intelligence (AI) solutions predicting aspects of proteins are revolutionizing experimental and computational molecular biology. The webserver LambdaPP aspires to supersede PredictProtein, the first in...
MOTIVATION: Protein secondary structure prediction (PSSP) is one of the fundamental and challenging problems in the field of computational biology. Accurate PSSP relies on sufficient homologous protein sequences to build the multiple sequence alignme...
Deep learning techniques have significantly advanced the field of protein structure prediction. LOMETS3 (https://zhanglab.ccmb.med.umich.edu/LOMETS/) is a new generation meta-server approach to template-based protein structure prediction and function...
MOTIVATION: A high-quality sequence alignment (SA) is the most important input feature for accurate protein structure prediction. For a protein sequence, there are many methods to generate a SA. However, when given a choice of more than one SA for a ...
MOTIVATION: Deep learning has revolutionized protein tertiary structure prediction recently. The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy tertiary structures for most individual protein chains. However, the accur...
MOTIVATION: Co-evolution analysis can be used to accurately predict residue-residue contacts from multiple sequence alignments. The introduction of machine-learning techniques has enabled substantial improvements in precision and a shift from predict...