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If one considers chemical-biology toolsets that have had the greatest impact on numerous fields of life sciences over the most recent years, proximity-labeling tools, such as APEX, and Bio-ID arguably lead the way. This article reflects upon the current st ...
Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's ph ...
Partially replacing ordinary Portland cement (OPC) with low-carbon supplementary cementitious materials (SCMs) in blended cement concrete (BCC) is perceived as the most promising route for sustainable concrete production. Despite having a lower environment ...
The sheer size of the protein sequence space is massive: a protein of 100 residues can have 20^100 possible sequence combinations; and knowing that this exceeds the number of atoms in the universe, the chance of randomly discovering a stable new sequence w ...
Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families ...
Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the li ...
Interactive simulations allow students to independently ex- plore scientific phenomena and ideally infer the underlying principles through their exploration. Effectively using such environments is challenging for many students and there- fore, adaptive gui ...
BackgroundStatistical potentials, also named knowledge-based potentials, are scoring functions derived from empirical data that can be used to evaluate the quality of protein folds and protein-protein interaction (PPI) structures. In previous works we deco ...
Following the hugely successful application of deep learning methods to protein structure prediction, an increasing number of design methods seek to leverage generative models to design proteins with improved functionality over native proteins or novel str ...
Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left behind in a cou ...