Abstract: Systems and methods of the present invention may be used to determine metrics and health scores for content that may correspond to an educational course or textbook, which may be in a digital format. The metrics and health scores may be determined at various hierarchical content levels, and may be used to quantitatively assess how well the corresponding content is performing based on responses submitted to assessment item parts of the content by responders. The metrics may include difficulty and discrimination metrics, which may be determined using maximum likelihood estimation methods based on a modified two parameter item response model. A content analytics interface corresponding to a given content element may be generated and displayed via a user device, and may include content health scores of subcontent within that content element. The subcontent may be ordered according to content health score.

Abstract: The present disclosure includes a method for locating functionally relevant atoms in protein structures, and a representation of spatial arrangements of these atoms allowing for flexible description of active sites in proteins. The search method can be based on comparison of local structure features of proteins that share a common biochemical function. Generally, the method does not depend on overall similarity of structures and sequences of compared proteins, or on previous knowledge about functionally relevant residues. The compared protein structures can be condensed to a graph representation, with atoms as nodes and distances as edge labels. Protein graphs can then be compared to extract all possible Common Structural Cliques. These cliques can be merged to create structural templates: graphs that describe structural analogies between compared proteins. Structures of serine endopeptidases were compared in pairs using the presented algorithm with different geometrical parameters.

Abstract: A system and methods for rapidly and accurately assessing ligand binding characteristics for diverse classes of protein molecules. Modeling methods are used to represent the protein molecules and simulate their interaction with ligand molecules. Protein/ligand interactions are characterized by a fingerprint analysis that permits grouping of the proteins based on predicted structural features and ligand reactivity rather than sequence similarities or homology alone.