Structural sciences.

Applications of Structural Equation Modeling in Social Sciences Research

Structural equation modeling (SEM) is a comprehensive statistical modeling tool for analyzing multivariate data involving complex relationships between and among variables (Hoyle, 1995). SEM surpasses traditional regression models by including multiple independent and dependent variables to test associated hypothesizes about relationships among observed and latent variables. SEM explain why res...

Structural Equation Modeling in the Communication Sciences , 1995 – 2000

Structural equation modeling (SEM) is a viable multivariate tool used by communication researchers for the past quarter century. Building off Cappella (1975) as well as McPhee and Babrow (1987), this study summarizes the use of this technique from 1995–2000 in 37 communication-based academic journals. We identify and critically assess 3 unique methods for testing structural relationships via SE...

Structural biology and its applications to the health sciences.

Part of the decipherment of genomic information lies in understanding the structure and function of the protein products of these genes. Protein structure is of further importance because of the molecular basis of many diseases. Structural biology is the field of research focusing on the experimental determination of the structure of biological molecules. We review the field of structural biolo...

in Humanities , Social Sciences , and Natural Sciences

Current methods in structural proteomics and its applications in biological sciences

A broad working definition of structural proteomics (SP) is that it is the process of the high-throughput characterization of the three-dimensional structures of biological macromolecules. Recently, the process for protein structure determination has become highly automated and SP platforms have been established around the globe, utilizing X-ray crystallography as a tool. Although protein struc...