There is growing interest in RNA as a drug target due to its widespread involvement in biological processes. To exploit the power of structure-based drug-design approaches, novel scoring and docking tools need to be developed that can efficiently and reliably predict binding modes and binding affinities of RNA ligands. We report for the first time the development of a knowledge-based scoring fu...

Protein-protein interactions take place in every aspect of life. The diversity of those interactions and their significant role in regulatory pathways account for the special interest in them. As shown in various diseases, protein-protein interactions can be deregulated and the cause of illness. Therefore, a better and more detailed understanding of protein-protein interactions is of great impo...

Proteins play fundamental roles in all biological processes. Akin to the complete sequencing of genomes, complete descriptions of protein structures is a fundamental step towards understanding biological life, and is also highly relevant in the development of therapeutics and drugs. Computational prediction methods, especially template-based modeling, can quickly generate crude but useful struc...

Protein-protein docking (PPD) predictions usually rely on the use of a scoring function to rank docking models generated by exhaustive sampling. To rank good models higher than bad ones, a large number of scoring functions have been developed and evaluated, but the methods used for the computation of PPD predictions remain largely unsatisfactory. Here, we report a network-based PPD scoring func...

The curated CSAR-NRC benchmark sets provide valuable opportunity for testing or comparing the performance of both existing and novel scoring functions. We apply two different scoring functions, both independently and in combination, to predict the binding affinity of ligands in the CSAR-NRC data sets. One reported here for the first time employs multiple chemical-geometrical descriptors of the ...

in this paper data were collected from 120 farmers in north khorassan province for the two periods (2005-2007) in order to survey the role of rain-fed lentil risk profile for designing an insurance model. to evaluate looses of each risk, risk frequency, risk impact criteria’s as well as risk matrix were used. results showed that low risk was the largest risk area. during study period, a decreas...

OBJECTIVES Text categorization has been used in biomedical informatics for identifying documents containing relevant topics of interest. We developed a simple method that uses a chi-square-based scoring function to determine the likelihood of MEDLINE citations containing genetic relevant topic. METHODS Our procedure requires construction of a genetic and a nongenetic domain document corpus. W...