COGNAC: a web server for searching and annotating hydrogen-bonded base interactions in RNA three-dimensional structures

Hydrogen bonds are crucial factors that stabilize a complex ribonucleic acid (RNA) molecule's three-dimensional (3D) structure. Minute conformational changes can result in variations in the hydrogen bond interactions in a particular structure. Furthermore, networks of hydrogen bonds, especially those found in tight clusters, may be important elements in structure stabilization or function and can therefore be regarded as potential tertiary motifs. In this paper, we describe a graph theoretical algorithm implemented as a web server that is able to search for unbroken networks of hydrogen-bonded base interactions and thus provide an accounting of such interactions in RNA 3D structures. This server, COGNAC (COnnection tables Graphs for Nucleic ACids), is also able to compare the hydrogen bond networks between two structures and from such annotations enable the mapping of atomic level differences that may have resulted from conformational changes due to mutations or binding events. The COGNAC server can be accessed at http://mfrlab.org/grafss/cognac

Eye Corners Detection using HAAR Cascade Classifiers in Controlled Environment

Facial landmarks detection is undoubtedly important in many applications in computer vision for example face detection and recognition. This article demonstrated the use of Haar Cascade Classifiers to automatically locate the eye corners. We acquired our 3D face image data by Vectra 3D camera in a controlled environment. We use two data set of 300 eye images to train en and ex cascade classifiers regardless of the left and the right eye. These classifiers were then used to detect and locate the inner (en) and outer (ex) eye landmarks. To train HAAR cascade classifier we usually use huge amounts of data. But in this study, about 300 positive images used to train each classifier. Due to this we observed quite an amount of false positive detection. We developed a simple algorithm to predict the eye corners by first eliminate the false detection and geometrically modeled the eye. Our classifiers able to detect and locate en on 53 out of 60 test images and the ability to detect ex in 59 out of 60 test images. In craniofacial anthropometry, it is very important to locate the facial landmarks as per the standard definition of the landmarks. Our results demonstrated accurate detection of ex and en facial landmarks as per standard definition. In conclusion, our trained enHaar and exHaar cascade classifiers are able to automatically detect the en and ex craniofacial landmarks in a controlled environment

InterRNA: A database of base interactions in RNA structures

A major component of RNA structure stabilization are the hydrogen bonded interactions between the base residues. The importance and biological relevance for large clusters of base interactions can be much more easily investigated when their occurrences have been systematically detected, catalogued and compared. In this paper, we describe the database InterRNA (INTERactions in RNA structures database-http://mfrlab.org/interrna/) that contains records of known RNA 3D motifs as well as records for clusters of bases that are interconnected by hydrogen bonds. The contents of the database were compiled from RNA structural annotations carried out by the NASSAM (http://mfrlab.org/grafss/nassam) and COGNAC (http://mfrlab.org/grafss/cognac) computer programs. An analysis of the database content and comparisons with the existing corpus of knowledge regarding RNA 3D motifs clearly show that InterRNA is able to provide an extension of the annotations for known motifs as well as able to provide novel interactions for further investigations