afpCOOL: A tool for antifreeze protein prediction.

Various cold-adapted organisms produce antifreeze proteins (AFPs), which prevent the freezing of cell fluids by inhibiting the growth of ice crystals. AFPs are currently being recognized in various organisms, living in extremely low temperatures. AFPs have several important applications in increasing freeze tolerance of plants, maintaining the tissue in frozen conditions and producing cold-hardy plants by applying transgenic technology. Substantial differences in the sequence and structure of the AFPs, pose a challenge for researchers to identify these proteins. In this paper, we proposed a novel method to identify AFPs, using supportive vector machine (SVM) by incorporating 4 types of features. Results of the two used benchmark datasets, revealed the strength of the proposed method in AFP prediction. According to the results of an independent test setup, our method outperformed the current state-of-the-art methods. In addition, the comparison results of the discrimination power of different feature types revealed that physicochemical descriptors are the most contributing features in AFP detection. This method has been implemented as a stand-alone tool, named afpCOOL, for various operating systems to predict AFPs with a user friendly graphical interface.

rpiCOOL: A tool for In Silico RNA-protein interaction detection using random forest.

Understanding the principle of RNA-protein interactions (RPIs) is of critical importance to provide insights into post-transcriptional gene regulation and is useful to guide studies about many complex diseases. The limitations and difficulties associated with experimental determination of RPIs, call an urgent need to computational methods for RPI prediction. In this paper, we proposed a machine learning method to detect RNA-protein interactions based on sequence information. We used motif information and repetitive patterns, which have been extracted from experimentally validated RNA-protein interactions, in combination with sequence composition as descriptors to build a model to RPI prediction via a random forest classifier. About 20% of the "sequence motifs" and "nucleotide composition" features have been selected as the informative features with the feature selection methods. These results suggest that these two feature types contribute effectively in RPI detection. Results of 10-fold cross-validation experiments on three non-redundant benchmark datasets show a better performance of the proposed method in comparison with the current state-of-the-art methods in terms of various performance measures. In addition, the results revealed that the accuracy of the RPI prediction methods could vary considerably across different organisms. We have implemented the proposed method, namely rpiCOOL, as a stand-alone tool with a user friendly graphical user interface (GUI) that enables the researchers to predict RNA-protein interaction. The rpiCOOL is freely available at http://biocool.ir/rpicool.html for non-commercial uses.

Use of porous high-density polyethylene grafts in open rhinoplasty: no infectious complication seen in spreader and dorsal grafts.

OBJECTIVE: The aim of this study is to use porous high-density polyethylene grafts (Medpor) in open rhinoplasty and then assess complication rate and aesthetic outcomes. METHODS: In a prospective cohort study, we performed open rhinoplasty and employed Medpor as rhinoplasty grafts. Then we compared their complication rate. RESULTS: In a total of 64 patients, 84 Medpor grafts--8 dorsal grafts, 23 strut grafts, 8 rim grafts, 5 button grafts and 10 spreader grafts--were utilized. Moreover, 5septal perforation repairs with Medpor were performed. The complication rates were 5.3% in dorsal graft (complication in dorsal graft was only movement of implant), 21.7% in strut graft and 25.0% in rim graft. No complication was seen in spreader and button grafts. All 5septal perforation repairs were successfully performed with the same rhinoplasty approach. CONCLUSION: Medpor can be used as dorsal and spreader graft in reconstruction of severe nose deformity with lowest complication rate and without infectious complication and extrusion.