New Software for the Identification and Characterization of Peptides Generated during Fontina Cheese Ripening Using Mass Spectrometry Data

The aim of this work was to design and implement a new bioinformatics software which is able to identify the protein peptides from the peaks which arise from in-source or MS/MS fragmentation. The oligopeptide fraction was extracted from Fontina cheese at different ages of ripening and subsequently analyzed by LC/MS/MS. On the resulting total ion chromatograms, the peptides were identified by a method based both on the in-source fragmentation detectable with a single-quadrupole mass analyzer and by a new software which was developed. This software performs an in-silieo digestion of the major milk proteins, it calculates all the possible peptide fragments which are generated by the loss of the first N- or C-terminal amino acids, and finally, it matches the experimental ion chromatogram with the in-silico which generated theoretical spectrum to identify the exact amino-acid protein sequence of the unknown oligopeptide. With this tool, the useful insights into the proteolytic processes which occur during Fontina cheese aging are obtained, which leads to a better knowledge about the functional features of the proteolysis end product.

A Novel Gaussian Extrapolation Approach for 2D Gel Electrophoresis Saturated Protein Spots

Analysis of images obtained from two-dimensional gel electrophoresis （2D-GE） is a topic of utmost importance in bioinformatics research, since commercial and academic software available currently has proven to be neither completely effective nor fully automatic, often requiring manual revision and refinement of computer generated matches. In this work, we present an effective technique for the detection and the reconstruction of over-saturated protein spots. Firstly, the algorithm reveals overexposed areas, where spots may be truncated, and plateau regions caused by smeared and overlapping spots. Next, it reconstructs the correct distribution of pixel values in these overexposed areas and plateau regions, using a two-dimensional least-squares fitting based on a generalized Gaussian distribution. Pixel correction in saturated and smeared spots allows more accurate quantification, providing more reliable image analysis results. The method is validated for processing.highly exposed 2D-GE images, comparing reconstructed spots with the corresponding non-saturated image, demonstrating that the algorithm enables correct spot quantification.

One Decade of Development and Evolution of MicroRNA Target Prediction Algorithms

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs （miRNAs）. The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mech- anisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computa- tional algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of compu tational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future directions.