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MicroRNA (miRNA) molecules, which are effective on the initiation and progression of many different diseases, are a type of noncoding RNA with a length of about 22 nucleotides. Scientists have reported the importance of miRNAs in the prevention, diagnosis, and treatment of complex human diseases. Therefore, in the last decade, researchers have been working hard to find potential miRNAdisease associations. Many computational techniques have been developed because of the experimental techniques are time-consuming and expensive used to find new relationships between miRNAs and diseases. In this study, we suggested Kernelized Bayesian matrix factorization (KBMF) technique to predict new miRNA-disease relationships. We applied 5-fold cross validation technique and obtained an average value AUC of 0.9450. Also, we applied case studies based on breast, lung, and colon neoplasms to prove the performance of KBMF technique. The results showed that KBMF can be used as a reliable computational model to reveal possible miRNA-disease relationships.

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Collagen has been implicated in a number of pathological conditions. When an amino acid in triple helix is replaced with other amino acids, the collagen structure is destroyed. The deterioration in the collagen structure causes various hereditary diseases and dysfunctions. In this study, the mutations on the alpha-1 chain of type I collagen, which is the most common in the human body, were examined using Python programming language. Based on the previous studies, brittle bone disease (OI) type 2 caused by mutations in type-I collagen alpha-1 chains, has been focused on. UniprotKB database were used for the mutations reported. The mutations obtained were combined in an alpha-I chain and it was seen that the most mutated amino acid was glycine (Gly). Since glycine amino acid affects the stability of the helix structure of the collagen alpha-I chain, it can be considered to influence collagen-induced diseases. The most frequently recurring mutations (glycine (G)> arginine (R), glycine (G)> serine (S), glycine (G)>aspartate (D)) were detected. As a result of comparison, increase in molecular mass, change in isoelectric point, decrease in hydropathy index, change in charge state and acid-base properties were observed. The effect of these changed features on brittle bone disease (OI) has been interpreted.