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Amaç: MikroRNA'lar, hepatosellüler karsinomun (HCC) gelişiminde ve ilerlemesinde anahtar düzenleyicilerdir. Yakın tarihli bir çalışmada, miR-4746'nın HCC’de aşırı ifade edildiği bulunmuş olsa da miR-4746’nın HCC’deki farklı seviyelerde ifade edilmesi ve klinikopatolojik önemi belirsizliğini korumaktadır. Bu çalışmada miR-4746’nın gen ifade özelliğini, klinikopatolojik rolünü ve kestirim değerini hesaplamalı yaklaşımlar kullanarak değerlendirmeyi amaçladık. Gereç ve Yöntemler: Çeşitli insan kanserlerinde miR-4746’nın gen ifade özelliği dbDEMC veri tabanı kullanılarak belirlendi. Ayrıca, HCC’de miR-4746 gen ifade seviyesini analiz etmek için ENCORI/Starbase v2 ve UALCAN veri tabanlarını kullandık. Ayrıca UALCAN veri tabanını kullanarak miR-4746’nın klinikopatolojik işlevini araştırdık. Son olarak, miR-4746’nın HCC’deki kestirim özelliğini belirleyebilmek için Kaplan-Meier plotter ve ENCORI/Starbase v2 veri tabanları aracılığıyla sağ kalım analizi ile gerçekleştirdik. Bulgular: miR-4746, çeşitli insan kanserlerinde farklı gen ifade değerlerine sahipti ve normal örneklere kıyasla HCC dokularında önemli ölçüde arttığı gözlemlenmiştir. Klinikopatolojik analiz, miR-4746’nın kanser evresi, tümör derecesi, lenf bezi metastaz durumu, TP53 mutasyon durumu ve hastanın yaşı dahil olmak üzere farklı klinik parametrelerde farklı gen ifade seviyelerine sahip olduğunu koydu. Ek olarak, miR-4746’nın yüksek ifadesi, HCC’de kötü prognoz ile önemli ölçüde ilişkili olduğu bulunmuştur. Sonuç: Bulgularımız, miR-4746’nın kötü kestirim ve çok kötü klinikopatolojik çıktılarla ilişkilendirilen onkojenik bir miRNA olabileceğini gösterdi. Ayrıca miR-4746, HCC’nin tümorogenezinde önemli bir role sahip olabilir ve potansiyel kestirim biyobelirteç olarak hizmet edebilir.

Polymerase chain reaction (PCR) and its derivatives are one of the most widely used DNA-based methods in species determination studies in meat and meat products. Chromosomal or mitochondrial genes of the species can be targeted in PCR-based analyzes used in species detection studies. Many researchers are able to realize oligonucleotide differences between species through online alignment programs on mitochondrial DNA. Using chromosomal DNA would provide more concise results in quantification studies. However, determining the marker regions for genomic DNA is challenging due to the large size of the chromosomes. Bioinformatics approaches are available for selected applications. However, using those approaches requires intensive knowledge of computer science, molecular biology, and bioinformatics in addition to high computational power. In this study, a pipeline is presented that will provide a user-friendly approach to be adopted by facilities where contamination analyzes are routinely performed.

In this study, bioinformatics analysis of fugu (Fugu rubripes) catalase (cat) gene was performed. Molecular biology science is developing rapidly in parallel with the increasing importance of bioinformatics, thanks to the developed techniques in recent years. In this bioinformatics-based study wich enables the effective identification and characterization of genes in living organisms using online genome databases and statistics and storage, organization and sharing of the ever-increasing genetic data we designed the conserved gene synteny and gene structure and detected the identiy-similarity ratios between fugu and the other telosts and tetrapods. NCBI-GeneBank, EMBL, ENSEML and UNIPROT databases have been used for all these bioinformatics studies. Bioedit and Mega programs were used to perform the analysis and evaluate the data obtained from all these databases. In silico analysis such as the identification and characterization of fugu cat gene, exons-introns organization, phylogenetic tree and gene synteny were completed in this study and presented with tables and figures.

In this study, we present a new web interface for major bioinformatics algorithms and introduce a novel approximate string matching algorithm. Our web interface executes major algorithms on the field for the use of computational biologists, students or any other interested researchers. In the web interface, algorithms come under three sections: Sequence alignment, pattern matching and motif finding. In each section, we introduce algorithms in order to find best fitting one for specific dataset and problem. The interface introduces execution time, memory usage and context specific results of algorithms such as alignment score. The interface utilizes emerging open source languages and tools. In order to develop light and user-friendly interface, all parts of the interface coded with Python language. On the other hand, Django is used for web interface. Second contribution of the study is novel A-BOM algorithm, which is designed for approximate pattern matching problem. The algorithm is approximate matching variation of Backward Oracle Matching. We compare our algorithm with popular approximate string matching algorithms. Results denote that A-BOM introduces %30 to %80 short runtime improvement when compared to current approximate pattern matching algorithms on long patterns.