Editorial (Thematic Issue: “miRNA and Cancer; Computational and Experimental Approaches”)
TL;DRAbstract
Human genome sequencing was started to solve four letter algorithm of the genome to understand the complex nature of human metabolism. However, after completion of Human Genome Project many scientists realized that sequence information alone was not sufficient to solve the biochemical mechanism of the organism through classical approaches. Non-coding parts of the genome produce small conserved ribonucleic acids, miRNAs to control cellular and physiological processes [1, 2]. This breakthrough discovery directed researches to examine role of miRNA in cancer since miRNAs are involved in the development, cell differentiation, and regulation of cell cycle [3]. The first paper of the special issue provides general information of miRNA in cancer research. This thematic issue presents two computational approaches for miRNA identification and their role in cancer. The first one comes from Dr. Wang and his presented work predicts cancer-related miRNAs by using expression profiles in tumor tissue
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Human genome sequencing was started to solve four letter algorithm of the genome to understand the complex nature of human metabolism. However, after completion of Human Genome Project many scientists realized that sequence information alone was not sufficient to solve the biochemical mechanism of the organism through classical approaches. Non-coding parts of the genome produce small conserved ribonucleic acids, miRNAs to control cellular and physiological processes [1, 2]. This breakthrough discovery directed researches to examine role of miRNA in cancer since miRNAs are involved in the development, cell differentiation, and regulation of cell cycle [3]. The first paper of the special issue provides general information of miRNA in cancer research. This thematic issue presents two computational approaches for miRNA identification and their role in cancer. The first one comes from Dr. Wang and his presented work predicts cancer-related miRNAs by using expression profiles in tumor tissue
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