Abstract: The present invention pertains to a pharmaceutical composition for preventing or treating squamous cell carcinoma, the pharmaceutical composition containing a highly expressed lncRNAs in esophageal squamous cell carcinoma (HERES) expression inhibitor. More specifically, the present invention pertains to a pharmaceutical composition which uses a HERES expression inhibitor to reduce the expression of HERES and affect Wnt signaling pathways, and thereby prevent or treat squamous cell carcinoma. The present inventors discovered that the expression pattern of HERES is related to the onset of squamous cell carcinoma, and found that HERES can be a target for treating squamous cell carcinoma.

Abstract: The present invention relates to a squamous cell carcinoma diagnostic or prognosis prediction marker and the use thereof and, more particularly, to the use of a long non-coding RNA as a marker composition for diagnosing or predicting the prognosis of squamous cell carcinoma, a diagnostic composition, diagnostic information-providing method and the like, by means of the correlation between an expression of the long non-coding RNA and squamous cell carcinoma pathogenesis. The inventors discovered that the expression pattern of a long non-coding RNA is related to cancer pathogenesis, investigated the correlation between the expression of a specific long non-coding RNA and squamous cell carcinoma pathogenesis and thus confirmed that the long non-coding RNA can be a squamous cell carcinoma diagnostic or prognosis prediction marker.

Abstract: Disclosed is a method of detecting a genomic structural variation based on k-mer set in a reference genome by means of a computer apparatus, the method including receiving sample sequence data, comparing the sample sequence data to k-mer set in reference genome data to determine at least one k-mer read that is not included in the reference genome data among reads of the sample sequence data, determining a breakpoint and a candidate region of a structural variation by mapping the at least one k-mer read to standard reference genome data, and predicting a structural variation type for the sample sequence data on the basis of a sequence mapping pattern and the breakpoint corresponding to the mapping result.

Abstract: Disclosed are a method of predicting mature microRNA regions using a bidirectional hidden Markov model and a medium recording a computer program to implement the method. The method includes representing each base pair comprising the microRNA precursor by state information of match, mismatch and bulge states; representing the base pair by a basepair emission symbol; computing a Viterbi probability (P) for microRNA using a probability (Es(q)) that state s emits symbol q and a transition probability (Tab) from state a to state b; computing a Viterbi probability (Pt(i)) that the i-th base pair is true and another Viterbi probability (Pf(i)) that the i-th base pair is false; and computing a position probability (S(i)) for mature microRNA using the Viterbi probability, wherein, if the position probability (S(i)) for mature microRNA is greater than a predetermined value, the position at which the base pair is present is taken as the mature microRNA region.