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MicroRNAs (miRNAs) are ∼22-nt long, non-coding RNAs that regulate gene silencing. It is known that many human miRNAs are deregulated in numerous types of tumors. Here we report the sequencing of small RNAs (17-25 nt) from 23 breast, bladder, colon and lung tumor samples using high throughput sequencing. We identified 49 novel miRNA and miR-sized small RNAs.(More)
10575 Background: Cancer of unknown primary (CUP) constitutes 3%-5% of all newly diagnosed cancer cases. It presents a major diagnostic challenge as knowing the tumor tissue of origin (ToO) of the cancer is crucial for choosing the optimal treatment. MicroRNAs are a family of non-coding, regulatory RNA genes involved in development and differentiation that(More)
For patients with primary lung cancer, accurate determination of the tumor type significantly influences treatment decisions. However, techniques and methods for lung cancer typing lack standardization. In particular, owing to limited tumor sample amounts and the poor quality of some samples, the classification of primary lung cancers using small(More)
The process of designing novel RNA sequences by inverse RNA folding, available in tools such as RNAinverse and InfoRNA, can be thought of as a reconstruction of RNAs from secondary structure. In this reconstruction problem, no physical measures are considered as additional constraints that are independent of structure, aside of the goal to reach the same(More)
Identification of the tissue of origin of a tumor is vital to its management. Previous studies showed tissue-specific expression patterns of microRNA and suggested that microRNA profiling would be useful in addressing this diagnostic challenge. MicroRNAs are well preserved in formalin-fixed, paraffin-embedded (FFPE) samples, further supporting this(More)
AIMS The distinction between benign and malignant thyroid nodules has important therapeutic implications. Our objective was to develop an assay that could classify indeterminate thyroid nodules as benign or suspicious, using routinely prepared fine needle aspirate (FNA) cytology smears. METHODS A training set of 375 FNA smears was used to develop the(More)
Previously, it was shown that predicting selective mutations leading to topological transitions in the secondary structure of RNAs can be achieved by a coarse-grain Laplacian matrix tree graph representation using its second eigenvalue. When applying the coarse-grain tree graph representation, introduced by Shapiro and coworkers in the 80's, it is possible(More)
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