Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CAMIRADA: Cancer microRNA association discovery algorithm, a case study
  on breast cancer   In recent studies, non-coding protein RNAs have been identified as microRNA
that can be used as biomarkers for early diagnosis and treatment of cancer,
that decrease mortality in cancer. A microRNA may target hundreds or thousands
of genes and a gene may regulate several microRNAs, so determining which
microRNA is associated with which cancer is a big challenge. Many computational
methods have been performed to detect micoRNAs association with cancer, but
more effort is needed with higher accuracy. Increasing research has shown that
relationship between microRNAs and TFs play a significant role in the diagnosis
of cancer. Therefore, we developed a new computational framework (CAMIRADA) to
identify cancer-related microRNA based on the relationship between microRNAs
and disease genes (DG) in the protein network, the functional relationships
between microRNAs and Transcription Factors (TF) on the co-expression network,
and the relationship between microRNAs and the Differential Expression Gene
(DEG) on co-expression network. The CAMIRADA was applied to assess breast
cancer data from two HMDD and miR2Disease databases. In this study, the AUC for
the 65 microRNA of the top of the list was 0.95, which was more accurate than
the similar methods used to detect microRNA associated with the cancer artery.

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The categories of this paper are: quant-ph
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The categories of this paper are: q-alg
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The categories of this paper are: gr-qc
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The categories of this paper are: hep-ex
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The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: eess
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-th
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The categories of this paper are: astro-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: math-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: supr-con
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The categories of this paper are: bayes-an
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The categories of this paper are: cmp-lg