Additional file 7 of Computational prediction of lncRNA-mRNA interactions by integrating tissue specificity in human transcriptome Junichi Iwakiri Goro Terai Michiaki Hamada 10.6084/m9.figshare.c.3799336_D8.v2 https://springernature.figshare.com/articles/journal_contribution/Additional_file_7_of_Computational_prediction_of_lncRNA-mRNA_interactionsby_integrating_tissue_specificity_in_human_transcriptome/5096863 Our predictions of TINCR-mRNA interactions using 31 different tissue-specific candidate mRNAs. For each tissue, the tissue-specific candidate mRNAs were selected by using RNA-seq data derived from Human Protein Atlas project (Expression Atlas ID: E-MTAB-2836). Combination of two prediction (ranking) methods (MinEnergy and SumEnergy) and two candidate mRNA sets (initial and tissue-specific) were used for the predictions. Experimentally-validated TINCR-mRNA interactions [9] (considered as true positives) were used for evaluating the prediction results. Horizontal axis indicates the number of predicted TINCR-mRNA interactions. Vertical axis indicates the total number of experimentally-validated interactions (true positives). The prediction using skin-specific candidates is already shown in Fig 2. (PDF 51 kb) 2017-06-08 05:00:00 RNA-RNA interaction Long non-coding RNA Tissue specificity RNA-seq Computational prediction