First mirDeep2 uses a pre-filtering step to filter out potential hairpins which do not have a predetermined number of sequence miRNA at each location.
And socially, it's an ideal set-up: there are few other opportunities in life to filter potential friends via their hobbies.
In addition, we used the tissue atlas provided by Su et al. [17] to filter potential microRNA targets for a specific disease and a given tissue.
As microRNA expression is tissue-specific annotated in PhenomiR, we used the tissue atlas provided by Su et al. [17] to filter potential microRNA targets in a specific tissue.
Therefore, although, in this experiment we used IPI-based detection of protein expression to filter potential targets for verification, it is clear that not all genes displaying AS will also be detected as canonical isoforms and vice versa.
Our approach to solve this problem is by using a "error-prone words pair list" to filter potential mismatches.
The advantage of using of eQTL related co-expression clusters is an opportunity to filter potential candidates by their genomic position.
The first stage is to filter potential methods using two matrices and the second stage is to compare the filtered methods in terms of the four resource requirements (time, money, knowledge and data).
As a means to filter potential false positives, core SNP with iHS >3 and at least 10 other nearby (0.5 Mb) core SNPs with iHS >2 were considered further.
