Table 2. Our database/tissue/disease filters can significantly reduce the number of predicted miRNA targets but still keep the functional one.

Human miRNA	Functional target	Reference Pubmed ID	Filter settings: (database/tissue/disease)	# of predicted targets when using only the database filter	# of predicted targets when using all three (database/tissue/disease) filters	Reduced ratio
miR-16-5p	PPM1D	20668064	4 / breast tissue / invasive breast cancer	883	16	98.19% = (883–16)/883
miR-301a-3p	PTEN	21393507	4 / breast tissue / invasive breast cancer	533	14	97.37%
miR-195-5p	SLC2A3	22265971	3 / bladder tissue / carcinoma of bladder	3008	125	95.84%
miR-615-5p	IGF2	22819824	3 / liver tissue / liver neoplasms	1238	57	95.40%
miR-519d-3p	CDKN1A	22262409	4 / liver tissue / liver neoplasms	717	45	93.72%
miR-135a-5p	APC	18632633	4 / colon / colorectal neoplasms	374	27	92.78%
miR-153-3p	MCL1	19676043	3 / brain / glioblastoma	1816	156	91.41%
miR-204-5p	EZR	21416062	3 / stomach / stomach carcinoma	1152	104	90.97%
miR-103a-3p	KLF4	22593189	3 / colon / colorectal carcinoma	2095	236	88.74%
miR-497-5p	RAF1	21350001	4 / breast tissue / breast neoplasms	887	106	88.05%