Computational identification of condition-specific miRNA targets based on gene expression profiles and sequence information

Table 1 Feature selection in the gene expression dataset.

Rank	Sample ID	Type	Tissue
1	ATGE26	D	Leaf
2	Heat-Shoots-1.0 h	S	Shoot
3	UV-B-Roots-1.0 h	S	Root
4	ATGE73	D	Pollen
5	ATGE91	D	Leaf
6	ATGE34	D	Flower
7	Drought-Roots-0.25 h	S	Root
8	Drought-Shoots-0.25 h	S	Shoot
9	UV-B-Shoots-3.0 h	S	Shoot
10	Cold-Roots-24 h	S	Root
11	ATGE97	D	Seedling
12	Drought-Roots-24.0 h	S	Root
13	UV-B-shoots-0.5 h	S	Shoot
14	ATGE55	D	Flower
15	ATGE101	D	Seedling
16	Drought-Shoots-3.0 h	S	Shoot
17	Wounding-Shoots-6.0 h	S	Shoot
18	Osmotic-Shoots-1.0 h	S	Shoot
19	Oxidative-Roots-6.0 h	S	Root
20	UV-B-Roots-6.0 h	S	Root

The top 20 ranked features for miRNA target classification. Each feature corresponds to a condition in the two expression datasets (D: developmental process and S: stress treatment).

ISSN: 1471-2105