PMC:4331678 / 25558-26150 JSONTXT

{"project":"2_test","denotations":[{"id":"25707434-20507895-14839086","span":{"begin":77,"end":79},"obj":"20507895"},{"id":"25707434-23514608-14839087","span":{"begin":113,"end":114},"obj":"23514608"},{"id":"25707434-11101803-14839088","span":{"begin":162,"end":164},"obj":"11101803"},{"id":"25707434-23353650-14839089","span":{"begin":431,"end":432},"obj":"23353650"}],"text":"We compared our proposed MNet with other related algorithms: ProMK [25], SW [16], OMG [27], LIG [28], and MSkNN [7]. MSkNN first trains a weighted majority vote [31] classifier (similar to a weighted kNN) on each individual network, and then integrates these classifiers for protein function prediction; it achieves competent performance on the first large-scale community based critical assessment of protein function annotation [2]. The details of the other comparing methods were introduced in the section of Related Work, and their parameter setting is discussed in the Additional File 1."}