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Table 2 The considered node features and their types, i.e., weighted dynamic, weighted static, unweighted dynamic, and unweighted static

From: Improved supervised prediction of aging-related genes via weighted dynamic network analysis

 

Weighted

Unweighted

Dynamic

Diff-nobin-2

DegC-wt, ClusC-wt, CloseC-wt, BetwC-wt, EigenC-wt

DGDV, GoT, GDC,

ECC, KC, DegC, CentraMV

Static

Static-nobin-2

SGDV, UniNet, 30BPIs

  1. Features in bold are (the best versions of) our proposed features, and the rest are the considered existing features. Note that we list only the best version of our proposed weighted dynamic features for simplicity, as we proposed, tested, and compared 30 such features. Also, note that we only test the weighted static counterpart of the best weighted dynamic feature. For the discussion on our proposed weighted dynamic features, see Section “The proposed weighted features”. For the discussion on how we select the best of the existing weighted dynamic features and the best of our proposed weighted dynamic features, see Additional file 1: Section S2 and Additional file 1: Fig. S1
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BMC Bioinformatics

ISSN: 1471-2105

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