Page 81 - GPD-1-2

Gene & Protein in Disease Recent advances and challenges of network biology

Ranking of network elements based on functional 130. Vinayagam A, Gibson TE, Lee HJ, et al., 2016, Controllability
substructures. J Theor Biol, 248(3): 471–479. analysis of the directed human protein interaction network
identifies disease genes and drug targets. Proc Natl Acad Sci
https://doi.org/10.1016/j.jtbi.2007.05.038
U S A, 113(18): 4976–4981.
118. Rual JF, Venkatesan K, Hao T, et al., 2005, Towards
a proteome-scale map of the human protein-protein https://doi.org/10.1073/pnas.1603992113
interaction network. Nature, 437(7062): 1173–1178. 131. Yan G, Vertes PE, Towlson EK, et al., 2017, Network control
principles predict neuron function in the Caenorhabditis
https://doi.org/10.1038/nature04209
elegans connectome. Nature, 550(7677): 519–523.
119. Cui Y, Cai M, Dai Y, et al., 2018, A hybrid network-based https://doi.org/10.1038/nature24056
method for the detection of disease-related genes. Physica A,
492: 389–394. 132. Wang P, Wang DJ, Lü JH, 2019, Controllability analysis of a
gene network for Arabidopsis thaliana reveals characteristics
https://doi.org/10.1016/j.physa.2017.10.026
of functional gene families. IEEE/ACM Trans Comput Biol
120. Milo R, Shen-Orr S, Itzkovitz S, et al., 2002, Network motifs: Bioinform, 16(3): 912–924.
Simple building blocks of complex networks. Science,
298(5594): 824–827. https://doi.org/10.1109/TCBB.2018.2821145
133. Guo WF, Zhang SW, Zeng T, et al., 2020, Network control
https://doi.org/10.1126/science.298.5594.824
principles for identifying personalized driver genes in
121. Shen-Orr SS, Milo R, Mangan S, et al., 2002, Network motifs cancer. Brief Bioinform, 21(5): 1641–1662.
in the transcriptional regulation network of Escherichia coli.
Nat Genet, 31(1): 64–68. https://doi.org/10.1093/bib/bbz089
134. Zheng W, Wang DJ, Zou XF, 2019, Control of multilayer
https://doi.org/10.1038/ng881
biological networks and applied to target identification of
122. Louie B, Higdon R, Kolker E, 2009, A statistical model of complex diseases. BMC Bioinformatics, 20: 271.
protein sequence similarity and function similarity reveals https://doi.org/10.1186/s12859-019-2841-2
overly-specific function predictions. PLoS One, 4(10): e7546.
135. Subramanian A, Tamayo P, Mootha VK, et al., 2005, Gene
https://doi.org/10.1371/journal.pone.0007546
set enrichment analysis: A knowledge-based approach for
123. Watson JD, 2011, Molecular Biology of the Gene. London: interpreting genome-wide expression profiles. Proc Natl
Pearson. Acad Sci U S A, 102(43): 15545–15550.
124. Sharan R, Ulitsky I, Shamir R, 2007, Network-based https://doi.org/10.1073/pnas.0506580102
prediction of protein function. Mol Syst Biol, 3: 88.
136. Subramanian A, Kuehn H, Gould J, et al., 2007, GSEA-P:
https://doi.org/10.1038/msb4100129 A desktop application for gene set enrichment analysis.
Bioinformatics, 23(23): 3251–3253.
125. Klie S, Nikoloski Z, Selbig J, 2014, Biological cluster
evaluation for gene function prediction. J Comput Biol, https://doi.org/10.1093/bioinformatics/btm369
21(6): 428–445.
137. Huang DW, Sherman BT Lempicki RA, 2009, Systematic
https://doi.org/10.1089/cmb.2009.0129 and integrative analysis of large gene lists using DAVID
bioinformatics resources. Nature Pro, 4(1): 44–57.
126. Liu YY, Slotine JJ, Barabási AL, 2011, Controllability of
complex networks. Nature, 473(7346): 167–173. https;//doi.org/10.1038/nprot.2008.211
https://doi.org/10.1038/nature10011 138. Yu GC, Wang LG, Han YY, et al., 2012, ClusterProfiler: An
R package for comparing biological themes among gene
127. Wuchty S, 2014, Controllability in protein interaction
networks. Proc Natl Acad Sci U S A, 111(19): 7156–7160. clusters. OMICS, 16(5): 284–287.
https://doi.org/10.1089/omi.2011.0118
https://doi.org/10.1073/pnas.1311231111
139. Zheng Q, Wang XJ, 2008, GOEAST: A web-based software
128. Liu XM, Pan LQ, 2015, Identifying driver nodes in the human
signaling network using structural controllability analysis. toolkit for gene ontology enrichment analysis. Nucl Acids
IEEE/ACM Trans Comput Biol Bioinform, 12(2): 467–472. Res, 36: 358–363.
https://doi.org/10.1093/nar/gkn276
https://doi.org/10.1109/TCBB.2014.2360396
140. Pawson T, Linding R, 2008, Network medicine. FEBS Lett,
129. Zhang XF, Le OY, Zhu Y, et al., 2015, Determining minimum
set of driver nodes in protein-protein interaction networks. 582(8): 1266–1270.
BMC Bioinformatics, 16: 146. https://doi.org/10.1016/j.febslet.2008.02.011
https://doi.org/10.1186/s12859-015-0591-3 141. Chen Y, Zhu J, Lum PY, et al., 2008, Variations in DNA

Volume 1 Issue 2 (2022) 15 https://doi.org/10.36922/gpd.v1i2.101