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

Gysi et al. [148] developed a network framework to explore modularity features of biological networks are in need of
drug-repurposing opportunities for COVID-19. Among the development of the multilayer network theory [156-162] . In
the six drugs that reduced viral infection, four drugs could fact, multilayer biological networks have been extensively
be directly repurposed to treat COVID-19, thus proposing researched on in recent years [134,158-162] . However, publicly
novel treatments for COVID-19. available multilayer biological network datasets are still

In addition to the above discussions, there are many lacking. With the accumulation of various omics data
other research works and applications of network biology and the development of network inference techniques, it
in systems biology [2-5] and ecology [150] . Systems biology is possibly to develop efficient data-driven frameworks
investigates the composition of complex biological systems to construct multilayer biological networks. Finally, the
and the interactions among genes, mRNAs, proteins, and cooperation of scientists from different fields is essential
all other biomacromolecules. Hence, network biology is for the applications of network biology. Network biology
pivotal for systems biology. Network biology and systems provides effective tools for exploring bioinformatics, and
biology share many common topics. Due to knowledge both, biologists and medical workers are prerequisites for
limitations, we will not delve in further on other the applications of the theoretical results.
applications. 5. Conclusion

4. Challenges of network biology This paper reviews some of the recent progresses and
challenges of network biology. We discuss two aspects of
Although great advances have been achieved in network
biology during the past few decades, there are still some network biology, biological network construction, and
challenges. First, it is still difficult to predict the causal their applications and summarize four approaches to
constructing biological networks: Online database, artificial
relationships among genes for many organisms; network algorithms, topological identification based on dynamical
construction remains a problem to be further studied [37,71,102] . network theory, and data-driven approaches. Among the
Second, the currently investigated biological networks are four approaches, the data-driven approach is currently
still far from the whole connectome and are always noisy; a research focus in network biology, which has wide
the currently investigated PPI networks for yeast cover applications in biological systems. We also briefly introduce
approximately 90% genes of the whole genome ; and the their applications in identifying important genes/proteins,
[6]
considered human PPI networks encompass about 17,000 predicting the functions of genes/proteins, exploring the
genes out of 25,000 genes . There are still uncertainties molecular mechanisms behind complex phenotypes and
[13]
whether the obtained knowledge from sub-networks still biological network control, identifying drug targets, and
holds in the whole connectome. For example, it has been exploring drug combinations and drug repurposing. We
reported that the subnets of scale-free networks are in declare that most of the applications of network biology
fact not scale-free [149] . Therefore, it would be interesting rely on the guilt-by-association and guilt-by-rewiring
to further explore whether the current results about principles. Some challenges of network biology are also
network biology still hold in the whole connectome. False- discussed in this paper, reflecting our future research
positive edges in existing biological networks may also
affect the obtained results. It is also intriguing to develop direction. Network biology is a promising interdisciplinary
effective tools to exclude false-positive edges in large- field, which will undoubtedly provide important clues for
scale biological networks. Third, real-world biological understanding complex phenotypes in biological systems.
systems are far more complex; they may involve different Acknowledgments
scales of interactions, including gene, RNA, protein,
and metabolic levels. Most studies tend to focus only I would like to thank my students for helping me to check
on certain levels of interactions among the same type of the references.
biomolecules. With the development of high-throughput
technologies and the accumulation of various omics Funding
data, it would be interesting to perform network biology This work was supported by the National Natural Science
analysis by integrating multi-omics data [140-152] . Fourth, Foundation of China (Grant No.: 61773153) and in part
most of the investigated biology networks are static. Real- by the Natural Science Foundation of Henan Province
world biological networks may dynamically change their (Grant No.: 202300410045), the Program for Science and
structures over time [153] . Moreover, some genes may be only Technology Innovation Talents in Universities of Henan
expressed in specific tissues and at some given time points; Province (Grant No.: 20HASTIT025), and the Training
biological networks may display temporal, dynamical, Plan of Young Key Teachers in Colleges and Universities of
and modularity features [17,79,154,155] . The time-varying and Henan Province (Grant No.: 2018GGJS021).

Volume 1 Issue 2 (2022) 9 https://doi.org/10.36922/gpd.v1i2.101