G. Naveen Sundar¹, Stalin Selvaraj², D. Narmadha¹, K. Martin Sagayam³, A. Amir Anton Jone³, Ayman A. Aly⁴, Dac-Nhuong Le^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 31-46, 2022, DOI:10.32604/cmes.2022.019914

Abstract Hepatocellular carcinoma (HCC) is one major cause of cancer-related mortality around the world. However, at advanced stages of HCC, systematic treatment options are currently limited. As a result, new pharmacological targets must be discovered regularly, and then tailored medicines against HCC must be developed. In this research, we used biomarkers of HCC to collect the protein interaction network related to HCC. Initially, DC (Degree Centrality) was employed to assess the importance of each protein. Then an improved Graph Coloring algorithm was used to rank the target proteins according to the interaction with the primary target protein after assessing the top… More >

Shenglong Wang^1,*, Jing Yang^1,*, Xiaoyu Ding², Jianpei Zhang¹, Meng Zhao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 215-249, 2022, DOI:10.32604/cmes.2022.018050

Abstract In recent years, local community detection algorithms have developed rapidly because of their nearly linear computing time and the convenience of obtaining the local information of real-world networks. However, there are still some issues that need to be further studied. First, there is no local community detection algorithm dedicated to detecting a seed-oriented local community, that is, the local community with the seed as the core. The second and third issues are that the quality of local communities detected by the previous local community detection algorithms are largely dependent on the position of the seed and predefined parameters, respectively. To… More >