Name
Abstract | ||
|---|---|---|
Graph models often give us a deeper understanding of real-world networks. In the case of biological networks they help in predicting the evolution and history of biomolecule interactions, provided we map properly real networks into the corresponding graph models. In this paper, we show that for biological graph models many of the existing parameter estimation techniques overlook the critical prope... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCBB.2020.2980260 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | DocType | Volume |
Proteins,Biological system modeling,Maximum likelihood estimation,Parameter estimation,Evolution (biology) | Journal | 18 |
Issue | ISSN | Citations |
3 | 1545-5963 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jithin Kazuthuveettil Sreedharan | 1 | 10 | 3.39 |
| Krzysztof Turowski | 2 | 4 | 5.65 |
| Wojciech Szpankowski | 3 | 1557 | 192.33 |