| Autor: |
Rangarajan, Prasanna Kumar, Gurusamy, Bharathi Mohan, Rajasekar, Elakkiya, Ippatapu Venkata, Srisurya, Chereddy, Spandana |
| Zdroj: |
International Journal of Information Technology; 20230101, Issue: Preprints p1-13, 13p |
| Abstrakt: |
Protein–Protein interactions (PPI) networks are protein complexes arranged in networks that are created by biochemical processes or electrostatic forces to carry out biological functions. PPI research is a challenging problem for both computer scientists as well as biologists due to the inherent potential of the original source that researchers can work with. PPI networks are being employed to research ailments, develop better medications, and comprehend various medical and health procedures that will finally benefit mankind. Retroactive data structures are a type of data structure that allows actions to be done on it in the past. The only restrictions included in the data structure are consistency requirements, which allow for arbitrary operation insertion and deletion at arbitrary moments. It is shown that efficient retroactivity, unlike persistence, is not always possible. In this work, the performance demonstrated their utility through real-world use cases and applications, in addition to going through the data structures employed in their implementation. The dynamic single source shortest path problem was successfully resolved by modifying the Dijkstra algorithm dynamically. The Dijkstra method is changed into a dynamic one via the retroactive priority queue data structure. Retroactive data structures identify the group of updated vertices one by one, requiring fewer calculations to accept the modifications. In order to dynamically adjust the Dijkstra method, which solves the dynamic single source shortest path problem with a quick update time, we used a suitable dynamic graph representation and a retroactive priority queue. A protein-protein interaction network is created for the protein involved in lung cancer and then the modified Dijkstra algorithm is applied to calculate the all-pair shortest path. Finally based on different metrics top 10 genes were summarised. |
| Databáze: |
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