Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Meaningful Infrastructures in Biological Networks: Related Studies, Algorithms and Evaluation Parameters

Version 1 : Received: 10 January 2022 / Approved: 12 January 2022 / Online: 12 January 2022 (14:17:32 CET)

How to cite: Ngobesing, L.A.; Atay, Y. Meaningful Infrastructures in Biological Networks: Related Studies, Algorithms and Evaluation Parameters. Preprints 2022, 2022010170 (doi: 10.20944/preprints202201.0170.v1). Ngobesing, L.A.; Atay, Y. Meaningful Infrastructures in Biological Networks: Related Studies, Algorithms and Evaluation Parameters. Preprints 2022, 2022010170 (doi: 10.20944/preprints202201.0170.v1).

Abstract

Abstract: In network science and big data, the concept of finding meaningful infrastructures in networks has emerged as a method of finding groups of entities with similar properties within very complex systems. The whole concept is generally based on finding subnetworks which have more properties (links) amongst nodes belonging to the same cluster than nodes in other groups (A concept presented by Girvan and Newman, 2002). Today meaningful infrastructure identification is applied in all types of networks from computer networks, to social networks to biological networks. In this article we will look at how meaningful infrastructure identification is applied in biological networks. This concept is important in biological networks as it helps scientist discover patterns in proteins or drugs which helps in solving many medical mysteries. This article will encompass the different algorithms that are used for meaningful infrastructure identification in biological networks. These include Genetic Algorithm, Differential Evolution, Water Cycle Algorithm (WCA), Walktrap Algorithm, Connect Intensity Iteration Algorithm (CIIA), Firefly algorithms and Overlapping Multiple Label Propagation Algorithm. These al-gorithms are compared with using performance measurement parameters such as the Mod-ularity, Normalized Mutual Information, Functional Enrichment, Recall and Precision, Re-dundancy, Purity and Surprise, which we will also discuss here.

Keywords

significative infrastructure; biological networks; normalized mutual information; recall; pre-cision; modularity; gene ontology

Subject

MATHEMATICS & COMPUTER SCIENCE, Other

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