A review of aligners for protein protein interaction networks

Ali, Anooja; Viswanath, P.; Patil, S. S.; Venugopal, K. R.

doi:10.1109/rteict.2017.8256879

Cited by 11 publications

(2 citation statements)

References 33 publications

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“…The correctness of an alignment is measured by the preservation of the network structure and the proteins functional information. See surveys (Ali, Viswanath, Patil, & Venugopal, 2017;Clark & Kalita, 2014;Elmsallati, Clark, & Kalita, 2016;Ma CY, 2020;Erten, 2021) for a review of implemented aligners and their evaluation. However, it is very difficult to fulfill both requirements.…”

Section: Introductionmentioning

confidence: 99%

PINAWeb: A web-based tool for the comparison of Protein-Protein Interaction Networks Aligners

Alcalá

Riera

García

et al. 2021

Preprint

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MotivationSeveral protein-protein interaction networks (PPIN) aligners have been developed during the last 15 years. One of their goals is to help the functional annotation of proteins and the prediction of protein-protein interactions. A correct aligner must preserve the network’s topology as well as the biological coherence. However, this is a trade-off that is hard to achieve. In addition, most aligners require a considerable effort to use in practice and many researchers must choose an aligner without the opportunity to previously compare the performance of different aligners.ResultsWe developed PINAWeb, a user-friendly web-based tool to obtain and compare the results produced by the aligners: AligNet, HubAlign, L-GRAAL, PINALOG and SPINAL. PPINs can be uploaded either from the STRING database or from a user database. The source code of PINAWeb is freely available on GitHub to enable researchers to add other aligners, network databases or alignment score metrics. In addition, PINAWeb provides a report with the analysis for every alignment in terms of topological and functional information scores, as well as the visualization of the alignments’ comparison (agreement/differences) when more than one aligner are considered.Availabilityhttps://bioinfo.uib.es/~recerca/PINAWeb

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Section: Introductionmentioning

confidence: 99%

PINAWeb: A web-based tool for the comparison of Protein-Protein Interaction Networks Aligners

Alcalá

Riera

García

et al. 2021

Preprint

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“…The knowledge of protein protein interactions can be used to diagnose diseases like auto immune disorders and cancer [8]. Several studies proved that rather than considering individual molecules, considering the interactions as a network is effective for many complex multi genetic diseases [9].…”

Section: Introductionmentioning

confidence: 99%

Alignment of Protein Interaction Networks and Disease Prediction: A Survey

Ali¹

2019

IJATCSE

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Proteins interact each other to perform many cellular activities. These interactions can be considered as Protein Protein Interaction networks (PPI). Interacting proteins form protein complexes. Mapping nodes between networks is denoted as alignment. The main intention of network alignment approach is to identify the protein complexes, which in turn helps to identify the functionality of protein complexes in various cellular systems. These interactome units form the conserved pathways between the networks. So network alignment requires lot of attention and several algorithms and techniques have been proposed to address this. The study of PPI is widely recognized to know more about the underlying complex disease because proteins associated with any disease get connected and form subgraphs or pathways. In this paper, the authors compared the various aligners, the performance evaluation metrics, the common databases used for PPI evaluation and the importance of PPI network in biomedical research.

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