Real-world protein particle network reconstruction based on advanced hybrid features

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dc.contributor.authorGul, Haji
dc.contributor.authorAl-Obeidat, Feras
dc.contributor.authorTahir, Muhammad
dc.contributor.authorAmin, Adnan
dc.contributor.authorMoreira, Fernando
dc.date.accessioned2022-08-01T15:27:46Z
dc.date.available2022-08-01T15:27:46Z
dc.date.issued2022-04-21
dc.description.abstractBiological network proteins are key operational particles that substantially and operationally cooperate to bring out cellular progressions. Protein links with some other biological network proteins to accomplish their purposes. Physical collaborations are commonly referred to by the relationships of domain-level. The interaction among proteins and biological network reconstruction can be predicted based on various methods such as social theory, similarity, and topological features. Operational particles of proteins collaboration can be indirect among proteins based on mutual fields, subsequently particles of proteins involved in an identical biological progression be likely to harbor similar fields. To reconstruct the real-world network of proteins particles, some methods need only the notations of proteins domain, and then, it can be utilized to multiple species. A novel method we have introduced will analyze and reconstruct the real-world network of protein particles. The proposed technique works based on protein closeness, algebraic connectivity, and mutual proteins. Our proposed method was practically tested over different data sets and reported the results. Experimental results clearly show that the proposed technique worked best as compared to other state-of-the-art algorithms.pt_PT
dc.identifier.citationGul, H., Al-Obeidat, F., Moreira, F., Tahir, M., & Amin, A. (2022). Real-world protein particle network reconstruction based on advanced hybrid features. In A. Ullah, S. Anwar, Á. Rocha, & S. Gill (Eds.), Proceedings of International Conference on Information Technology and Applications. Lecture Notes in Networks and Systems, (vol. 350, pp. 15-22). Springer. https://doi.org/10.1007/978-981-16-7618-5_2. Repositório Institucional UPT. http://hdl.handle.net/11328/4390pt_PT
dc.identifier.doihttps://doi.org/10.1007/978-981-16-7618-5_2pt_PT
dc.identifier.isbn978-981-16-7617-8 (Print)
dc.identifier.isbn978-981-16-7618-5 (Online)
dc.identifier.urihttp://hdl.handle.net/11328/4390
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.rightsrestricted accesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectReconstruction biological networkpt_PT
dc.subjectProtein–protein interactionpt_PT
dc.subjectReal-world entity relationship predictionpt_PT
dc.subjectComplex networkspt_PT
dc.titleReal-world protein particle network reconstruction based on advanced hybrid featurespt_PT
dc.typeconferenceObjectpt_PT
degois.publication.firstPage15pt_PT
degois.publication.lastPage22pt_PT
degois.publication.titleProceedings of International Conference on Information Technology and Applications. Lecture Notes in Networks and Systemspt_PT
degois.publication.volume350pt_PT
dspace.entity.typePublicationen
person.affiliation.nameUniversidade Portucalense
person.familyNameMoreira
person.givenNameFernando
person.identifier.ciencia-id7B1C-3A29-9861
person.identifier.orcid0000-0002-0816-1445
person.identifier.ridP-9673-2016
person.identifier.scopus-author-id8649758400
relation.isAuthorOfPublicationbad3408c-ee33-431e-b9a6-cb778048975e
relation.isAuthorOfPublication.latestForDiscoverybad3408c-ee33-431e-b9a6-cb778048975e

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