Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks

Thesis (M.S.) -- Computer Science, May 2024

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Daou, Leonardo (author)
التنسيق: masterThesis
منشور في: 2024
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10725/16104
https://doi.org/10.26756/th.2023.705
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
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author Daou, Leonardo
author_facet Daou, Leonardo
author_role author
dc.creator.none.fl_str_mv Daou, Leonardo
dc.date.none.fl_str_mv 2024-09-12T08:29:33Z
2024-09-12T08:29:33Z
2024
2024-05-15
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/16104
https://doi.org/10.26756/th.2023.705
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Protein-protein interactions
Computational biology
Protein-protein interactions -- Computer simulation
Lebanese American University -- Dissertations
Dissertations, Academic
dc.title.none.fl_str_mv Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description Thesis (M.S.) -- Computer Science, May 2024
eu_rights_str_mv openAccess
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id LAURepo_2fcc61c798262ccff0554f6f558453b2
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/16104
publishDate 2024
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution NetworksDaou, LeonardoProtein-protein interactionsComputational biologyProtein-protein interactions -- Computer simulationLebanese American University -- DissertationsDissertations, AcademicThesis (M.S.) -- Computer Science, May 2024Protein complexes are groups of interacting proteins that are central to multiple biological processes. Studying protein complexes as well as their constituents can enhance our understanding of cellular functions and malfunctions, and thus leads to the development of more effective cures for diseases. High-throughput experimental techniques allow the generation of large-scale protein-protein interaction datasets. Accordingly, various computational approaches were proposed to predict protein complexes from protein-protein interaction networks in which nodes and edges represent proteins and their interactions, respectively. State-of-the-art approaches mainly rely on clustering static networks to identify complexes. However, since protein interactions are highly dynamic in nature, recent approaches seek to model such dynamics by typically integrating gene expression data and identifying protein complexes accordingly. We propose MComplex, a method that uses time-series gene expression with interaction data to generate a temporal network which is passed to a generative adversarial network that utilizes a graph convolutional network as generator. This creates embeddings which are then analyzed using a modified graph-based version of the Mapper algorithm to detect corresponding protein complexes. We test our approach on multiple benchmark datasets and compare identified complexes against gold-standard protein complex datasets. Our results show that MComplex outperforms existing methods in several evaluation aspects, namely recall and sensitivity as well as a composite score covering aggregated evaluation measures.1 online resource (xi, 81 leaves): ill. (some col.)Bibliography: leaves 74-81.Lebanese American University2024-09-12T08:29:33Z2024-09-12T08:29:33Z20242024-05-15Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/16104https://doi.org/10.26756/th.2023.705http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.phpeninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/161042024-12-06T13:54:19Z
spellingShingle Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
Daou, Leonardo
Protein-protein interactions
Computational biology
Protein-protein interactions -- Computer simulation
Lebanese American University -- Dissertations
Dissertations, Academic
status_str publishedVersion
title Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
title_full Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
title_fullStr Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
title_full_unstemmed Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
title_short Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
title_sort Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks
topic Protein-protein interactions
Computational biology
Protein-protein interactions -- Computer simulation
Lebanese American University -- Dissertations
Dissertations, Academic
url http://hdl.handle.net/10725/16104
https://doi.org/10.26756/th.2023.705
http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php