Filters








2,128 Hits in 5.3 sec

An Extensive Assessment of Network Embedding in PPI Network Alignment

Marianna Milano, Chiara Zucco, Marzia Settino, Mario Cannataro
2022 Entropy  
In this survey, we present an overview of current PPI network embedding alignment methods, a comparison among them, and a comparison to classical PPI network alignment algorithms.  ...  A recent trend in network science concerns network embedding, i.e., the modelling of nodes in a network as a low-dimensional feature vector.  ...  that have addressed the problem of exploiting network embedding (NE) for network alignment (NA) in the context of PPI networks.  ... 
doi:10.3390/e24050730 pmid:35626613 pmcid:PMC9141406 fatcat:zpiu4mmmvza5rggc2xksajdscm

Learning Heat Diffusion for Network Alignment [article]

Sisi Qu, Mengmeng Xu, Bernard Ghanem, Jesper Tegner
2020 arXiv   pre-print
The EDNA algorithm is versatile in that other available network alignments/embeddings can be used as an initial baseline alignment, and then EDNA works as a wrapper around them by running the evolutionary  ...  In conclusion, EDNA outperforms state-of-the-art methods for network alignment, thus setting the stage for large-scale comparison and integration of networks.  ...  To assess the performance of our method EDNA, we feed two different features, ndegree feature and struc2vec embedding, of PPI networks into our pipeline and calculate baseline alignment on them. struc2vec  ... 
arXiv:2007.05401v1 fatcat:psh4n53chnb3lmast6jegikbsa

NetQuilt: Deep Multispecies Network-based Protein Function Prediction using Homology-informed Network Similarity [article]

Meet Barot, Vladimir Gligorijevic, Kyunghyun Cho, Richard Bonneau
2020 bioRxiv   pre-print
In this work, we integrate sequence and network information across multiple species by applying an IsoRank-derived network alignment algorithm to create a meta-network profile of the proteins of multiple  ...  Further, we evaluate our approach in a setting in which an organism's PPI network is left out, using other organisms' network information and sequence homology in order to make predictions for the left-out  ...  In [23] , an unsupervised neural network is used to learn embeddings from a tissue-specific multi-layer PPI graph. These task-independent embeddings are then used to predict multi-cellular function.  ... 
doi:10.1101/2020.07.30.227611 fatcat:hlson6rstfcnfdvu2v4zz3meii

Assessing and predicting protein interactions by combining manifold embedding with multiple information integration

Ying-Ke Lei, Zhu-Hong You, Zhen Ji, Lin Zhu, De-Shuang Huang
2012 BMC Bioinformatics  
Protein-protein interactions (PPIs) play crucial roles in virtually every aspect of cellular function within an organism.  ...  Validation of the proposed method was performed with extensive experiments on densely-connected and sparse PPI networks of yeast respectively.  ...  In this work, we take an alternative view of manifold embedding to develop an efficient algorithm that models PPI networks. It is based on isometric feature mapping (ISOMAP) [21, 54] .  ... 
doi:10.1186/1471-2105-13-s7-s3 pmid:22595000 pmcid:PMC3348017 fatcat:qmg2sykaizeepanqtj27vjp6tu

NetQuilt: Deep Multispecies Network-based Protein Function Prediction using Homology-informed Network Similarity

Meet Barot, Vladimir Gligorijević, Kyunghyun Cho, Richard Bonneau
2021 Bioinformatics  
We are able to demonstrate that our approach performs well even in cases where a species has no network information available: when an organism's PPI network is left out we can use our multi-species method  ...  learning sequence-based method, and the BLAST annotation method used in the Critial Assessment of Functional Annotation.  ...  Acknowledgements The authors thank Nicholas Carriero and Ian Fisk of the Flatiron Insitute for discussion and help with high performance computing.  ... 
doi:10.1093/bioinformatics/btab098 pmid:33576802 fatcat:zeqszhghvzd3nfxjm2nthxktsi

A Multi-Species Functional Embedding Integrating Sequence and Network Structure [article]

Jason Fan, Anthony Cannistra, Inbar Fried, Tim Lim, Thomas Schaffner, Mark Crovella, Benjamin Hescott, Mark DM Leiserson
2017 bioRxiv   pre-print
Specifically, our kernel-based method, HANDL (Homology Assessment across Networks using Diffusion and Landmarks), integrates sequence and network structure to create a functional embedding in which proteins  ...  Many approaches address this problem by expanding the notion of homology by leveraging high-throughput genomic and proteomic measurements, such as through network alignment.  ...  Acknowledgements This work was supported in part by NSF grants IIS-1421759 and CNS-1618207 (to M.C.) and by a grant from the Boston University Undergraduate Research Opportunities Program (to T.L.).  ... 
doi:10.1101/229211 fatcat:moj24tapgnfbzp3v4xp4uvccfm

A Survey on Evolutionary Analysis in PPI Networks [chapter]

Pavol Jancura, Elena Marchiori
2012 Protein-Protein Interactions - Computational and Experimental Tools  
The next natural extension is aligning more than two PPI networks, that is multiple network alignment.  ...  Evolution and modularity of PPI networks All the evidences above that PPIs whose proteins are evolutionary correlated tend to form stable complexes and to be embedded in cohesive areas of a network topology  ... 
doi:10.5772/37313 fatcat:t7airbrmjrd47l3qnv6fwjjplq

Global graph matching using diffusion maps

Jingtian Hu, Andrew L. Ferguson
2016 Intelligent Data Analysis  
We have tested our approach in pairwise alignments of protein-protein interaction networks of Xenopus laevis (frog), Rattus norvegicus (rat), Caenorhabditis elegans (worm), Mus musculus (mouse), and Drosophila  ...  We present a new algorithm, global positioning graph matching (GPGM), to perform global network alignments between pairs of undirected graphs by minimizing a dissimilarity score over matched vertices.  ...  Global Alignment of Distinct PPI Networks We assessed the performance of GPGM against IsoRank in computing global pairwise alignments between the largest connected component of the five PPI networks of  ... 
doi:10.3233/ida-160824 fatcat:mcubi3arjrg3tpr5xlgk7bcqja

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

Walter Nelson, Marinka Zitnik, Bo Wang, Jure Leskovec, Anna Goldenberg, Roded Sharan
2019 Frontiers in Genetics  
In particular, network embedding methods outshine direct methods according to some of those measures and are, thus, an essential tool in bioinformatics research.  ...  We consider a broad variety of applications including protein network alignment, community detection, and protein function prediction.  ...  An extensive review of methods for biological network alignment can be found in (Guzzi and Milenkovic, 2018) that mentions over thirty different approaches.  ... 
doi:10.3389/fgene.2019.00381 pmid:31118945 pmcid:PMC6504708 fatcat:t4h5izbezrfdbawvvcfutjyzlu

Deep Learning-Powered Prediction of Human-Virus Protein-Protein Interactions

Xiaodi Yang, Shiping Yang, Panyu Ren, Stefan Wuchty, Ziding Zhang
2022 Frontiers in Microbiology  
Recent advances in high-throughput experimental techniques enable the significant accumulation of human-virus PPI data, which have further fueled the development of machine learning-based human-virus PPI  ...  Identifying human-virus protein-protein interactions (PPIs) is an essential step for understanding viral infection mechanisms and antiviral response of the human host.  ...  AUTHOR CONTRIBUTIONS XY wrote the draft of the manuscript. ZZ supervised the work and significantly revised the manuscript. SW, SY, and PR revised the final version of manuscript.  ... 
doi:10.3389/fmicb.2022.842976 pmid:35495666 pmcid:PMC9051481 fatcat:hsbujsdghbeo7fjvn5pta2hjdq

SEQUOIA: significance enhanced network querying through context-sensitive random walk and minimization of network conductance

Hyundoo Jeong, Byung-Jun Yoon
2017 BMC Systems Biology  
Recent advances in technologies for high throughput measurement of protein-protein interactions have enabled genome-scale studies of protein interactions, and systematic analyses of the available PPI networks  ...  Conclusions: Performance assessment based on real PPI networks and known molecular complexes show that SEQUOIA outperforms existing methods and clearly enhances the biological significance of the query  ...  Acknowledgements This work was supported in part by the National Science Foundation through the NSF Award CCF-1149544.  ... 
doi:10.1186/s12918-017-0404-6 pmid:28361708 pmcid:PMC5374659 fatcat:6a5ir3bir5cqznm7lvljy4klqu

SEQUOIA

Hyundoo Jeong, Byung-Jun Yoon
2016 Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '16  
Recent advances in technologies for high throughput measurement of protein-protein interactions have enabled genome-scale studies of protein interactions, and systematic analyses of the available PPI networks  ...  Conclusions: Performance assessment based on real PPI networks and known molecular complexes show that SEQUOIA outperforms existing methods and clearly enhances the biological significance of the query  ...  Acknowledgements This work was supported in part by the National Science Foundation through the NSF Award CCF-1149544.  ... 
doi:10.1145/2975167.2985676 dblp:conf/bcb/JeongY16 fatcat:arggxqnbgrbt3eb6pptym6cvr4

Graph Spectral Embedding using the Geodesic Betweeness Centrality [article]

Shay Deutsch, Stefano Soatto
2022 arXiv   pre-print
edges in material science and network alignment in the human-SARS CoV-2 protein-protein interactome.  ...  We introduce the Graph Sylvester Embedding (GSE), an unsupervised graph representation of local similarity, connectivity, and global structure.  ...  Network alignment of Protein-protein interactions (PPIs) networks is considered as an important first step for the analysis of biological processes in computational biology.  ... 
arXiv:2205.03544v1 fatcat:klzrwr7mabh55fludsv6ndghxe

Functional protein representations from biological networks enable diverse cross-species inference

2019 Nucleic Acids Research  
Many current approaches for this problem leverage sequence and interaction network data to transfer knowledge across species, exemplified by network alignment methods.  ...  Specifically, our kernel-based method, MUNK, integrates sequence and network structure to create functional protein representations, embedding proteins from different species in the same vector space.  ...  (22) we constructed datasets of SLI from BioGRID (v3.4.157) in S.c. and S.p. sampling an equivalent number of non-SLI from pairs in the PPI network without an SLI.  ... 
doi:10.1093/nar/gkz132 pmid:30847485 pmcid:PMC6511848 fatcat:z36hvsjtq5bzpplb7fxq6tp3ye

A fast approach to global alignment of protein-protein interaction networks

Giorgos Kollias, Madan Sathe, Shahin Mohammadi, Ananth Grama
2013 BMC Research Notes  
Global network alignment has been proposed as an effective tool for computing functional orthology.  ...  Conclusions: We have demonstrated significant reductions in global network alignment computation times by coupling heuristic bipartite matching methods with the similarity scoring step of the IsoRank procedure  ...  Acknowledgements This work was supported by the Center for Science of Information (CSoI), an NSF Science and Technology Center, under grant agreement CCF-0939370, and by NSF grants DBI 0835677 and 0641037  ... 
doi:10.1186/1756-0500-6-35 pmid:23363457 pmcid:PMC3672019 fatcat:hv232aurzfdj7gvdha7iadpl5e
« Previous Showing results 1 — 15 out of 2,128 results