tag:joss.theoj.org,2005:/papers/tagged/graphJournal of Open Source Software2024-03-27T17:32:28ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/45642024-03-27T17:32:28Z2024-03-28T00:01:19ZRaphtory: The temporal graph engine for Rust and Pythonacceptedv0.4.22023-06-26 16:02:18 UTC952024-03-27 17:32:28 UTC920245940BenSteerPometry, United Kingdom, School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom0000-0001-9446-5690NaomiA.ArnoldNetworks Science Institute, Northeastern University London, United Kingdom0000-0001-6396-4788CheickTidianeUniversity of Milan, Italy, School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom0000-0002-4035-7464RenaudLambiotteMathematical Institute, University of Oxford, United Kingdom, Pometry, United Kingdom, Alan Turing Institute, United Kingdom0000-0002-0583-4595HaaroonYousafPometry, United Kingdom0000-0001-5098-5811LucasJeubPometry, United Kingdom0000-0001-8941-9227FabianMurariu32 Bytes Software, United KingdomShivamKapoorPometry, United KingdomPedroRicoPometry, United Kingdom0000-0002-4698-8435RachelChanPometry, United KingdomLouisChanPometry, United KingdomJamesAlfordPometry, United KingdomRichardG.CleggSchool of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom0000-0001-7241-6679FelixCuadradoUniversidad Politécnica de Madrid, Spain, School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom0000-0002-5745-1609MatthewRussellBarnesSchool of Electronic Engineering and Computer Science, Queen Mary University of London, United KingdomPeijieZhongSchool of Electronic Engineering and Computer Science, Queen Mary University of London, United KingdomJohnPougué-BiyongMathematical Institute, University of Oxford, United Kingdom0000-0002-6582-193XAlhamzaAlnaimiPometry, United Kingdom10.21105/joss.05940https://doi.org/10.5281/zenodo.10530613Python, Rusthttps://joss.theoj.org/papers/10.21105/joss.05940.pdftemporal networks, graphs, dynamicstag:joss.theoj.org,2005:Paper/48522024-03-09T21:38:19Z2024-03-11T01:37:29ZHyperNetX: A Python package for modeling complex network data as hypergraphsacceptedv2.0.52023-10-16 19:38:03 UTC952024-03-09 21:38:19 UTC920246016BrendaPraggastisPacific Northwest National Laboratory, USA0000-0003-1344-0497SinanAksoyPacific Northwest National Laboratory, USA0000-0002-3466-3334DustinArendtPacific Northwest National Laboratory, USA0000-0003-2466-199XMarkBonicilloPacific Northwest National Laboratory, USA0009-0003-9764-2180CliffJoslynPacific Northwest National Laboratory, USA0000-0002-5923-5547EmiliePurvinePacific Northwest National Laboratory, USA0000-0003-2069-5594MadelynShapiroPacific Northwest National Laboratory, USA0000-0002-2786-7056JiYoungYunPacific Northwest National Laboratory, USA10.21105/joss.06016https://doi.org/10.5281/zenodo.10795225Pythonhttps://joss.theoj.org/papers/10.21105/joss.06016.pdfhypergraph, network science, simplicial-complexes, knowledge graph, simplicial-homology, s-linegraph, property hypergraphtag:joss.theoj.org,2005:Paper/48132024-02-27T21:24:38Z2024-03-22T14:09:24ZDeepRank2: Mining 3D Protein Structures with Geometric Deep Learningacceptedv2.1.02023-09-22 15:36:51 UTC942024-02-27 21:24:38 UTC920245983GiuliaCrocioniNetherlands eScience Center, Amsterdam, The Netherlands0000-0002-0823-0121DaniL.BodorNetherlands eScience Center, Amsterdam, The Netherlands0000-0003-2109-2349CoosBaakmanThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0003-4317-1566FarzanehM.PariziThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0003-4230-7492Daniel-T.RademakerThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0003-1959-1317GayatriRamakrishnanThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0001-8203-2783SvenA.van der BurgNetherlands eScience Center, Amsterdam, The Netherlands0000-0003-1250-6968DarioF.MarzellaThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0002-0043-3055JoãoM.c.TeixeiraIndependent Researcher0000-0002-9113-0622LiC.XueThe Department of Medical BioSciences, Radboud University Medical Center, Nijmegen, The Netherlands0000-0002-2613-538X10.21105/joss.05983https://doi.org/10.5281/zenodo.10566809Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05983.pdfPyTorch, structural biology, geometric deep learning, 3D protein structures, protein-protein interfaces, single-residue variants, graph neural networks, convolutional neural networks, DeepRanktag:joss.theoj.org,2005:Paper/49042024-01-19T08:12:03Z2024-01-20T00:00:42ZCM++ - A Meta-method for Well-Connected Community Detectionacceptedv4.0.02023-10-29 23:28:31 UTC932024-01-19 08:12:03 UTC920246073VikramRamavarapuDepartment of Computer Science, University of Illinois Urbana-Champaign, IL 61801, USA0009-0001-8875-7213FábioJoseAyresInsper Institute, Sao Paulo, Brazil0009-0000-6821-4687MinhyukParkDepartment of Computer Science, University of Illinois Urbana-Champaign, IL 61801, USA0000-0002-8676-7565VidyaKamathPailodiDepartment of Computer Science, University of Illinois Urbana-Champaign, IL 61801, USA0009-0000-0987-5901JoãoAlfredo CardosoLamyInsper Institute, Sao Paulo, Brazil0009-0005-4744-4754TandyWarnowDepartment of Computer Science, University of Illinois Urbana-Champaign, IL 61801, USA0000-0001-7717-3514GeorgeChackoDepartment of Computer Science, University of Illinois Urbana-Champaign, IL 61801, USA0000-0002-2127-189210.21105/joss.06073https://doi.org/10.5281/zenodo.10501118Python, Rhttps://joss.theoj.org/papers/10.21105/joss.06073.pdfCM++, connectivity, minimum cut, complex network analysis, graph, network, degree, clusteringtag:joss.theoj.org,2005:Paper/45652023-10-01T12:42:45Z2023-10-02T00:01:29ZPyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphsacceptedv1.3.12023-06-26 18:09:02 UTC902023-10-01 12:42:45 UTC820235713FedericoErricaNEC Laboratories Europe, Germany0000-0001-5181-2904DavideBacciuUniversity of Pisa, Italy0000-0001-5213-2468AlessioMicheliUniversity of Pisa, Italy0000-0001-5764-523810.21105/joss.05713https://doi.org/10.5281/zenodo.8396373Pythonhttps://joss.theoj.org/papers/10.21105/joss.05713.pdfMachine Learning, Graph Networks, Deep Learning for Graphstag:joss.theoj.org,2005:Paper/40032023-08-25T03:11:09Z2023-08-26T00:01:24ZGNS: A generalizable Graph Neural Network-based simulator for particulate and fluid modelingacceptedv1.0.12022-11-13 22:08:21 UTC882023-08-25 03:11:09 UTC820235025KrishnaKumarAssistant Professor, University of Texas at Austin, Texas, USA0000-0003-2144-5562JosephVantasselAssistant Professor, Virginia Tech, Virginia, USA, Texas Advanced Computing Center, University of Texas at Austin, Texas, USA0000-0002-1601-335410.21105/joss.05025https://doi.org/10.5281/zenodo.8249813Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05025.pdfmachine learning, simulationtag:joss.theoj.org,2005:Paper/39922023-08-14T16:45:04Z2023-08-17T12:43:29ZdiscourseGT: An R package to analyze discourse networks in educational contextsaccepted1.1.82022-11-09 00:14:01 UTC882023-08-14 16:45:04 UTC820235143QiCuiUniversity of California, San Diego0000-0002-3034-1143JoshuaP.LeUniversity of California, San Diego0000-0003-0872-7098AlbertChaiUniversity of California, San Diego0000-0002-2340-7044AndrewS. Lee WithoutOrcidUniversity of California, Los AngelesJitarthSheth WithoutOrcidUniversity of California, San DiegoKevinBanh WithoutOrcidUniversity of California, San DiegoPriyaPahal WithoutOrcidUniversity of California, San DiegoKatherineLy WithoutOrcidUniversity of California, San DiegoStanleyM.LoUniversity of California, San Diego0000-0003-3574-219710.21105/joss.05143https://doi.org/10.5281/zenodo.8164950Rhttps://joss.theoj.org/papers/10.21105/joss.05143.pdfstudent group work, discourse network, graph theory, discourseGTtag:joss.theoj.org,2005:Paper/41632023-08-04T17:14:02Z2023-08-05T00:01:33ZCNATool - Complex Network Analysis Toolaccepted2.0.42023-01-14 22:39:11 UTC882023-08-04 17:14:02 UTC820235373RobertoLuiz SouzaMonteiroSENAI CIMATEC University Center, Brasil \newline, Universidade do Estado da Bahia, Brasil \newline0000-0002-3931-5953RenataSouza Freitas DantasBarretoUniversidade do Estado da Bahia, Brasil \newline0000-0002-1607-4800AndréiaRitada SilvaUniversidade do Estado da Bahia, Brasil \newline0009-0009-0587-1263Alexandredo NascimentoSilvaUniversidade do Estado da Bahia, Brasil \newline, Universidade Estadual de Santa Cruz, Brasil \newline0000-0001-7436-8818JoséRoberto Araújode FontouraUniversidade do Estado da Bahia, Brasil \newline0000-0002-9703-835XMarcosBatistaFigueredoUniversidade do Estado da Bahia, Brasil \newline0000-0002-8193-5419HernaneBorges Barrosde PereiraSENAI CIMATEC University Center, Brasil \newline, Universidade do Estado da Bahia, Brasil \newline0000-0001-7476-926710.21105/joss.05373https://doi.org/10.5281/zenodo.8206265JavaScripthttps://joss.theoj.org/papers/10.21105/joss.05373.pdfCNATool, complex network analysis, graph, network, degree, clustering, centrality, Pajektag:joss.theoj.org,2005:Paper/43152023-07-19T16:44:11Z2023-07-21T12:42:35ZNetgraph: Publication-quality Network Visualisations in Pythonaccepted4.12.42023-03-16 15:43:55 UTC872023-07-19 16:44:11 UTC820235372PaulJ. n.BrodersenDepartment of Pharmacology, University of Oxford, United Kingdom0000-0001-5216-786310.21105/joss.05372https://doi.org/10.5281/zenodo.8138403Pythonhttps://joss.theoj.org/papers/10.21105/joss.05372.pdfgraph, network, visualisation, visualization, matplotlib, networkx, igraph, graph-tooltag:joss.theoj.org,2005:Paper/39442023-05-12T12:14:29Z2023-05-13T00:01:21ZGraphNeT: Graph neural networks for neutrino telescope event reconstructionacceptedv0.2.22022-10-06 11:55:25 UTC852023-05-12 12:14:29 UTC820234971AndreasSøgaardNiels Bohr Institute, University of Copenhagen, Denmark0000-0002-0823-056XRasmusF.ØrsøeNiels Bohr Institute, University of Copenhagen, Denmark, Technical University of Munich, Germany0000-0001-8890-4124MortenHolmNiels Bohr Institute, University of Copenhagen, Denmark0000-0003-1383-2810LeonBozianuNiels Bohr Institute, University of Copenhagen, Denmark0000-0002-1243-9980AskeRostedChiba University, Japan0000-0003-2410-400XTroelsC.PetersenNiels Bohr Institute, University of Copenhagen, Denmark0000-0003-0221-3037KaareEndrupIversenNiels Bohr Institute, University of Copenhagen, Denmark0000-0001-6533-4085AndreasHermansenNiels Bohr Institute, University of Copenhagen, Denmark0009-0006-1162-9770TimGuggenmosTechnical University of Munich, GermanyPeterAndresenNiels Bohr Institute, University of Copenhagen, Denmark0009-0008-5759-0490MartinHaMinhTechnical University of Munich, Germany0000-0001-7776-4875LudwigNesteTechnical University of Dortmund, Germany0000-0002-4829-3469MoustHolmesNiels Bohr Institute, University of Copenhagen, Denmark0009-0000-8530-7041AxelPonténUppsala University, Sweden0009-0008-2463-2930KaylaLeonardDeHoltonPennsylvania State University, USA0000-0002-8795-0601PhilippEllerTechnical University of Munich, Germany0000-0001-6354-520910.21105/joss.04971https://doi.org/10.5281/zenodo.7928487Pythonhttps://joss.theoj.org/papers/10.21105/joss.04971.pdfmachine learning, deep learning, neural networks, graph neural networks, astrophysics, particle physics, neutrinos