tag:joss.theoj.org,2005:/papers/tagged/networksJournal of Open Source Software2024-03-09T21:38:19ZJournal of Open Source Softwarehttps://joss.theoj.orgtag: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/48582024-03-06T17:32:25Z2024-03-07T00:00:24Zcalorine: A Python package for constructing and sampling neuroevolution potential modelsacceptedv2.02023-10-21 15:02:27 UTC952024-03-06 17:32:25 UTC920246264EricLindgrenDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-8549-6839MagnusRahmDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-6777-0371ErikFranssonDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0001-5262-3339FredrikErikssonDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-7945-5483NicklasÖsterbackaDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-6043-4607ZheyongFanCollege of Physical Science and Technology, Bohai University, Jinzhou 121013, P. R. China0000-0002-2253-8210PaulErhartDepartment of Physics, Chalmers University of Technology, Gothenburg 412 96, Sweden0000-0002-2516-606110.21105/joss.06264https://doi.org/10.5281/zenodo.10723374Python, C++, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.06264.pdfcondensed matter, machine learning, interatomic potentials, force fields, molecular dynamics, neuroevolution, neural networktag:joss.theoj.org,2005:Paper/48132024-02-27T21:24:38Z2024-03-15T08:45:59ZDeepRank2: 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 Netherlands0000-0003-2109-2349CoosBaakmanCenter for Molecular Bioinformatics, Radboud Universitair Medisch Centrum, Nijmegen, Gelderland, The Netherlands0000-0003-4317-1566FarzanehM.PariziCenter for Molecular Bioinformatics, Radboud Universitair Medisch Centrum, Nijmegen, Gelderland, The Netherlands0000-0003-4230-7492Daniel-T.RademakerCenter for Molecular Bioinformatics, Radboud Universitair Medisch Centrum, Nijmegen, Gelderland, The Netherlands0000-0003-1959-1317GayatriRamakrishnanCenter for Molecular Bioinformatics, Radboud Universitair Medisch Centrum, Nijmegen, Gelderland, The Netherlands0000-0001-8203-2783SvenA.van der BurgNetherlands eScience Center, Amsterdam, The Netherlands0000-0003-1250-6968DarioF.MarzellaCenter for Molecular Bioinformatics, Radboud Universitair Medisch Centrum, Nijmegen, Gelderland, The Netherlands0000-0002-0043-3055JoãoM.c.TeixeiraIndependent Researcher0000-0002-9113-0622LiC.XueCenter for Molecular Bioinformatics, Radboud Universitair Medisch Centrum, Nijmegen, Gelderland, 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/45532024-02-25T16:09:51Z2024-02-26T00:00:51ZPyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operatoracceptedv1.0.32023-06-20 18:07:16 UTC942024-02-25 16:09:51 UTC920245881ShaowuPanDepartment of Applied Mathematics, University of Washington, Seattle, WA 98195, United States, Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, United States0000-0002-2462-362XEurikaKaiserDepartment of Mechanical Engineering, University of Washington, Seattle, WA 98195, United States0000-0001-6049-0812BrianM.de SilvaDepartment of Applied Mathematics, University of Washington, Seattle, WA 98195, United States0000-0003-0944-900XJ.NathanKutzDepartment of Applied Mathematics, University of Washington, Seattle, WA 98195, United States0000-0002-6004-2275StevenL.BruntonDepartment of Mechanical Engineering, University of Washington, Seattle, WA 98195, United States0000-0002-6565-511810.21105/joss.05881https://doi.org/10.5281/zenodo.10685233Pythonhttps://joss.theoj.org/papers/10.21105/joss.05881.pdfdynamical systems, Koopman operator, system identification, machine learning, neural networkstag: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/47282024-01-17T17:48:17Z2024-01-18T00:00:51Znetroles: A Java library for role equivalence analysis in networksacceptedv0.22023-08-31 16:13:57 UTC932024-01-17 17:48:17 UTC920245903JulianMüllerSocial Networks Lab, ETH Zürich, Switzerland, Institute of Computing, Università della Svizzera italiana, Switzerland0000-0001-6440-804610.21105/joss.05903https://doi.org/10.5281/zenodo.10070537Groovy, Javahttps://joss.theoj.org/papers/10.21105/joss.05903.pdfnetwork analysis, role analysistag:joss.theoj.org,2005:Paper/45602023-12-04T17:06:09Z2023-12-05T00:00:57ZEPyT: An EPANET-Python Toolkit for Smart Water Network Simulationsacceptedv1.0.62023-06-24 07:51:13 UTC922023-12-04 17:06:09 UTC820235947MariosS.KyriakouKIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus0000-0002-2324-8661MariosDemetriadesKIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus0000-0001-7775-4319SteliosG.VrachimisKIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus, Department of Electrical and Computer Engineering, University of Cyprus, Cyprus0000-0001-8862-5205DemetriosG.EliadesKIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus0000-0001-6184-6366MariosM.PolycarpouKIOS Research and Innovation Center of Excellence, University of Cyprus, Cyprus, Department of Electrical and Computer Engineering, University of Cyprus, Cyprus0000-0001-6495-917110.21105/joss.05947https://doi.org/10.5281/zenodo.10223298Python, Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05947.pdfEPANET, smart water networks, hydraulics, water quality, simulationtag:joss.theoj.org,2005:Paper/47102023-11-21T14:35:15Z2023-11-22T00:01:03ZPhasik: a Python package to identify system states in partially temporal networksacceptedv1.3.22023-08-19 19:13:03 UTC912023-11-21 14:35:15 UTC820235872MaximeLucasCENTAI Institute, Turin, Italy0000-0001-8087-2981AlexTownsend-TeagueDahlem Center for Complex Quantum Systems, Freie Universitat Berlin, 14195 Berlin, GermanyMatteoNeriCENTAI Institute, Turin, Italy, Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, Marseille 13005, France0009-0007-0998-552XSimonePoettoCENTAI Institute, Turin, Italy, Center for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, PolandArthurMorrisTheory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, J. J. Thomson Avenue, Cambridge CB3 0HE, United KingdomBiancaHabermannAix Marseille University, CNRS, IBDM UMR 7288, Turing Center for Living Systems, Marseille, France0000-0002-2457-7504LaurentTichitAix Marseille University, CNRS, I2M UMR 7373, Turing Center for Living Systems, Marseille, France0000-0002-8350-144610.21105/joss.05872https://doi.org/10.5281/zenodo.10113244Jupyter Notebook, Pythonhttps://joss.theoj.org/papers/10.21105/joss.05872.pdftemporal networkstag:joss.theoj.org,2005:Paper/43692023-11-07T16:38:40Z2023-11-09T00:00:29Zpyflowline: a mesh-independent river network generator for hydrologic modelsacceptedv0.2.22023-03-27 23:32:35 UTC912023-11-07 16:38:40 UTC820235446ChangLiaoAtmospheric, Climate, and Earth Sciences, Pacific Northwest National Laboratory, Richland, WA, USA0000-0002-7348-8858MattG.CooperAtmospheric, Climate, and Earth Sciences, Pacific Northwest National Laboratory, Richland, WA, USA0000-0002-0165-209X10.21105/joss.05446https://doi.org/10.5281/zenodo.10076553Jupyter Notebookhttps://joss.theoj.org/papers/10.21105/joss.05446.pdfPython, hydrologic model, river networks, mesh, geographic information systemtag:joss.theoj.org,2005:Paper/45982023-10-13T08:34:18Z2023-10-14T00:00:39Zchessboard: An R package for creating network connections based on chess movesaccepted0.12023-07-13 08:51:14 UTC902023-10-13 08:34:18 UTC820235753NicolasCasajusFRB-CESAB, Montpellier, France0000-0002-5537-5294ÉricaRievrsBorgesFRB-CESAB, Montpellier, France0000-0001-7751-6265ÉricTabacchiCNRS, Toulouse, France0000-0001-7729-4439GuillaumeFriedANSES, Montpellier, France0000-0002-3653-195XNicolasMouquetFRB-CESAB, Montpellier, France, MARBEC, Univ Montpellier, CNRS, IFREMER, IRD, Montpellier, France0000-0003-1840-698410.21105/joss.05753https://doi.org/10.5281/zenodo.8424609Rhttps://joss.theoj.org/papers/10.21105/joss.05753.pdfr, package, networks, neighbors, edges