Výsledky vyhľadávania - (( (stavba OR state:id) python code analysis ) OR ( state python code analysis ))~

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  1. 1

    The CoLoMoTo Interactive Notebook: Accessible and Reproducible Computational Analyses for Qualitative Biological Networks Autor Naldi, Aurélien, Hernandez, Céline, Levy, Nicolas, Stoll, Gautier, Monteiro, Pedro T., Chaouiya, Claudine, Helikar, Tomáš, Zinovyev, Andrei, Calzone, Laurence, Cohen-Boulakia, Sarah, Thieffry, Denis, Paulevé, Loïc

    ISSN: 1664-042X, 1664-042X
    Vydavateľské údaje: Switzerland Frontiers 19.06.2018
    Vydané v Frontiers in physiology (19.06.2018)
    “… The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve…”
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  2. 2

    Algorithm-Aided Design with Python: Analysis of Technological Competence of Subjects Autor Pontes, Thiago Bessa, Miranda, Guilhermina Lobato, Celani, Gabriela Caffarena

    ISSN: 2227-7102, 2227-7102
    Vydavateľské údaje: Basel MDPI AG 01.12.2018
    Vydané v Education sciences (01.12.2018)
    “… on the basis of the 4C-ID instructional design model. These results are a sociodemographic analysis, and the technological competence of these subjects…”
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  3. 3

    Analysis methods and code for very high-precision mass measurements of unstable isotopes Autor Karthein, J., Atanasov, D., Blaum, K., Lunney, D., Manea, V., Mougeot, M.

    ISSN: 0010-4655, 1879-2944
    Vydavateľské údaje: Elsevier B.V 01.10.2021
    Vydané v Computer physics communications (01.10.2021)
    “…We present a robust analysis code developed in the Python language and incorporating libraries of the ROOT data analysis framework for the state-of-the-art mass spectrometry method called phase…”
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  4. 4

    A Study of Large Language Models in Detecting Python Code Violations Autor Mohammed Salih, Hekar A., Sarhan, Qusay I.

    ISSN: 2410-9355, 2307-549X
    Vydavateľské údaje: Koya University 01.10.2025
    Vydané v ARO (Koya) (01.10.2025)
    “… Common static code analysis tools for Python, such as Pylint and Flake8, are widely used to enforce code quality by detecting coding violations without executing the code…”
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  5. 5

    Fast and Efficient XML Data Access for Next-Generation Mass Spectrometry Autor Röst, Hannes L., Schmitt, Uwe, Aebersold, Ruedi, Malmström, Lars

    ISSN: 1932-6203, 1932-6203
    Vydavateľské údaje: United States Public Library of Science 30.04.2015
    Vydané v PloS one (30.04.2015)
    “… the proteomics community to access algorithms in a vendor-independent fashion and perform transparent and reproducible data analysis…”
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  6. 6

    libRoadRunner 2.0: a high performance SBML simulation and analysis library Autor Welsh, Ciaran, Xu, Jin, Smith, Lucian, König, Matthias, Choi, Kiri, Sauro, Herbert M

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Vydavateľské údaje: England Oxford University Press 01.01.2023
    Vydané v Bioinformatics (Oxford, England) (01.01.2023)
    “…Abstract Motivation This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML…”
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  7. 7

    Dynamic Event Tree Analysis as a Tool for Risk Assessment in Nuclear Fusion Plants Using RAVEN and MELCOR Autor D'Onorio, Matteo, Glingler, Tommaso, Giannetti, Fabio, Caruso, Gianfranco

    ISSN: 0093-3813, 1939-9375
    Vydavateľské údaje: New York IEEE 01.11.2022
    Vydané v IEEE transactions on plasma science (01.11.2022)
    “…In the broad framework of the nuclear power plants (NPPs) industry, the dynamic probabilistic risk assessment could answer the time dependence deficiency of the event tree and fault tree analysis…”
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  8. 8

    PyLAT: Python LAMMPS Analysis Tools Autor Humbert, Michael T, Zhang, Yong, Maginn, Edward J

    ISSN: 1549-960X
    Vydavateľské údaje: United States 22.04.2019
    “… Here we describe a suite of open-source Python-based postprocessing routines we have developed called PyLAT…”
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  9. 9

    GSEApy: a comprehensive package for performing gene set enrichment analysis in Python Autor Fang, Zhuoqing, Liu, Xinyuan, Peltz, Gary

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Vydavateľské údaje: England Oxford University Press 01.01.2023
    Vydané v Bioinformatics (Oxford, England) (01.01.2023)
    “…Abstract Motivation Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes…”
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    GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries Autor Fachada, Nuno, Fernandes, Daniel, Fernandes, Carlos M., Ferreira-Saraiva, Bruno D., Matos-Carvalho, João P.

    ISSN: 1999-5903, 1999-5903
    Vydavateľské údaje: Basel MDPI AG 01.09.2025
    Vydané v Future internet (01.09.2025)
    “… unfamiliar Python APIs for complex computational experiments remains poorly characterized. This study systematically benchmarks a selection of state-of-the-art LLMs in generating functional Python code for two increasingly challenging scenarios…”
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    Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics Autor Goloborodko, Anton A., Levitsky, Lev I., Ivanov, Mark V., Gorshkov, Mikhail V.

    ISSN: 1044-0305, 1879-1123, 1879-1123
    Vydavateľské údaje: New York Springer-Verlag 01.02.2013
    “…Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics…”
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    VULCAN: An Open-source, Validated Chemical Kinetics Python Code for Exoplanetary Atmospheres Autor Tsai, Shang-Min, Lyons, James R., Grosheintz, Luc, Rimmer, Paul B., Kitzmann, Daniel, Heng, Kevin

    ISSN: 0067-0049, 1538-4365
    Vydavateľské údaje: United States The American Astronomical Society 01.02.2017
    “…We present an open-source and validated chemical kinetics code for studying hot exoplanetary atmospheres, which we name VULCAN…”
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    Scikit-Dimension: A Python Package for Intrinsic Dimension Estimation Autor Bac, Jonathan, Mirkes, Evgeny M., Gorban, Alexander N., Tyukin, Ivan, Zinovyev, Andrei

    ISSN: 1099-4300, 1099-4300
    Vydavateľské údaje: Switzerland MDPI AG 19.10.2021
    Vydané v Entropy (Basel, Switzerland) (19.10.2021)
    “…). A number of methods have been suggested for the purpose of estimating ID, but no standard package to easily apply them one by one or all at once has been implemented in Python…”
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    stk: A python toolkit for supramolecular assembly Autor Turcani, Lukas, Berardo, Enrico, Jelfs, Kim E.

    ISSN: 0192-8651, 1096-987X, 1096-987X
    Vydavateľské údaje: Hoboken, USA John Wiley & Sons, Inc 05.09.2018
    Vydané v Journal of computational chemistry (05.09.2018)
    “… stk is a modular, extensible and open‐source Python library that provides a simple Python API and integration with third party computational codes…”
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    MechElastic: A Python library for analysis of mechanical and elastic properties of bulk and 2D materials Autor Singh, Sobhit, Lang, Logan, Dovale-Farelo, Viviana, Herath, Uthpala, Tavadze, Pedram, Coudert, François-Xavier, Romero, Aldo H.

    ISSN: 0010-4655, 1879-2944
    Vydavateľské údaje: United States Elsevier B.V 01.10.2021
    Vydané v Computer physics communications (01.10.2021)
    “…The MechElastic Python package evaluates the mechanical and elastic properties of bulk and 2D materials using the elastic coefficient matrix (Cij…”
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  16. 16

    scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data Autor Faure, Louis, Soldatov, Ruslan, Kharchenko, Peter V, Adameyko, Igor

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Vydavateľské údaje: England Oxford University Press 01.01.2023
    Vydané v Bioinformatics (Oxford, England) (01.01.2023)
    “…Abstract Summary scFates provides an extensive toolset for the analysis of dynamic trajectories comprising tree learning, feature association testing, branch differential expression and with a…”
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    The fast azimuthal integration Python library: pyFAI Autor Ashiotis, Giannis, Deschildre, Aurore, Nawaz, Zubair, Wright, Jonathan P., Karkoulis, Dimitrios, Picca, Frédéric Emmanuel, Kieffer, Jérôme

    ISSN: 1600-5767, 0021-8898, 1600-5767
    Vydavateľské údaje: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01.04.2015
    Vydané v Journal of applied crystallography (01.04.2015)
    “… It is written in Python (with binary submodules for improved performance), a language widely accepted and used by the scientific community today, which enables users to easily incorporate the pyFAI library into their processing pipeline…”
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    pyIAST: Ideal adsorbed solution theory (IAST) Python package Autor Simon, Cory M., Smit, Berend, Haranczyk, Maciej

    ISSN: 0010-4655, 1879-2944
    Vydavateľské údaje: Netherlands Elsevier B.V 01.03.2016
    Vydané v Computer physics communications (01.03.2016)
    “… We present an open-source, user-friendly Python package, pyIAST, to perform IAST calculations for an arbitrary number of components…”
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    Deep learning for the diagnosis of mesial temporal lobe epilepsy Autor Sakashita, Kyoya, Akiyama, Yukinori, Hirano, Tsukasa, Sasagawa, Ayaka, Arihara, Masayasu, Kuribara, Tomoyoshi, Ochi, Satoko, Enatsu, Rei, Mikami, Takeshi, Mikuni, Nobuhiro

    ISSN: 1932-6203, 1932-6203
    Vydavateľské údaje: United States Public Library of Science (PLoS) 23.02.2023
    Vydané v PLOS ONE (23.02.2023)
    “… In this study, we used an AI program to diagnose MTLE. The image sets were processed using a code written in Python 3.7.4…”
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    PHOTONAI—A Python API for rapid machine learning model development Autor Leenings, Ramona, Winter, Nils Ralf, Plagwitz, Lucas, Holstein, Vincent, Ernsting, Jan, Sarink, Kelvin, Fisch, Lukas, Steenweg, Jakob, Kleine-Vennekate, Leon, Gebker, Julian, Emden, Daniel, Grotegerd, Dominik, Opel, Nils, Risse, Benjamin, Jiang, Xiaoyi, Dannlowski, Udo, Hahn, Tim

    ISSN: 1932-6203, 1932-6203
    Vydavateľské údaje: San Francisco Public Library of Science 21.07.2021
    Vydané v PloS one (21.07.2021)
    “…PHOTONAI is a high-level Python API designed to simplify and accelerate machine learning model development…”
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