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  1. 1

    Percolation theory using Python by Malthe-Sørenssen, Anders

    ISBN: 3031598997, 9783031598999, 3031599004, 9783031599002
    Published: Cham Springer 2024
    “… Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes…”
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    eBook Book
  2. 2

    Statistics Using Python by Campesato, Oswald

    ISBN: 9781683928805, 1683928806
    Published: Berlin Mercury Learning and Information 2024
    “…This book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors…”
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    eBook
  3. 3

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

    ISSN: 1549-960X, 1549-960X
    Published: 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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    Journal Article
  4. 4

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

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Published: England Oxford University Press 01.01.2023
    Published in 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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    Journal Article
  5. 5

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

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Published: England Oxford University Press 01.01.2023
    Published in 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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    Journal Article
  6. 6

    PHOTONAI—A Python API for rapid machine learning model development by 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
    Published: San Francisco Public Library of Science 21.07.2021
    Published in 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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    Journal Article
  7. 7

    Snakes on a Spaceship - An Overview of Python in Heliophysics by Burrell, A.G., Halford, A., Klenzing, J., Stoneback, R. A., Morley, S. K., Annex, A. M., Laundal, K. M., Kellerman, A. C., Stansby, D., Ma, J.

    ISSN: 2169-9380, 2169-9402
    Published: Goddard Space Flight Center AGU - American Geophysical Union 01.12.2018
    “…Computational analysis has become ubiquitous within the heliophysics community. However, community standards for peer review of codes and analysis have lagged behind these developments…”
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    Journal Article
  8. 8
  9. 9

    Micki: A python-based object-oriented microkinetic modeling code by Hermes, Eric D, Janes, Aurora N, Schmidt, J R

    ISSN: 1089-7690, 1089-7690
    Published: United States 07.07.2019
    Published in The Journal of chemical physics (07.07.2019)
    “… This Python-based code is modular and object oriented, framing the development of microkinetic models in familiar chemical terms…”
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    Journal Article
  10. 10

    galpy: A python LIBRARY FOR GALACTIC DYNAMICS by Bovy, Jo

    ISSN: 1538-4365, 0067-0049, 1538-4365
    Published: United States 01.02.2015
    “…I describe the design, implementation, and usage of galpy, a python package for galactic-dynamics calculations…”
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    Journal Article
  11. 11

    Detecting Memory Errors in Python Native Code by Tracking Object Lifecycle with Reference Count by Ma, Xutong, Yan, Jiwei, Zhang, Hao, Yan, Jun, Zhang, Jian

    ISSN: 2643-1572
    Published: IEEE 11.09.2023
    “… To detect such problems, state-of-the-art approaches have made groundbreaking contributions to identifying inappropriate final refcount values before returning from native code to Python…”
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    Conference Proceeding
  12. 12

    PBjam: A Python Package for Automating Asteroseismology of Solar-like Oscillators by Nielsen, M. B., Davies, G. R., Ball, W. H., Lyttle, A. J., Li 李坦, T. 达, Hall, O. J., Chaplin, W. J., Gaulme, P., Carboneau, L., Ong 王加, J. M. J. 冕, García, R. A., Mosser, B., Roxburgh, I. W., Corsaro, E., Benomar, O., Moya, A., Lund, M. N.

    ISSN: 0004-6256, 1538-3881, 1538-3881
    Published: Madison IOP Publishing 01.02.2021
    Published in The Astronomical journal (01.02.2021)
    “… So far the process of performing an asteroseismic analysis of a star has remained somewhat esoteric and inaccessible to nonexperts…”
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    Journal Article
  13. 13

    SBML2HYB: a Python interface for SBML compatible hybrid modeling by Pinto, José, Costa, Rafael S, Alexandre, Leonardo, Ramos, João, Oliveira, Rui

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Published: England Oxford University Press 01.01.2023
    Published in Bioinformatics (Oxford, England) (01.01.2023)
    “…Abstract Summary Here, we present sbml2hyb, an easy-to-use standalone Python tool that facilitates the conversion of existing mechanistic models of biological systems in Systems Biology Markup Language (SBML…”
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    Journal Article
  14. 14

    pyMBE: The Python-based molecule builder for ESPResSo by Beyer, David, Torres, Paola B, Pineda, Sebastian P, Narambuena, Claudio F, Grad, Jean-Noël, Košovan, Peter, Blanco, Pablo M

    ISSN: 1089-7690, 1089-7690
    Published: United States 14.07.2024
    Published in The Journal of chemical physics (14.07.2024)
    “…We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software application to design custom coarse-grained (CG…”
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    Journal Article
  15. 15

    powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions by Alstott, Jeff, Bullmore, Ed, Plenz, Dietmar

    ISSN: 1932-6203, 1932-6203
    Published: United States Public Library of Science 29.01.2014
    Published in PloS one (29.01.2014)
    “… In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package…”
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    Journal Article
  16. 16

    Kssdtree: an interactive Python package for phylogenetic analysis based on sketching technique by Yang, Hang, Lu, Xiaoxin, Chang, Jiaxing, Chang, Qing, Zheng, Wen, Chen, Zehua, Yi, Huiguang

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Published: England Oxford University Press 01.10.2024
    Published in Bioinformatics (Oxford, England) (01.10.2024)
    “… These limitations collectively impede the overall convenience and efficiency of the analysis. In this study, we introduce Kssdtree, an interactive Python package designed to address these challenges…”
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    Journal Article
  17. 17

    ABrox—A user-friendly Python module for approximate Bayesian computation with a focus on model comparison by Mertens, Ulf Kai, Voss, Andreas, Radev, Stefan

    ISSN: 1932-6203, 1932-6203
    Published: United States Public Library of Science 08.03.2018
    Published in PloS one (08.03.2018)
    “…We give an overview of the basic principles of approximate Bayesian computation (ABC), a class of stochastic methods that enable flexible and likelihood-free…”
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    Journal Article
  18. 18

    PyCG: Practical Call Graph Generation in Python by Salis, Vitalis, Sotiropoulos, Thodoris, Louridas, Panos, Spinellis, Diomidis, Mitropoulos, Dimitris

    ISBN: 1665402962, 9781665402965
    ISSN: 1558-1225
    Published: IEEE 01.05.2021
    “… We propose a pragmatic, static approach for call graph generation in Python. We compute all assignment relations between program identifiers of functions, variables, classes, and modules through an inter-procedural analysis…”
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    Conference Proceeding
  19. 19

    JBrowse Jupyter: a Python interface to JBrowse 2 by De Jesus Martinez, Teresa, Hershberg, Elliot A, Guo, Emma, Stevens, Garrett J, Diesh, Colin, Xie, Peter, Bridge, Caroline, Cain, Scott, Haw, Robin, Buels, Robert M, Stein, Lincoln D, Holmes, Ian H

    ISSN: 1367-4803, 1367-4811, 1367-4811
    Published: England Oxford University Press 01.01.2023
    Published in Bioinformatics (Oxford, England) (01.01.2023)
    “…Abstract Motivation JBrowse Jupyter is a package that aims to close the gap between Python programming and genomic visualization…”
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    Journal Article
  20. 20

    COBRApy: COnstraints-Based Reconstruction and Analysis for Python by Ebrahim, Ali, Lerman, Joshua A, Palsson, Bernhard O, Hyduke, Daniel R

    ISSN: 1752-0509, 1752-0509
    Published: London BioMed Central 08.08.2013
    Published in BMC systems biology (08.08.2013)
    “…Background COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes…”
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    Journal Article