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  1. 1

    Decoding the JAK-STAT Axis in Colorectal Cancer with AI-HOPE-JAK-STAT: A Conversational Artificial Intelligence Approach to Clinical–Genomic Integration by Yang, Ei-Wen, Waldrup, Brigette, Velazquez-Villarreal, Enrique

    ISSN: 2072-6694, 2072-6694
    Published: Switzerland MDPI AG 17.07.2025
    Published in Cancers (17.07.2025)
    “…: AI-HOPE-JAK-STAT combines large language models (LLMs), a natural language-to-code engine, and harmonized public CRC datasets from cBioPortal…”
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    Journal Article
  2. 2

    Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial by Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

    ISSN: 0277-6715, 1097-0258, 1097-0258
    Published: England Wiley Subscription Services, Inc 30.01.2022
    Published in Statistics in medicine (30.01.2022)
    “…The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize…”
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    Journal Article
  3. 3

    LiPydomics: A Python Package for Comprehensive Prediction of Lipid Collision Cross Sections and Retention Times and Analysis of Ion Mobility-Mass Spectrometry-Based Lipidomics Data by Ross, Dylan H, Cho, Jang Ho, Zhang, Rutan, Hines, Kelly M, Xu, Libin

    ISSN: 1520-6882, 1520-6882
    Published: United States 17.11.2020
    Published in Analytical chemistry (Washington) (17.11.2020)
    “… Existing solutions for these data analysis challenges (i.e., multivariate statistics and lipid identification…”
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    Journal Article
  4. 4

    MEG and EEG data analysis with MNE-Python by Gramfort, Alexandre

    ISSN: 1662-453X, 1662-4548, 1662-453X
    Published: Switzerland Frontiers Research Foundation 26.12.2013
    Published in Frontiers in neuroscience (26.12.2013)
    “… As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple…”
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    Journal Article
  5. 5

    Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors by Peng, Yun, Gao, Shuzheng, Gao, Cuiyun, Huo, Yintong, Lyu, Michael R.

    ISSN: 1558-1225
    Published: ACM 14.04.2024
    “…As a dynamic programming language, Python has become increasingly popular in recent years…”
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    Conference Proceeding
  6. 6

    Discovering Repetitive Code Changes in Python ML Systems by Dilhara, Malinda, Ketkar, Ameya, Sannidhi, Nikhith, Dig, Danny

    ISSN: 1558-1225
    Published: ACM 01.05.2022
    “… Despite the extraordinary rise in popularity of Python-based ML systems, they do not benefit from these advances…”
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    Conference Proceeding
  7. 7

    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
  8. 8

    Evaluating Large Language Models in Class-Level Code Generation by Du, Xueying, Liu, Mingwei, Wang, Kaixin, Wang, Hanlin, Liu, Junwei, Chen, Yixuan, Feng, Jiayi, Sha, Chaofeng, Peng, Xin, Lou, Yiling

    ISSN: 1558-1225
    Published: ACM 14.04.2024
    “…Recently, many large language models (LLMs) have been proposed, showing advanced proficiency in code generation…”
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    Conference Proceeding
  9. 9
  10. 10

    A Python Instrument Control and Data Acquisition Suite for Reproducible Research by Koerner, Lucas J., Caswell, Thomas A., Allan, Daniel B., Campbell, Stuart I.

    ISSN: 0018-9456, 1557-9662
    Published: New York IEEE 01.04.2020
    “… The National Synchrotron Light Source-II (NSLS-II) has generated an open-source Python data acquisition, management, and analysis software suite that automates X-ray…”
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    Journal Article
  11. 11

    PyTy: Repairing Static Type Errors in Python by Chow, Yiu Wai, Di Grazia, Luca, Pradel, Michael

    ISSN: 1558-1225
    Published: ACM 14.04.2024
    “… As more and more code bases get type-annotated, static type checkers detect an increasingly large number of type errors…”
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    Conference Proceeding
  12. 12

    Nestedness for Dummies (NeD): A user friendly web interface for exploratory nestedness analysis by Strona, Giovanni, Galli, Paolo, Seveso, Davide, Montano, Simone, Fattorini, Simone

    ISSN: 1548-7660, 1548-7660
    Published: Foundation for Open Access Statistics 01.08.2014
    Published in Journal of statistical software (01.08.2014)
    “…Recent theoretical advances in nestedness analysis have led to the introduction of several alternative metrics to overcome most of the problems biasing the use of matrix 'temperature' calculated…”
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    Journal Article
  13. 13

    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
  14. 14

    SpotFlow: Tracking Method Calls and States at Runtime by Hora, Andre

    ISSN: 2574-1934
    Published: ACM 14.04.2024
    “… In this paper, we propose SpotFlow, a tool to ease the runtime analysis of Python programs. With Spot-Flow, practitioners and researchers can easily extract information…”
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    Conference Proceeding
  15. 15

    CoverUp: Effective High Coverage Test Generation for Python by Altmayer Pizzorno, Juan, Berger, Emery D.

    ISSN: 2994-970X, 2994-970X
    Published: New York, NY, USA ACM 19.06.2025
    “… We evaluate our prototype CoverUp implementation across a benchmark of challenging code derived from open-source Python projects and show that CoverUp substantially improves on the state of the art…”
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    Journal Article
  16. 16

    SNPAAMapper-Python: A highly efficient genome-wide SNP variant analysis pipeline for Next-Generation Sequencing data by Li, Chang, Ma, Kevin, Xu, Nicole, Fu, Chenjian, He, Andrew, Liu, Xiaoming, Bai, Yongsheng

    ISSN: 2624-8212, 2624-8212
    Published: Frontiers Media S.A 12.09.2022
    Published in Frontiers in artificial intelligence (12.09.2022)
    “… In this study, we updated SNPAAMapper, a variant annotation pipeline by converting perl codes to python for generating annotation output with an improved computational efficiency and updated…”
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    Journal Article
  17. 17

    Bloat beneath Python’s Scales: A Fine-Grained Inter-Project Dependency Analysis by Drosos, Georgios-Petros, Sotiropoulos, Thodoris, Spinellis, Diomidis, Mitropoulos, Dimitris

    ISSN: 2994-970X, 2994-970X
    Published: New York, NY, USA ACM 12.07.2024
    “… In this work, we conduct a large-scale, fine-grained analysis to understand bloated dependency code in the PyPI ecosystem…”
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    Journal Article
  18. 18

    Inspect4py: A Knowledge Extraction Framework for Python Code Repositories by Filgueira, Rosa, Garijo, Daniel

    ISSN: 2574-3864
    Published: ACM 01.05.2022
    “…This work presents inspect4py, a static code analysis framework designed to automatically extract the main features, metadata and documentation of Python code repositories…”
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    Conference Proceeding
  19. 19

    Unleashing the Giants: Enabling Advanced Testing for Infrastructure as Code by Sokolowski, Daniel, Spielmann, David, Salvaneschi, Guido

    ISSN: 2574-1934
    Published: ACM 14.04.2024
    “…Infrastructure as Code (IaC) programs are written in imperative programming languages like Python or TypeScript while declar-atively defining the target state of software deployments, which the IaC solution then sets up, e.g…”
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    Conference Proceeding
  20. 20

    From code to reliability: Python-powered Paraconsistent Logic for alarm detection in the power gris/ Do codigo a confiabilidade: Logica Paraconsistente impulsionada por Python para a deteccao de alarmes na rede de energia by de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

    ISSN: 2178-9010, 2178-9010
    Published: Sindicato das Secretarias e Secretarios do Estado de Sao Paulo 01.10.2023
    Published in GeSec : Revista de Gestão e Secretariado (01.10.2023)
    “… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis…”
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    Journal Article