Suchergebnisse - (( (stated OR stat) python code analysis ) OR ( (statement OR state:new) python code analysis ))~

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

“… 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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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 von Ross, Dylan H, Cho, Jang Ho, Zhang, Rutan, Hines, Kelly M, Xu, Libin

“… Existing solutions for these data analysis challenges (i.e., multivariate statistics and lipid identification …”
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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 von de Oliveira, Joseffe Barroso, Gino, Joao Vitor Santa Rosa, de Lima, Carlos Jose, Filho, Joao Inacio da Silva

“… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis …”
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Decoding the JAK-STAT Axis in Colorectal Cancer with AI-HOPE-JAK-STAT: A Conversational Artificial Intelligence Approach to Clinical–Genomic Integration von Yang, Ei-Wen, Waldrup, Brigette, Velazquez-Villarreal, Enrique

“… : 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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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data von Pakkir Shah, Abzer K., Walter, Axel, Ottosson, Filip, Russo, Francesco, Navarro-Diaz, Marcelo, Boldt, Judith, Kalinski, Jarmo-Charles J., Kontou, Eftychia Eva, Elofson, James, Polyzois, Alexandros, González-Marín, Carolina, Farrell, Shane, Aggerbeck, Marie R., Pruksatrakul, Thapanee, Chan, Nathan, Wang, Yunshu, Pöchhacker, Magdalena, Brungs, Corinna, Cámara, Beatriz, Caraballo-Rodríguez, Andrés Mauricio, Cumsille, Andres, de Oliveira, Fernanda, Dührkop, Kai, El Abiead, Yasin, Geibel, Christian, Graves, Lana G., Hansen, Martin, Heuckeroth, Steffen, Knoblauch, Simon, Kostenko, Anastasiia, Kuijpers, Mirte C. M., Mildau, Kevin, Papadopoulos Lambidis, Stilianos, Portal Gomes, Paulo Wender, Schramm, Tilman, Steuer-Lodd, Karoline, Stincone, Paolo, Tayyab, Sibgha, Vitale, Giovanni Andrea, Wagner, Berenike C., Xing, Shipei, Yazzie, Marquis T., Zuffa, Simone, de Kruijff, Martinus, Beemelmanns, Christine, Link, Hannes, Mayer, Christoph, van der Hooft, Justin J. J., Damiani, Tito, Pluskal, Tomáš, Dorrestein, Pieter, Stanstrup, Jan, Schmid, Robin, Wang, Mingxun, Aron, Allegra, Ernst, Madeleine, Petras, Daniel

“… Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices …”
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Generation of Scale-Free Assortative Networks via Newman Rewiring for Simulation of Diffusion Phenomena von Di Lucchio, Laura, Modanese, Giovanni

“… By collecting and expanding several numerical recipes developed in previous work, we implement an object-oriented Python code, based on the networkX library, for the realization of the configuration …”
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Percolation theory using Python von Malthe-Sørenssen, Anders

“… 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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Python Data Analyst's Toolkit - Learn Python and Python-Based Libraries with Applications in Data Analysis and Statistics von Rajagopalan, Gayathri

“… The code is presented in Jupyter notebooks that can further be adapted and extended. This book is divided into three parts - programming with Python, data analysis and visualization, and statistics …”
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GSEApy: a comprehensive package for performing gene set enrichment analysis in Python von Fang, Zhuoqing, Liu, Xinyuan, Peltz, Gary

“… Abstract Motivation Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes …”
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MetPy: A Meteorological Python Library for Data Analysis and Visualization von May, Ryan M., Goebbert, Kevin H., Thielen, Jonathan E., Leeman, John R., Camron, M. Drew, Bruick, Zachary, Bruning, Eric C., Manser, Russell P., Arms, Sean C., Marsh, Patrick T.

“… MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries …”
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Python for MATLAB Development - Extend MATLAB with 300,000+ Modules from the Python Package Index von Danial, Albert

“… This book shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, optimization, statistics, finance, and simulation …”
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pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods von Behdenna, Abdelkader, Colange, Maximilien, Haziza, Julien, Gema, Aryo, Appé, Guillaume, Azencott, Chloé-Agathe, Nordor, Akpéli

“… Results In this technical note, we present a new Python implementation of ComBat and ComBat-Seq …”
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scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data von Faure, Louis, Soldatov, Ruslan, Kharchenko, Peter V, Adameyko, Igor

“… 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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stk: A python toolkit for supramolecular assembly von Turcani, Lukas, Berardo, Enrico, Jelfs, Kim E.

“… 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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Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements von Xu, Xiaoyan, Cogo, Filipe R., McIntosh, Shane

“… proposed LogCoCo - a tool that implements log-based code coverage for Java . While LogCoCo breaks important new ground, it has fundamental limitations, namely …”
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PHOTONAI—A Python API for rapid machine learning model development von 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

“… PHOTONAI is a high-level Python API designed to simplify and accelerate machine learning model development …”
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GPAW: An open Python package for electronic structure calculations von Mortensen, Jens Jørgen, Larsen, Ask Hjorth, Kuisma, Mikael, Ivanov, Aleksei V, Taghizadeh, Alireza, Peterson, Andrew, Haldar, Anubhab, Dohn, Asmus Ougaard, Schäfer, Christian, Jónsson, Elvar Örn, Hermes, Eric D, Nilsson, Fredrik Andreas, Kastlunger, Georg, Levi, Gianluca, Jónsson, Hannes, Häkkinen, Hannu, Fojt, Jakub, Kangsabanik, Jiban, Sødequist, Joachim, Lehtomäki, Jouko, Heske, Julian, Enkovaara, Jussi, Winther, Kirsten Trøstrup, Dulak, Marcin, Melander, Marko M, Ovesen, Martin, Louhivuori, Martti, Walter, Michael, Gjerding, Morten, Lopez-Acevedo, Olga, Erhart, Paul, Warmbier, Robert, Würdemann, Rolf, Kaappa, Sami, Latini, Simone, Boland, Tara Maria, Bligaard, Thomas, Skovhus, Thorbjørn, Susi, Toma, Maxson, Tristan, Rossi, Tuomas, Chen, Xi, Schmerwitz, Yorick Leonard A, Schiøtz, Jakob, Olsen, Thomas, Jacobsen, Karsten Wedel, Thygesen, Kristian Sommer

“… This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies …”
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SciPy 1.0: fundamental algorithms for scientific computing in Python von Virtanen, Pauli, Gommers, Ralf, Oliphant, Travis E., Haberland, Matt, Reddy, Tyler, Cournapeau, David, Burovski, Evgeni, Peterson, Pearu, Weckesser, Warren, Bright, Jonathan, van der Walt, Stéfan J., Brett, Matthew, Wilson, Joshua, Millman, K. Jarrod, Mayorov, Nikolay, Nelson, Andrew R. J., Jones, Eric, Kern, Robert, Larson, Eric, Carey, C J, Polat, İlhan, Feng, Yu, Moore, Eric W., VanderPlas, Jake, Laxalde, Denis, Perktold, Josef, Cimrman, Robert, Henriksen, Ian, Quintero, E. A., Harris, Charles R., Archibald, Anne M., Ribeiro, Antônio H., Pedregosa, Fabian, van Mulbregt, Paul

“… Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages …”
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Biotite: a unifying open source computational biology framework in Python von Kunzmann, Patrick, Hamacher, Kay

“… Results We have developed the Python package Biotite : a general computational biology framework, that represents sequence and structure …”
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PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces von Singh, Gursimran, Chharia, Aviral, Upadhyay, Rahul, Kumar, Vinay, Longo, Luca

“… PyNoetic is one of the very few frameworks in Python that encompasses the entire BCI design pipeline, from stimulus presentation and data …”
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