Suchergebnisse - (( (statee OR state:new) python code analysis ) OR ( stat 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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Identification of Novel Microcystins Using High-Resolution MS and MSn with Python Code von Baliu-Rodriguez, David, Peraino, Nicholas J, Premathilaka, Sanduni H, Birbeck, Johnna A, Baliu-Rodriguez, Tomás, Westrick, Judy A, Isailovic, Dragan

“… ) coupled with high-resolution (HR) Orbitrap mass spectrometry (MS) and a new bottom-up sequencing strategy …”
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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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Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics von Goloborodko, Anton A., Levitsky, Lev I., Ivanov, Mark V., Gorshkov, Mikhail V.

“… Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics …”
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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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Statistics Using Python von Campesato, Oswald

“… 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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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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Coherent manipulation of the internal state of ultracold 87Rb133Cs molecules with multiple microwave fields von Blackmore, Jacob A, Gregory, Philip D, Bromley, Sarah L, Cornish, Simon L

“… We explore coherent multi-photon processes in 87Rb133Cs molecules using 3-level lambda and ladder configurations of rotational and hyperfine states, and discuss their relevance to future applications …”
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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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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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Short communication: age2exhume – a MATLAB/Python script to calculate steady-state vertical exhumation rates from thermochronometric ages and application to the Himalaya von van der Beek, Peter, Schildgen, Taylor F.

“… datasets in such models remains challenging. Here, we present age2exhume, a thermal model in the form of a MATLAB or Python script, which can be used to rapidly obtain …”
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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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