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

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

“… Here we describe a suite of open-source Python-based postprocessing routines we have developed called PyLAT …”
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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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VULCAN: An Open-source, Validated Chemical Kinetics Python Code for Exoplanetary Atmospheres von Tsai, Shang-Min, Lyons, James R., Grosheintz, Luc, Rimmer, Paul B., Kitzmann, Daniel, Heng, Kevin

“… We present an open-source and validated chemical kinetics code for studying hot exoplanetary atmospheres, which we name VULCAN …”
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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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PypKa: A Flexible Python Module for Poisson-Boltzmann-Based pKa Calculations von Reis, Pedro B P S, Vila-Viçosa, Diogo, Rocchia, Walter, Machuqueiro, Miguel

“… The protonation of titratable residues has a significant impact on the structure and function of biomolecules, influencing many physicochemical and ADME …”
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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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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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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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