Search Results - (( (stat OR stated) python code analysis ) OR ( state:ne python code analysis ))*

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

“…: 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 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.

“…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 by 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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Percolation theory using Python by 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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Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data by 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

“… We provide explanations and code in two scripting languages (R and Python) as well…”
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The CoLoMoTo Interactive Notebook: Accessible and Reproducible Computational Analyses for Qualitative Biological Networks by Naldi, Aurélien, Hernandez, Céline, Levy, Nicolas, Stoll, Gautier, Monteiro, Pedro T., Chaouiya, Claudine, Helikar, Tomáš, Zinovyev, Andrei, Calzone, Laurence, Cohen-Boulakia, Sarah, Thieffry, Denis, Paulevé, Loïc

“… The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve…”
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Nestedness for Dummies (NeD): A user friendly web interface for exploratory nestedness analysis by Strona, Giovanni, Galli, Paolo, Seveso, Davide, Montano, Simone, Fattorini, Simone

“…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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Statistics Using Python by 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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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

“… This application enables the comparison of triggered alarms with the resultant logical states obtained during the analysis…”
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Statistical Analyses and Reproducible Research by Gentleman, Robert, Temple Lang, Duncan

“…It is important, if not essential, to integrate the computations and code used in data analyses, methodological descriptions, simulations, and so on with the documents that describe and rely…”
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Facilitating the Calculation of the Efficient Score Using Symbolic Computing by B. Sibley, Alexander, Li, Zhiguo, Jiang, Yu, Li, Yi-Ju, Chan, Cliburn, Allen, Andrew, Owzar, Kouros

“… In the analysis of data from high-throughput genomic assays, inference on the basis of the score usually enjoys greater stability, considerably higher computational efficiency, and lends itself…”
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Generation of Scale-Free Assortative Networks via Newman Rewiring for Simulation of Diffusion Phenomena by 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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Development of a New Thermal-Hydraulic Module for FRENETIC, a Code for the Multiphysics Analysis of Liquid Metal-Cooled Reactors by Lombardo, Antonino, Nallo, Giuseppe F., Abrate, Nicolò, Liu, Yapeng, Dulla, Sandra

“… The code performs steady-state and transient neutronic (NE) and TH coupled calculations while maintaining a relatively low computational cost thanks to the adoption of simplified physical models…”
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Avogadro: an advanced semantic chemical editor, visualization, and analysis platform by Hanwell, Marcus D, Curtis, Donald E, Lonie, David C, Vandermeersch, Tim, Zurek, Eva, Hutchison, Geoffrey R

“… Results The work presented here details the Avogadro library, which is a framework providing a code library and application programming interface (API…”
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NuRadioMC: simulating the radio emission of neutrinos from interaction to detector by Glaser, C., García-Fernández, D., Nelles, A., Alvarez-Muñiz, J., Barwick, S. W., Besson, D. Z., Clark, B. A., Connolly, A., Deaconu, C., de Vries, K. D., Hanson, J. C., Hokanson-Fasig, B., Lahmann, R., Latif, U., Kleinfelder, S. A., Persichilli, C., Pan, Y., Pfendner, C., Plaisier, I., Seckel, D., Torres, J., Toscano, S., van Eijndhoven, N., Vieregg, A., Welling, C., Winchen, T., Wissel, S. A.

“… NuRadioMC is designed as a modern, modular Python-based framework, combining flexibility in detector design with user-friendliness…”
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REGALS : a general method to deconvolve X-ray scattering data from evolving mixtures by Meisburger, Steve P., Xu, Da, Ando, Nozomi

“…Mixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis…”
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Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples by Mengesha, Betelhiem N., Grizzle, Andrew C., Demisse, Wondwosen, Klein, Kate L., Elliott, Amy, Tyagi, Pawan

“…Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical…”
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Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models by Graham, Matthew M., Thiery, Alexandre H., Beskos, Alexandros

“…Bayesian inference for nonlinear diffusions, observed at discrete times, is a challenging task that has prompted the development of a number of algorithms,…”
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False Discovery Rate Smoothing by Tansey, Wesley, Koyejo, Oluwasanmi, Poldrack, Russell A., Scott, James G.

“… In simulation studies, FDR smoothing exhibits state-of-the-art performance at modest computational cost…”
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Using GNU Make to Manage the Workflow of Data Analysis Projects by Baker, Peter

“…Data analysis projects invariably involve a series of steps such as reading, cleaning, summarizing and plotting data, statistical analysis and reporting…”
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