Suchergebnisse - (( state:mi 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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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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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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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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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

“… We provide explanations and code in two scripting languages (R and Python) as well …”
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SNPAAMapper-Python: A highly efficient genome-wide SNP variant analysis pipeline for Next-Generation Sequencing data von Li, Chang, Ma, Kevin, Xu, Nicole, Fu, Chenjian, He, Andrew, Liu, Xiaoming, Bai, Yongsheng

“… 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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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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Nestedness for Dummies (NeD): A user friendly web interface for exploratory nestedness analysis von 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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Statistical Analyses and Reproducible Research von 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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A NICER View of the Massive Pulsar PSR J0740+6620 Informed by Radio Timing and XMM-Newton Spectroscopy von Riley, Thomas E., Watts, Anna L., Ray, Paul S., Bogdanov, Slavko, Guillot, Sebastien, Morsink, Sharon M., Bilous, Anna V., Arzoumanian, Zaven, Choudhury, Devarshi, Deneva, Julia S., Gendreau, Keith C., Harding, Alice K., Ho, Wynn C. G., Lattimer, James M., Loewenstein, Michael, Ludlam, Renee M., Markwardt, Craig B., Okajima, Takashi, Prescod-Weinstein, Chanda, Remillard, Ronald A., Wolff, Michael T., Fonseca, Emmanuel, Cromartie, H. Thankful, Kerr, Matthew, Pennucci, Timothy T., Parthasarathy, Aditya, Ransom, Scott, Stairs, Ingrid, Guillemot, Lucas, Cognard, Ismael

“… We report on Bayesian estimation of the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, conditional on pulse-profile …”
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Potku – New analysis software for heavy ion elastic recoil detection analysis von Arstila, K., Julin, J., Laitinen, M.I., Aalto, J., Konu, T., Kärkkäinen, S., Rahkonen, S., Raunio, M., Itkonen, J., Santanen, J.-P., Tuovinen, T., Sajavaara, T.

“… The software combines a Python-language graphical front-end with a C code computing back-end in a user-friendly way …”
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Facilitating the Calculation of the Efficient Score Using Symbolic Computing von 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 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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PyIOmica: longitudinal omics analysis and trend identification von Domanskyi, Sergii, Piermarocchi, Carlo, Mias, George I

“… Abstract Summary PyIOmica is an open-source Python package focusing on integrating longitudinal multiple omics datasets, characterizing and categorizing temporal trends …”
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Enhanced deep learning model for precise nodule localization and recurrence risk prediction following curative-intent surgery for lung cancer von Park, Jihwan, Rho, Mi Jung, Moon, Mi Hyoung

“… Radical surgery is the primary treatment for early-stage resectable lung cancer, yet recurrence after curative surgery is not uncommon. Identifying patients at …”
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Nature and Diffusion of Gynecologic Cancer–Related Misinformation on Social Media: Analysis of Tweets von Chen, Liang, Wang, Xiaohui, Peng, Tai-Quan

“… Over the last two decades, the incidence and mortality rates of gynecologic cancers have increased at a constant rate in China. Gynecologic cancers have become …”
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Quantitative analysis of mitochondrial ATP synthesis von Randall, E. Benjamin, Hock, Marcus, Lopez, Rachel, Marzban, Bahador, Marshall, Collin, Beard, Daniel A.

“… Computer codes for these analyses are embedded as Python scripts in a Jupyter Book to facilitate …”
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BannMI deciphers potential n-to-1 information transduction in signaling pathways to unravel message of intrinsic apoptosis von Schmidt, Bettina, Sers, Christine, Klein, Nadja

“… ). Information integration takes place on the protein level via n-to-1 interactions. A state-of-the-art procedure to quantify information flow (edges …”
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Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models von 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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