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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 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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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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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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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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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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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.

“…We present false discovery rate (FDR) smoothing, an empirical-Bayes method for exploiting spatial structure in large multiple-testing problems. FDR smoothing…”
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Trimmed Constrained Mixed Effects Models: Formulations and Algorithms by Zheng, Peng, Barber, Ryan, Sorensen, Reed J. D., Murray, Christopher J. L., Aravkin, Aleksandr Y.

“…Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis…”
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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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Estimating Local Prevalence of Obesity Via Survey Under Cost Constraints: Stratifying ZCTAs in Virginia's Thomas Jefferson Health District by Lobo, Benjamin J., Bonds, Denise E., Kafadar, Karen

“… (here, ZIP Code Tabulation Areas, or ZCTAs) prior to conducting the survey for those situations where cost considerations make it infeasible to sample each geographic unit (here, ZCTA) in the region (here, TJHD…”
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Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care by Duarte, Martha, Salamanca, Mayra, Gonzalez, Juan M, Roman Laporte, Roberto, Gattamorta, Karina, Lopez Martinez, Fernando Enrique, Clochesy, John, Rincon Acuna, Juan Carlos

“…Depression is recognized as a significant public health issue in the United States. The National Survey on Drug Use and Health reports that 21.0 million adults…”
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A Review of Adversarial Attack and Defense for Classification Methods by Li, Yao, Cheng, Minhao, Hsieh, Cho-Jui, Lee, Thomas C. M.

“…Despite the efficiency and scalability of machine learning systems, recent studies have demonstrated that many classification methods, especially Deep Neural…”
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Manifold lifting: scaling Markov chain Monte Carlo to the vanishing noise regime by Au, Khai Xiang, Graham, Matthew M, Thiery, Alexandre H

“…Standard Markov chain Monte Carlo methods struggle to explore distributions that concentrate in the neighbourhood of low-dimensional submanifolds. This…”
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Domain-specific decision modelling and statistical analysis for combat system effectiveness simulation by Li, Xiaobo, Lei, Yonglin, Vangheluwe, Hans, Wang, Weiping, Li, Qun

“… decision models to Python code which is supported by a Python script framework to implement decision models and we present a Bayesian network-based statistical analysis method on simulation output data…”
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Much Ado About Survey Tables: A Comparison of Chi-Square Tests and Software to Analyze Categorical Survey Data by Hu, Li-Yen R., He, Yulei, Irimata, Katherine E., Beresovsky, Vladislav

“… This article aims to fill such a gap. Many modern statistical software packages for survey analysis are capable of computing either the Wald Chi-square test or the Rao…”
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Robust distributed precision matrix estimation for high-dimensional data by Ye, Yangqing, Yu, Yang, Ma, Xiaoyan, Liang, Wanfeng

“… Simulation studies and real data analysis demonstrate the superiority of the proposed method. The complete Python code supporting this study can be downloaded from https://github.com/littletesla/RDPM …”
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Graph analysis and visualization: discovering business opportunity in linked data by Brath, Richard, Jonker, David

“… The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book…”
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NODESTUDIO, A VISUAL PROGRAMMING FRAMEWORK FOR MUSCULOSKELETAL MRI ANALYSIS by Mendoza, M.A., Huo, Z., Diao, Y., Jin, Y., Huang, J., Bangerter, N.K.

“… to either implement or integrate software repositories in a clinical researcher's analysis pipeline…”
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Spatial Analysis Using Big Data by Hajime Seya, Yoshiki Yamagata

“…Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems…”
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