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Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial: Introduction to computational causal inference using reproducible Stata, R, and Python code: a tutorial

Authors: Matthew J. Smith Mohammad A. Mansournia Camille Maringe et al.

Contributors: Matthew J. Smith Mohammad A. Mansournia Camille Maringe et al.

Source: Stat Med
RISalud-ANDALUCIA. Repositorio Institucional de Salud de Andalucía
instname

Subject Terms: regression adjustment, 01 natural sciences, Article, Applications of statistics to biology and medical sciences, meta analysis, Modelos estadísticos, double-robust methods, Humans, Computer Simulation, causal inference, 0101 mathematics, Propensity Score, propensity score, Probability, Simulación por computador, Proyectos de investigación, Models, Statistical, g-formula, Causalidad, Humanos, 3. Good health, Causality, machine learning, Puntaje de propensión, G-methods, Research Design, targeted maximum likelihood estimation, Probabilidad, inverse probability weighting

File Description: application/pdf; application/xml

Access URL: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sim.9234
https://pubmed.ncbi.nlm.nih.gov/34713468
http://hdl.handle.net/10668/22539
https://hdl.handle.net/10668/24648
https://researchonline.lshtm.ac.uk/id/eprint/4664004/1/sim.9234.pdf

ImmobileParticles_MatchAndAnalyse: python code used for analysis of image data in Lenz et al. 2021, 'Measuring impacts of microplastic treatments via image recognition on immobilised particles below 100 µm'

Authors: Lenz, Robin Enders, Kristina Fischer, Franziska et al.

Subject Terms: microplastics microscopy image analysis python altair, scipo, stat

Relation: https://zenodo.org/record/4592320

Availability: https://zenodo.org/record/4592320

GE-IA-NAM: gene-environment interaction analysis via imaging-assisted neural additive model.

Authors: Li J Xu Y Ma S et al.

Source: Bioinformatics (Oxford, England) [Bioinformatics] 2025 Sep 01; Vol. 41 (9).

Publication Type: Journal Article

Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE

MeSH Terms: Lung Neoplasms*/genetics , Skin Neoplasms*/genetics , Melanoma*/genetics , Gene-Environment Interaction* , Deep Learning*, Datasets as Topic ; Humans ; Age Factors ; Sex Factors ; Smoking

Primary data for BJC Carbonic anhydrase IX is a pH-stat that sets an acidic tumour extracellular pH in vivo

Authors: Griffiths, JR Lee, Shen-Han McIntyre, Dominick John et al.

Index Terms: Carbonic anhydrase IX, Extracellular pH, Intracellular pH, ISUCA, Magnetic Resonance Spectroscopy, MRS, pH-stat, Tumour pH, Dataset

URL: https://www.repository.cam.ac.uk/handle/1810/361916
https://doi.org/10.17863/CAM.26029
https://doi.org/10.1038/s41416-018-0216-5
https://www.repository.cam.ac.uk/handle/1810/287141
https://doi.org/10.1038/s41416-018-0216-5
https://www.repository.cam.ac.uk/handle/1810/287141

Text Analysis with Python: A Research Oriented Guide

Authors: Mamta, Mittal Gopi, Battineni Bhimavarapu, Usharani et al.

Resource Type: eBook.

Subjects: Programming languages (Electronic computers), Python (Computer program language), Text processing (Computer science)

Categories: COMPUTERS / Languages / Python, COMPUTERS / Artificial Intelligence / General

A Short Guide to Using Python For Data Analysis In Experimental Physics

Authors: Fortune, Nathanael Alexander

Source: Physics: Faculty Publications

Subject Terms: DATA ANALYSIS, NUMPY, PHYSICS, PYTHON, SCIPY, Computer Sciences, stat, edu

Relation: https://scholarworks.smith.edu/phy_facpubs/30

Availability: https://scholarworks.smith.edu/phy_facpubs/30

Luminescence Signal Analysis Using Python

Authors: Vasilis Pagonis

Resource Type: eBook.

Subjects: Radiation dosimetry, Mathematical physics, Python (Computer program language), Quantum physics, Optical spectroscopy

Categories: SCIENCE / Life Sciences / Biophysics, COMPUTERS / Languages / Python, SCIENCE / Physics / Mathematical & Computational, SCIENCE / Physics / Quantum Theory, SCIENCE / Spectroscopy & Spectrum Analysis, TECHNOLOGY & ENGINEERING / Materials Science / General

Incorporating Computer Programming & Data Science into a Guided Inquiry-Based Undergraduate Ecology Lab.

Authors: RAHN, JENNIFER WILLNER, DANA DEVERICK, JAMES et al.

Source: American Biology Teacher (University of California Press); Nov/Dec2019, Vol. 81 Issue 9, p649-657, 9p

Subject Terms: COMPUTER programming, PROGRAMMING languages, LIFE sciences, PYTHON programming language, COMPUTER science, BIODIVERSITY

Company/Entity: COLLEGE of William & Mary

pyjeo: A Python Package for the Analysis of Geospatial Data

Authors: Pieter Kempeneers Ondrej Pesek Davide De Marchi et al.

Source: ISPRS International Journal of Geo-Information, Vol 8, Iss 10, p 461 (2019)

Subject Terms: open-source software, geospatial data, image processing, stat, geo

Relation: https://doaj.org/article/352223c398b04d87ade0a49b91244b53

Availability: https://doi.org/10.3390/ijgi8100461
https://doaj.org/article/352223c398b04d87ade0a49b91244b53

Linear Regression With Python : A Tutorial Introduction to the Mathematics of Regression Analysis

Authors: James V Stone

Resource Type: eBook.

Categories: MATHEMATICS / Probability & Statistics / Regression Analysis, COMPUTERS / Languages / Python, MATHEMATICS / Probability & Statistics / General

Applied Time Series Analysis and Forecasting with Python

Authors: Changquan Huang Alla Petukhina

Resource Type: eBook.

Subjects: Python (Computer program language), Time-series analysis, Time-series analysis--Forecasting, Time-series analysis--Computer programs

Categories: MATHEMATICS / Probability & Statistics / General, BUSINESS & ECONOMICS / Econometrics, BUSINESS & ECONOMICS / Statistics, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Languages / Python, COMPUTERS / Mathematical & Statistical Software

Time Series Analysis with Python Cookbook : Practical Recipes for Exploratory Data Analysis, Data Preparation, Forecasting, and Model Evaluation

Authors: Tarek A. Atwan

Resource Type: eBook.

Subjects: Machine learning, Python (Computer program language)

Categories: COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / Data Warehousing, COMPUTERS / Languages / Python

Prediction of Chemically Modified Antimicrobial Peptides and Their Sub-functional Activities Using Hybrid Features.

Authors: Yao Y Zhang D Fan H et al.

Source: Probiotics and antimicrobial proteins [Probiotics Antimicrob Proteins] 2026 Jan; Vol. 18 (1), pp. 921-935. Date of Electronic Publication: 2025 May 21.

Publication Type: Journal Article

Journal Info: Publisher: Springer Country of Publication: United States NLM ID: 101484100 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1867-1314 (Electronic) Linking ISSN: 18671306 NLM ISO Abbreviation: Probiotics Antimicrob Proteins Subsets: MEDLINE

MeSH Terms: Antimicrobial Peptides*/chemistry , Antimicrobial Peptides*/pharmacology , Computational Biology*/methods, Humans

Uncertainty quantification for severe-accident reactor modelling: Results and conclusions of the MUSA reactor applications work package

Authors: Brumm, S. Gabrielli, F. Sanchez Espinoza, V. et al.

Contributors: Brumm, S. Gabrielli, F. Sanchez Espinoza, V. et al.

Source: ISSN: 0306-4549 ; Annals of Nuclear Energy ; https://hal.science/hal-04777159 ; Annals of Nuclear Energy, 2025, 211, pp.110962. ⟨10.1016/j.anucene.2024.110962⟩.

Subject Terms: Uncertainty quantification, MUSA, Source Term, Modelling, Severe accident, Nuclear reactor, [PHYS]Physics [physics], [SPI]Engineering Sciences [physics], [STAT]Statistics [stat]

Relation: info:eu-repo/grantAgreement//847441/EU/MANAGEMENT AND UNCERTAINTIES OF SEVERE ACCIDENTS/MUSA

Availability: https://hal.science/hal-04777159
https://hal.science/hal-04777159v1/document
https://hal.science/hal-04777159v1/file/Final_version_ANE20225.pdf
https://doi.org/10.1016/j.anucene.2024.110962

NFEmbed: modeling nitrogenase activity via classification and regression with pretrained protein embeddings.

Authors: Nafi, Md Muhaiminul Islam Mohaimin, Abdullah Al

Source: Bioinformatics Advances; 2025, Vol. 5 Issue 1, p1-17, 17p

Subject Terms: NITROGENASES, MACHINE learning, CROP yields, MICROBIOLOGY, ENSEMBLE learning, GENOMICS, BIOFERTILIZERS

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Authors: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

Source: Future Internet; Sep2025, Vol. 17 Issue 9, p412, 28p

Subject Terms: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

A comparison of machine learning algorithms for survival with missing data ; Une comparaison des algorithmes d'apprentissage pour la survie avec données manquantes

Authors: Dufossé, Paul Benzekry, Sébastien Aix Marseille Université (AMU) et al.

Contributors: Dufossé, Paul Benzekry, Sébastien Aix Marseille Université (AMU) et al.

Source: 54es Journées de Statistique de la SFdS
JDS 2023 - 54e Journées de Statistique de la SFds
https://hal.science/hal-04384220
JDS 2023 - 54e Journées de Statistique de la SFds, SFdS, Jul 2023, Bruxelles (BEL), Belgique. ⟨10.48550/arXiv.2303.13590⟩

Subject Terms: Machine Learning (stat.ML), Machine Learning (cs.LG), Machine learning, neural networks, survival data, simulated data, missing data, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.AP]Statistics [stat]/Applications [stat.AP]

Subject Geographic: Bruxelles (BEL), Belgium

Availability: https://hal.science/hal-04384220
https://hal.science/hal-04384220v1/document
https://hal.science/hal-04384220v1/file/preprint_arxiv.pdf
https://doi.org/10.48550/arXiv.2303.13590

Statistics Every Programmer Needs : Practical Python Implementations and Quantitative Methods

Authors: Gary Sutton

Resource Type: eBook.

Categories: COMPUTERS / Data Science / General, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Languages / Python

Statistics for Data Science and Analytics

Authors: Peter C. Bruce Peter Gedeck Janet Dobbins

Resource Type: eBook.

Subjects: Statistics, Python (Computer program language)

Categories: COMPUTERS / Languages / Python, COMPUTERS / Data Science / Data Analytics, MATHEMATICS / Probability & Statistics / General

CLM App: Interlamellar Distance of Pearlite via CLM Revisited and Automated.

Authors: Zouhar, Martin Mikmeková, Šárka Hovjacký, Jan et al.

Source: Materials (1996-1944); Feb2026, Vol. 19 Issue 3, p635, 17p

Subject Terms: AUTOMATION, IMAGE analysis, QUALITY control, MICROSTRUCTURE