Suchergebnisse - (( (statny OR state) python code analysis ) OR ( (statent OR statnet) python code analysis ))

Smart Compiler Assistant: An AST based Python Code Analysis

Autoren: Aneesh, Ch Saumik, Gembali Varun, Kvv et al.

Quelle: 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) ; page 1-6

Verfügbarkeit: https://doi.org/10.1109/icccnt61001.2024.10724220
http://xplorestaging.ieee.org/ielx8/10723818/10723316/10724220.pdf?arnumber=10724220

Programming models to support data science workflows

Autoren: Ramón-Cortés Vilarrodona, Cristián

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Badia Sala, Rosa M. (Rosa Maria), Ejarque Artigas, Jorge

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Distributed computing, High-performance computing, Data science pipelines, Task-ba workflows, Dataflows, Containers (Computer sicience), COMPSs, PyCOMPSs, AutoParallel, Docker, Àrees temàtiques de la UPC::Informàtica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/669728
https://dx.doi.org/10.5821/dissertation-2117-330142

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

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

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

Schlagwörter: *Experimental design, *Quantitative research, Language models, Python programming language, Generative pre-trained transformers, Benchmark problems (Computer science), Code generators

ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.

Autoren: Ruta, Michael R Gaidici, Tony Irwin, Chase et al.

Quelle: Journal of Medical Internet Research. 2025, Vol. 27, p1-9. 9p.

Schlagwörter: *Data analysis, *Data management, ChatGPT, Inferential statistics, Medical care research, Statistical software, Univariate analysis, Descriptive statistics

Firma/Körperschaft: OpenAI Inc.

CLAVE: A deep learning model for source code authorship verification with contrastive learning and transformer encoders.

Autoren: Álvarez-Fidalgo, David Ortin, Francisco

Quelle: Information Processing & Management. May2025, Vol. 62 Issue 3, pN.PAG-N.PAG. 1p.

Schlagwörter: *Transformer models, Language models, Source code, Dispute resolution, Python programming language

Processing Government Data: ZIP Codes, Python, and OpenRefine.

Autoren: Donnelly, Frank¹ francis.donnelly@baruch.cuny.edu

Quelle: Code4Lib Journal. 7/21/2014, Issue 25, p10-10. 1p. 2 Color Photographs.

Schlagwörter: *Data analysis, *Librarians, Zip codes, Python programming language, Electronic spreadsheets

Percolation Theory Using Python

Autoren: Malthe-Sørenssen, Anders

Schlagwörter: fractal models, critical phenomena in statistical physics, disordered systems, scaling theory, anomalous diffusion, random media textbook, Statistical physics, Condensed matter physics (liquid state and solid state physics), Cybernetics and systems theory, Engineering applications of electronic, magnetic, optical materials, Mathematical physics, Geophysics

Dateibeschreibung: application/pdf

Relation: Lecture Notes in Physics

Zugangs-URL: https://library.oapen.org/handle/20.500.12657/92326

All of whom? Limitations encountered using All of Us Researcher Workbench in a Primary Care residents secondary data analysis research training block.

Autoren: LaPolla, Fred Willie Zametkin Grossi, Marco Barber Chen, Sharon et al.

Quelle: Journal of the American Medical Informatics Association. Dec2024, Vol. 31 Issue 12, p3008-3012. 5p.

Schlagwörter: Secondary analysis, Graduate medical education, Research personnel, Residents (Medicine), Research questions

User guide for Social Determinants of Health Survey data in the All of Us Research Program.

Autoren: Koleck, Theresa A Dreisbach, Caitlin Zhang, Chen et al.

Quelle: Journal of the American Medical Informatics Association. Dec2024, Vol. 31 Issue 12, p3032-3041. 10p.

Schlagwörter: Social determinants of health, Health equity, Research personnel, Sociometry, Source code

State of the interactomes: an evaluation of molecular networks for generating biological insights.

Autoren: Wright, Sarah N Colton, Scott Schaffer, Leah V et al.

Quelle: Molecular Systems Biology. Jan2025, Vol. 21 Issue 1, p1-29. 29p.

Schlagwörter: *SYSTEMS biology, *LIFE sciences, *REGULATOR genes, *BIOLOGICAL systems, *BIOLOGICAL networks

Exploring Methods for Quantifying Expressibility and Entangling Capability of Parameterized Quantum Circuits

Autoren: Mjaaseth, Jørgen

Verfügbarkeit: https://hdl.handle.net/11250/3145867

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

Autoren: Li, Jingmao Xu, Yaqing Ma, Shuangge et al.

Quelle: Bioinformatics. Sep2025, Vol. 41 Issue 9, p1-9. 9p.

Schlagwörter: *CANCER research, *GENOTYPE-environment interaction, *DIAGNOSTIC imaging, *DEEP learning, *EMPIRICAL research, *COMPUTER simulation

HABiC: an algorithm based on the exact computation of the Kantorovich-Rubinstein optimizer for binary classification in transcriptomics.

Autoren: Cordier, Chiara Jézéquel, Pascal Campone, Mario et al.

Quelle: Bioinformatics. Jun2025, Vol. 41 Issue 6, p1-13. 13p.

Schlagwörter: *PREDICTION algorithms, *TRANSCRIPTOMES, *DEGREES of freedom, *INDIVIDUALIZED medicine, *MACHINE learning

An algorithm for automated extraction of resonance parameters from the stabilization method.

Autoren: Langner, Johanna Sadhukhan, Anjan Saha, Jayanta K. et al.

Quelle: Computer Physics Communications. Nov2025, Vol. 316, pN.PAG-N.PAG. 1p.

Schlagwörter: *RESONANCE, *DENSITY of states, *STATISTICAL accuracy, *EIGENANALYSIS, *PYTHON programming language, *ALGORITHMS, *DATA extraction

Enhancing genome-scale metabolic models with kinetic data: resolving growth and citramalate production trade-offs in Escherichia coli.

Autoren: Lázaro, Jorge Wongprommoon, Arin Júlvez, Jorge et al.

Quelle: Bioinformatics Advances. 2025, Vol. 5 Issue 1, p1-11. 11p.

Schlagwörter: *ESCHERICHIA coli, *METABOLIC models, *CHEMICAL kinetics, *METABOLIC flux analysis, *MATHEMATICAL programming

Multiple scales analysis of slow–fast quasi-linear systems

Autoren: Michel, G. Chini, G. P.

Quelle: Proceedings: Mathematical, Physical and Engineering Sciences, 2019 Mar 01. 475(2223), 1-17.

Zugangs-URL: https://www.jstor.org/stable/26645709

A parametric analysis of CLT wall and outrigger structural system in tall timber buildings

Autoren: Blom, Herman Mørkved Hellem, Sverre Grøttebø Stamatopoulos, Haris et al.

Weitere Verfasser: Blom, Herman Mørkved Hellem, Sverre Grøttebø Stamatopoulos, Haris et al.

Verfügbarkeit: https://hdl.handle.net/11250/3024629

Quantifying the nuclear localization of fluorescently tagged proteins.

Autoren: Hurbain, Julien Wolde, Pieter Rein ten Swain, Peter S

Quelle: Bioinformatics Advances. 2025, Vol. 5 Issue 1, p1-8. 8p.

Schlagwörter: *CONVOLUTIONAL neural networks, *MACHINE learning, *CELLULAR signal transduction, *IMAGE processing, *FLUORESCENT proteins, *CELL analysis

MEG and EEG data analysis with MNE-Python

Autoren: Gramfort, Alexandre Luessi, Martin Hamalainen, Matti et al.

Quelle: Gramfort, A., M. Luessi, E. Larson, D. A. Engemann, D. Strohmeier, C. Brodbeck, R. Goj, et al. 2013. “MEG and EEG data analysis with MNE-Python.” Frontiers in Neuroscience 7 (1): 267. doi:10.3389/fnins.2013.00267. http://dx.doi.org/10.3389/fnins.2013.00267.

Schlagwörter: Methods Article, electroencephalography (EEG), magnetoencephalography (MEG), neuroimaging, software, python, open-source

Dateibeschreibung: application/pdf

Relation: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872725/pdf/; Frontiers in Neuroscience

Zugangs-URL: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11879699

Transforming Digital Phenotyping Raw Data Into Actionable Biomarkers, Quality Metrics, and Data Visualizations Using Cortex Software Package: Tutorial.

Autoren: Burns, James Chen, Kelly Flathers, Matthew et al.

Quelle: Journal of Medical Internet Research. 2024, Vol. 26, p1-27. 27p.

Schlagwörter: *Electronic data processing, *Data visualization, *Data quality, Cell phones, Integrated software