Suchergebnisse - (( (stateeni OR stat) python code analysis ) OR ( (statepoint OR stateed) python code analysis ))*

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'

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

Schlagwörter: microplastics microscopy image analysis python altair, scipo, stat

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

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

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

Autoren: Li J Xu Y Ma S et al.

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

Publikationsart: Journal Article

Info zur Zeitschrift: 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-Schlagworte: 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

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

Index Begriffe: 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

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

Autoren: Fortune, Nathanael Alexander

Quelle: Physics: Faculty Publications

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

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

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

pyjeo: A Python Package for the Analysis of Geospatial Data

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

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

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

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

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

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

Autoren: James V Stone

Resource Type: eBook.

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

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

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

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

Quelle: 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⟩.

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

Relation: info:eu-repo/grantAgreement//847441/EU/Euratom research and training programme 2014 – 2018/Euratom

Verfügbarkeit: 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

Applied Time Series Analysis and Forecasting with Python

Autoren: Changquan Huang Alla Petukhina

Resource Type: eBook.

Schlagworte: 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

Autoren: Tarek A. Atwan

Resource Type: eBook.

Schlagworte: Machine learning, Python (Computer program language)

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

Python How-To : 63 Techniques to Improve Your Python Code

Autoren: Yong Cui

Resource Type: eBook.

Schlagworte: Python (Computer program language), Computer programming, Video games--Programming

Categories: COMPUTERS / Languages / Python, COMPUTERS / Data Science / General, COMPUTERS / Internet / Web Programming

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

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

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

Quelle: 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⟩

Schlagwörter: 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]

Geographisches Schlagwort: Bruxelles (BEL), Belgium

Verfügbarkeit: 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

Extended sample size calculations for evaluation of prediction models using a threshold for classification.

Autoren: Whittle R Ensor J Archer L et al.

Quelle: BMC medical research methodology [BMC Med Res Methodol] 2025 Jul 01; Vol. 25 (1), pp. 170. Date of Electronic Publication: 2025 Jul 01.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE

MeSH-Schlagworte: Models, Statistical*, Risk Assessment/methods ; Sample Size ; Humans ; Predictive Value of Tests ; Sensitivity and Specificity ; Algorithms

Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care.

Autoren: Duarte, Martha Salamanca, Mayra Gonzalez, Juan M. et al.

Quelle: Clinical Nursing Research. Jun2024, Vol. 33 Issue 5, p355-369. 15p.

Schlagwörter: *MENTAL depression risk factors, *RISK assessment, *PREDICTION models, *SOCIAL determinants of health, *RECEIVER operating characteristic curves, *QUESTIONNAIRES, *PRIMARY health care, *RETROSPECTIVE studies, *QUANTITATIVE research, *DESCRIPTIVE statistics, *NURSING interventions, *SURVEYS, *HEALTH behavior, *MEDICAL records, *ACQUISITION of data, *SOCIODEMOGRAPHIC factors, *MACHINE learning, *DATA analysis software, *ACCURACY, *COMPARATIVE studies, *SOCIAL classes, *SENSITIVITY & specificity (Statistics), *SOCIAL isolation, *ALGORITHMS, *REGRESSION analysis, *MENTAL depression, *EVALUATION

Geografische Kategorien: FLORIDA

Software Design for Python Programmers : Principles and Patterns

Autoren: Ronald Mak

Resource Type: eBook.

Categories: COMPUTERS / Languages / Python, COMPUTERS / Programming / Object Oriented, COMPUTERS / Software Development & Engineering / Systems Analysis & Design

Data and code for project 'What makes users click: The effect of news values negativity and surprise in news headlines on selection likelihood'

Autoren: Femke Kok Emily Kruidhof

Schlagwörter: stat, info

Relation: https://zenodo.org/record/5940294

Verfügbarkeit: https://zenodo.org/record/5940294

Statistics Every Programmer Needs

Autoren: Gary Sutton

Resource Type: eBook.

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

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

Autoren: Yao Y Zhang D Fan H et al.

Quelle: Probiotics and antimicrobial proteins [Probiotics Antimicrob Proteins] 2025 May 21. Date of Electronic Publication: 2025 May 21.

Publikationsart: Journal Article

Info zur Zeitschrift: 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

A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data.

Autoren: Pripp AH Łosińska K Korkosz M et al.

Quelle: Rheumatology international [Rheumatol Int] 2024 Jul; Vol. 44 (7), pp. 1265-1274. Date of Electronic Publication: 2024 Apr 24.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Springer International Country of Publication: Germany NLM ID: 8206885 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1437-160X (Electronic) Linking ISSN: 01728172 NLM ISO Abbreviation: Rheumatol Int Subsets: MEDLINE

MeSH-Schlagworte: Rheumatic Diseases*/therapy, Observational Studies as Topic/methods ; Humans ; Treatment Outcome ; Propensity Score ; Regression Analysis ; Data Interpretation, Statistical

Phenotype structuring in collective cell migration: a tutorial of mathematical models and methods.

Autoren: Lorenzi T Painter KJ Villa C

Quelle: Journal of mathematical biology [J Math Biol] 2025 May 16; Vol. 90 (6), pp. 61. Date of Electronic Publication: 2025 May 16.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Springer Verlag Country of Publication: Germany NLM ID: 7502105 Publication Model: Electronic Cited Medium: Internet ISSN: 1432-1416 (Electronic) Linking ISSN: 03036812 NLM ISO Abbreviation: J Math Biol Subsets: MEDLINE

MeSH-Schlagworte: Cell Movement*/physiology , Models, Biological*, Neoplasms/pathology ; Phenotype ; Humans ; Mathematical Concepts ; Computer Simulation ; Animals

Data from: A strong test of the Maximum Entropy Theory of Ecology

Autoren: Xiao, Xiao Aravajy, S. Baribault, Thomas W. et al.

Quelle: 10.5061/dryad.5fn46 ; oai:services.nod.dans.knaw.nl:Products/dans:oai:easy.dans.knaw.nl:easy-dataset:86630 ; oai:easy.dans.knaw.nl:easy-dataset:86630 ; oai:figshare.com:article/4152633 ; 10.5061/dryad.5fn46/1 ; 10|openaire____::9e3be59865b2c1c335d32dae2fe7b254 ; 10|re3data_____::94816e6421eeb072e7742ce6a9decc5f ; 10|eurocrisdris::fe4903425d9040f680d8610d9079ea14 ; 10|re3data_____::84e123776089ce3c7a33db98d9cd15a8 ; 10|re3data_____::7980778c78fb4cf0fab13ce2159030dc ; 10|openaire____::081b82f96300b6a6e3d282bad31cb6e2 ; re3data_____::r3d100000044 ; 10|opendoar____::8b6dd7db9af49e67306feb59a8bdc52c

Schlagwörter: species abundance distribution, size distributions, trees, Life sciences, medicine and health care, Genetics, Evolutionary Biology, Ecology, Inorganic Chemistry, Science Policy, 69999 Biological Sciences not elsewhere classified, 19999 Mathematical Sciences not elsewhere classified, 29999 Physical Sciences not elsewhere classified, subset, data product, Python code, al, Xiao, Maximum Entropy Theory, analyses, dataset, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, Physical Sciences not elsewhere classified, envir, stat

Relation: http://dx.doi.org/10.5061/dryad.5fn46; https://dx.doi.org/10.5061/dryad.5fn46; https://figshare.com/articles/Data_from_A_strong_test_of_the_Maximum_Entropy_Theory_of_Ecology/4152633; http://dx.doi.org/10.5061/dryad.5fn46/1; https://dx.doi.org/10.5061/dryad.5fn46/1

Verfügbarkeit: https://doi.org/10.5061/dryad.5fn46
https://figshare.com/articles/Data_from_A_strong_test_of_the_Maximum_Entropy_Theory_of_Ecology/4152633
https://doi.org/10.5061/dryad.5fn46/1