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  1. 4661
    “…In addition, we provide a Python library for simplified access to the dataset and an online reconstruction challenge. …”
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    LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction
  2. 4662
    “…COSMAS is provided in two languages, Matlab and Python, and is distributed with a user guide and sample scripts, so that accessibility to researchers is maximized.…”
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    COSMAS: a lightweight toolbox for cardiac optical mapping analysis
  3. 4663
    “…Moreover, we assessed the biological relevance of one LRE discovered by DExTER in P. falciparum using an in vivo reporter assay. The source code (python) of DExTER is available at https://gite.lirmm.fr/menichelli/DExTER.…”
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    Identification of long regulatory elements in the genome of Plasmodium falciparum and other eukaryotes
  4. 4664
    “…AVAILABILITY AND IMPLEMENTATION: Our method is available as a Python package at https://github.com/jmschrei/kiwano and can be installed using the command pip install kiwano. …”
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    Prioritizing transcriptomic and epigenomic experiments using an optimization strategy that leverages imputed data
  5. 4665
    por Kundert, Kale
    Publicado 2021
    “…It is also accompanied by a tool for generating clear visualizations of layout files, and a simple API for parsing layout files in analysis scripts written in python or R. We have used wellmap in our own research to annotate data from a wide variety of experiments, including qPCR and flow cytometry. …”
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    Wellmap: a file format for microplate layouts
  6. 4666
    “…Our method is implemented in Python as an open source, publicly available software tool. …”
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    Overcoming an Annotation Hurdle: Digitizing Pen Annotations from Whole Slide Images
  7. 4667
    “…Moreover, the significant alternative splicing events identified by AS-Quant between two biological contexts were validated by RT-PCR experiment. (3) Availability: AS-Quant is implemented in Python 3.0. Source code and a comprehensive user’s manual are freely available online.…”
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    AS-Quant: Detection and Visualization of Alternative Splicing Events with RNA-seq Data
  8. 4668
    “…We analyzed 2398 anterior segment SD-OCT images from 34 patients using code written in Python. Cell density, size, and eccentricity were measured automatically. …”
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    Development of fully automated anterior chamber cell analysis based on image software
  9. 4669
    “…Unfortunately, these optimal points are intrinsically hard to control since their transition energy cannot be tuned by an external magnetic field; moreover, their resilience towards geometric distortions has not yet been analyzed. Here we employ a python-based computational tool for the systematic theoretical analysis and chemical optimization of CTs. …”
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    Exploiting clock transitions for the chemical design of resilient molecular spin qubits
  10. 4670
    “…Datasets from 2013–2018 were joined using the Python programming language. Aggregation and sub-setting by characteristics of interest was done in R to calculate means and frequencies of reported general physician payments from industry across different specialties, locations, timeframes, and payment types. …”
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    Physicians payment in the United States between 2014 and 2018: An analysis of the CMS Open Payments database
  11. 4671
    por Masri, Aladdin, Al-Jabi, Muhannad
    Publicado 2021
    “…To test and validate the models, two powerful modeling tools were used: MATLAB and Anaconda–Python. The results showed an accuracy of about 97% with a standard deviation of 2.3%. …”
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    Toward fault tolerant modelling for SCADA based electricity distribution networks, machine learning approach
  12. 4672
    “…Based on the annotated landmarks, reference lines were defined using an algorithm coded in Python. The CNN and random forest algorithms exhibited similar accuracy for the distance between the menton and vertical reference line. …”
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    Landmark annotation and mandibular lateral deviation analysis of posteroanterior cephalograms using a convolutional neural network
  13. 4673
    “…Our framework is fully developed in Python language as an open source software licensed under the MIT License, and is freely available at https://github.com/BiodataAnalysisGroup/kmerAnalyzer.…”
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    A Computational Framework for Pattern Detection on Unaligned Sequences: An Application on SARS-CoV-2 Data
  14. 4674
    por Song, Qianqian, Su, Jing, Zhang, Wei
    Publicado 2021
    “…Through benchmarking with other label transfer methods on a total of 30 single cell omics datasets, scGCN consistently demonstrates superior accuracy on leveraging cells from different tissues, platforms, and species, as well as cells profiled at different molecular layers. scGCN is implemented as an integrated workflow as a python software, which is available at https://github.com/QSong-github/scGCN.…”
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    scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics
  15. 4675
    por Bayraktar, Yusuf, Ayan, Enes
    Publicado 2021
    “…Of these, 800 were augmented and annotated as “decay” by two experienced dentists using a labeling tool developed in Python programming language. The 800 radiographs were consisted of 11,521 approximal surfaces of which 1,847 were decayed (lesion prevalence for train data was 16.03%). …”
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    Diagnosis of interproximal caries lesions with deep convolutional neural network in digital bitewing radiographs
  16. 4676
    “…The methylation frequencies of 6 genes (FHIT, p16, MGMT, RASSF1A, APC, DAPK) in lung cancer patients, the basic clinical information, and tumor marker levels of these patients were analyzed. Then, the python package “sklearn” was employed to build a support vector machine (SVM) classifier which performed 10-fold cross-validation to construct diagnostic models that could identify lung cancer risk of suspected cases. …”
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    Construction and Validation of a Lung Cancer Diagnostic Model Based on 6-Gene Methylation Frequency in Blood, Clinical Features, and Serum Tumor Markers
  17. 4677
    “…The G2PDeep server is publicly available at http://g2pdeep.org. The Python-based deep-learning model is available at https://github.com/shuaizengMU/G2PDeep_model.…”
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    G2PDeep: a web-based deep-learning framework for quantitative phenotype prediction and discovery of genomic markers
  18. 4678
    “…AVAILABILITY AND IMPLEMENTATION: Our metaball skinning algorithm is implemented in Blender 2.82 relying on its Python API (Application Programming Interface). To make it accessible to computational biologists and neuroscientists, the implementation has been integrated into NeuroMorphoVis, an open source and domain specific package that is primarily designed for neuronal morphology visualization and meshing. …”
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    Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics
  19. 4679
    “…AVAILABILITY AND IMPLEMENTATION: Our method is realized with Python 3.7 and Pytorch 1.5.0 and method and data are freely available at: https://github.com/juanshu30/Disease-Gene-Prioritization-with-Privileged-Information-and-Heteroscedastic-Dropout.…”
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    Disease gene prediction with privileged information and heteroscedastic dropout
  20. 4680
    “…The ACE API can be used with R, Python, Java, HTTP, and a Web UI. RESULTS: ACE offers an expressive query language for complex temporal search across many clinical data types with multiple output options. …”
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    ACE: the Advanced Cohort Engine for searching longitudinal patient records
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