Gene dataset Kaggle

Context. This dataset comes from a proof-of-concept study published in 1999 by Golub et al. It showed how new cases of cancer could be classified by gene expression monitoring (via DNA microarray) and thereby provided a general approach for identifying new cancer classes and assigning tumors to known classes 2 competitions. 79 datasets. 83 kernels. Human genetics encompasses a variety of overlapping fields including: classical genetics, cytogenetics, molecular genetics, biochemical genetics, genomics, population genetics, developmental genetics, clinical genetics, and genetic counseling Explore and run machine learning code with Kaggle Notebooks | Using data from Gene expression dataset (Golub et al.

Gene expression dataset (Golub et al.) Molecular Classification of Cancer by Gene Expression Monitoring. Chris Crawford • updated 4 years ago We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. By using Kaggle, you agree to our use of cookies. Got it Dataset GSE45827 on breast cancer gene expression from CuMiDa. 6 classes; 54676 genes; 151 samples; About. Here we present the Curated Microarray Database (CuMiDa), a repository containing 78 handpicked cancer microarray datasets, extensively curated from 30.000 studies from the Gene Expression Omnibus (GEO), solely for machine learning.The aim of CuMiDa is to offer homogeneous and state-of. The provided tables contain meta data which allows for high level analysis of a wide variety of sequenced genomes for multi cell organisms ranging from humans to corn, as we as bacteria and viruses. The tables also contain links to the actual genome sequence data via the 'GenBank FTP' and 'RefSeq FTP' columns. Links in these columns can provide. Kaggle is the world's largest data science community with powerful tools and resources to help you achieve your data science goals

Gene expression dataset (Golub et al

Molecular Classification of Cancer by Gene Expression Monitoring- A Kaggle Challenge - mitra052/Cancer-Detection-Kaggle Kaggle. Cervical Cancer Classification. This is another cancer prediction dataset however unlike previous datasets this is not focused on cell images or gene expression but rather it is focused personal history of patients including demographic info, STD's, and smoking history. This is great to practice working with sparse datasets The dataset of this competition is on E047 (Primary T CD8+ naive cells from peripheral blood) celltype from Roadmap Epigenomics Mapping Consortium (REMC) database. For each gene, it has 100 bins with five core histone modification marks [1] Datasets and files used in the GenePattern Tutorial. gp_tutorial_files.tar.gz. Tutorial files (gzip format) ALL/AML. Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression. Golub and Slonim et al., 1999. all_aml.tar.gz This project is based on Gene expression dataset from Kaggle. Here Molecular Classification of Cancer by Gene Expression monitoring Dataset is done. This dataset comes from a proof-of-concept study published in 1999 by Golub et al. It showed how new cases of cancer could be classified by gene expression monitoring (via DNA microarray) and thereby provided a general approach for identifying new.

genetics Datasets and Machine Learning Projects Kaggl

Gene Expression Classification Kaggl

Hello All,In this video we will be discussing about how to implement DNA sequencing classifier.Reference Url :https://www.kaggle.com/thomasnelson/working-wit.. The dataset for this research is taken from Kaggle and is provided by the Memorial Sloan Kettering Cancer Center (MSKCC). The world-class researchers and oncologists contribute the dataset. Three text transformation models, namely, CountVectorizer, TfidfVectorizer, and Word2Vec, are utilized for the conversion of text to a matrix of token counts Liver cancer Datasets. [ Sorting Controls ] Datasets are collections of data. BioGPS has thousands of datasets available for browsing and which can be easily viewed in our interactive data chart . Learn more. ‹‹ previous 1 2 next ››. Displaying datasets 1 - 10 of 11 in total Gene-1 values are the average of the gene-1 expression over 100 cell lines as explained in figure 2 step 4. Cell-1 value is the viability of the cells belonging to cell line 1 as explained in.

Gene Expression Analysis Kaggl

  1. Displaying datasets 1 - 10 of 248 in total. View Dataset Antisense miRNA-221/222 (si221/222) and control inhibitor (GFP) treated fulvestrant-resistant breast cancer cell
  2. Print a summary of a gene dataset by NCBI Gene ID, gene symbol or RefSeq nucleotide or protein accession. The summary is returned in JSON format. Refer to NCBI's command line quickstart documentation for information about getting started with the command-line tools. Examples datasets summary gene gene-id 672 datasets summary gene symbol brca1.
  3. Coronary artery Datasets. [ Sorting Controls ] Datasets are collections of data. BioGPS has thousands of datasets available for browsing and which can be easily viewed in our interactive data chart . Learn more. ‹‹ previous 1 2 next ››. Displaying datasets 1 - 10 of 17 in total
  4. Chromosome Datasets. Datasets are collections of data. BioGPS has thousands of datasets available for browsing and which can be easily viewed in our interactive data chart . Learn more

  1. He intentado descargar el kaggle dataset de kaggle dataset mediante el uso de Python. Sin embargo, me enfrenté a problemas mediante el uso del método de request y los archivos .csv de salida descargados son archivos html dañados
  2. This post will be focused on datasets openly available on Kaggle, I will write future posts on more comprehensive datasets and meta-datasets. Gene Expression Dataset This data set acts as a proof concept for the idea of classifying cancer by measuring gene expression
  3. Dataformat. There are training and test csv files which correspond to either variants or text. variants: columns = (ID,Gene,Variation,Class) ID: int, Index Column. GENE: str, name of gene. Mutation: str, mutation in gene. Class: int, 1-9, class of mutation (corresponds to cancer risk), this is the column we are trying to predict
  4. analysis of the dataset from kaggle.com. Contribute to babinyurii/cancer_gene_expression_profile_analysis-microarray_data development by creating an account on GitHub
  5. Featurizing Gene. There are 229 different categories of genes in the train data, and they are distibuted as follows. Next, we featurize Gene using one-hot encoding giving us 229 new features. In test data 643 out of 665 data points are covered: 96.69% In cross validation data 514 out of 532 data points are covered: 96.61%. Featurizing Variation

The problem deals with predicting the duration of a trip taken in New York City given the pickup and dropoff locations. This was a competition hosted on Kaggle.The primary dataset is released by the NYC Taxi and Limousine Commission, which includes pickup time, geo-coordinates, number of passengers, and several other variables 原文 标签 python download request dataset kaggle 我试图通过使用python下载 kaggle dataset 。 但是我通过使用 request 方法遇到了问题,下载的输出.csv文件是损坏的html文件 Alzheimer's disease Datasets. Datasets are collections of data. BioGPS has thousands of datasets available for browsing and which can be easily viewed in our interactive data chart . Learn more Displaying datasets 1 - 10 of 14 in total. View Dataset Expression data of human induced pluripotent stem cells (hiPSCs), human embryonic stem cells (hESCs) and those differentiated cells PulmonDB a curated gene expression lung disease database. PulmonDB is a curated gene expression database of human lung diseases, with RNA-seq and microarray data from different platforms that have.

Public Datasets. This site is a repository for selected datasets that have been collected and analyzed by investigators at MD Anderson. We have tried to provide a reasonable amount of explanation. Certain tools used to analyze these data are also posted under Software. Please note that supplementary data sets to published papers are found in. The online 'COVID-19 Radiography Dataset' [] by Tawsifur Rahman, which is the 'Winner of COVID-19 Dataset Award by Kaggle' is used here for the CNN-based CAD method.This dataset collects COVID-19 images from Cohen JP [] and different publications and Pneumonia and Normal images from the Kaggle pneumonia dataset of Paul M [].The dataset consists of 1200 COVID-19 images, 1341 Normal.

413. 2020 Kaggle Machine Learning & Data Science Survey. The most comprehensive dataset available on the state of ML and data science . Prize: $30,000. Team: - Kind: Analytics. Metric: - Year: 2021. Not Available! 412. NFL 1st and Future - Impact Detection. Detect helmet impacts in videos of NFL plays. Prize: $75,000. Team: 459. Kind: Feature In this video we'll use the Kaggle API to download a dataset from Kaggle using Python in a Jupyter Notebook. We'll use a generated token to be able to access.. I am searching some gene dataset where I can classify between animal and plant. Please help!! Press J to jump to the feed. Press question mark to learn the rest of the keyboard shortcuts. Log in sign up

Displaying datasets 1 - 10 of 74 in total. View Dataset A novel five-gene signature predicts overall and recurrence-free survival in NSCL About me Hey, listen! (weird Navi reference) . Allow me to introduce myself: I'm Johann. I was trained as a software developer at ModulAcht e. K. and have several years of experience in developing websites (C#, ASP.NET, HTML, CSS and such), desktop and lately also mobile applications (mostly C# and Java, for mobile development Flutter/Dart).. I further studied Bioinformatics (BSc and Msc) at. NCBI Datasets. NCBI Datasets is a new resource that lets you easily gather data from across NCBI databases. Find and download gene, transcript, protein and genome sequences, annotation and metadata We are going to create a deep learning model for a Kaggle competition: Personalized Medicine: Redefining Cancer Treatment The goal of the competition is to classify a document, a paper, into the type of mutation that will contribute to tumor growth. We also have the gene and the variant for the classification In this competition, you will have access to a unique dataset that combines gene expression and cell viability data. The data is based on a new technology that measures simultaneously (within the same samples) human cells' responses to drugs in a pool of 100 different cell types (thus solving the problem of identifying ex-ante, which cell.

Breast cancer gene expression - CuMiDa Kaggl

Genome Information For Sequenced Organisms Kaggl

The outcome of phase 1 for Kaggle dataset is a pandas dataframe of sentences and their clean tokens. Prepare task dataset: For the CORD-19 Kaggle submission, as mentioned before, task 4 from round #2 was selected and the below dataset were prepared: blood, purified virus, vp1 gene, as well as numeric data such as sample size: 25 gl, 2 or. Introduction and Project Scope One of the most exciting frontiers for machine learning is the field of medical diagnosis, where background information and nuanced decision-making are considered essential. When Memorial Sloan Kettering (MSK) released a Kaggle competition entitled Personalized Medicine: Redefining Cancer Treatment, we took on the controversial challenge of creating models. Datasets for the paper Zheng et al, Massively parallel digital transcriptional profiling of single cells (previously deposited to biorxiv). We encourage you to download the data here, as the BAM files deposited in the SRA database have had the cell barcode tags removed. We are working with NCBI to resolve this issue gene expression features. There are 772 gene expression features and they have g- prefix (g-0 to g-771). Each gene expression feature represents the expression of one particular gene, so there are.

Submitted Solution for Kaggle COVID-19 Open Research

David Beniaguev Kaggl

JMP Public featured datasets; Kaggle Datasets. KDD Cup center, with all data, tasks, and results. Kevin Chai list of datasets, for text, SNA, and other fields. KONECT, the Koblenz Network Collection, with large network datasets of all types in order to perform research in the area of network mining This example summarizes a data table using Datalib.You can fork this Block and change the data to get a quick overview of the shape of your data. This data was scrapped from IMDB and compiled by Kaggle hub protein Gene Sets. 289 sets of interacting proteins for hub proteins from the curated Hub Proteins Protein-Protein Interactions dataset. Gene Set. Description. AAR2. AAR2 splicing factor homolog (S. cerevisiae)|This gene encodes the homolog of the yeast A1-alpha2 repressin protein that is involved in mRNA splicing Hi Folks, I am looking for a dataset that would be used for symbolic regression through gene expression programming. I am going to compare the results with the Neural Net based regression. I have used the Boston house prices dataset so far but results are not encouraging on GEP. If anyone has any idea, please help. 0 comments gene expression cancer RNA-Seq Data Set Download: Data Folder, Data Set Description. Abstract: This collection of data is part of the RNA-Seq (HiSeq) PANCAN data set, it is a random extraction of gene expressions of patients having different types of tumor: BRCA, KIRC, COAD, LUAD and PRAD

Currently, we offer the following data sets: GENIE gene finding data set, containing a total of 793 unrelated human genes. This data set was used to train the GENIE gene finding system ( WWW-access) developed at LBNL and UC Santa Cruz. The last update was done in March 1998 using GenBank v.105. Please see the documentation file for further. Latest complete Netflix movie dataset . Created from 4 APIs. 11K+ rows and 30+ attributes of Netflix (Ratings, earnings, actors, language, availability, movie trailers, and many more) Dataset on Kaggle. Explore this dataset using FlixGem.com (this dataset is powering this webapp) Dataset on Google Sheets. Common Craw Conclusion Permalink. In this analysis we took a look at the thyroid related gene expression data available in the ARCHS 4 database. In general, we could see that the data are rather diverse in terms of tissue annotation, but can to some extend be merged together to obtain a more homogeneous annotation Kaggle, 2019 detect and segment tumors from brain MRI images data founded on Kaggle as here! The same dataset for thresholding of e-04 for model 2, the trained architecture was via. Dataset founded on Kaggle as reported here: Accuracy: 88 % of! Layers with large kernels set is the most technique in OpenCV, which is a clear between Dataset Search. Try coronavirus covid-19 or education outcomes site:data.gov. Learn more about Dataset Search. ‫العربية‬. ‪Deutsch‬. ‪English‬

Two dataset: 1. Training_variants(ID,gene,variation) This contain the information of the genetic mutation 2. Training_text(ID,Text) Workflow of the project: 1. Load the dataset and done some text-based preprocessing method. 2. Applied Exploratory Data analysis on the train dataset. 3. Features engineering: I. Gene feature from dataset. The encoded protein undergoes a series of cleavages during corneocyte maturation. This gene is highly polymorphic in human populations, and variation has been associated with skin diseases such as psoriasis, hypotrichosis and peeling skin syndrome. The gene is located in the major histocompatibility complex (MHC) class I region on chromosome 6 They also give results (not cross-validated) for classification by a rule-based expert system with that version of the dataset. Reference: Expert Sytem for Predicting Protein Localization Sites in Gram-Negative Bacteria, Kenta Nakai & Minoru Kanehisa, PROTEINS: Structure, Function, and Genetics 11:95-110, 1991

Taxon, Uniprot and the Gene Ontology. Using these vo-cabularies along with others describing indications, phe-notypes, species, countries, genes, proteins and drugs, we applied our named entity recognition tool, TERMite, to annotate the entire CORD-19 dataset. This has produced a richly annotated dataset with over 45 million annota The emergence of the novel COVID-19 pandemic has had a significant impact on global healthcare and the economy over the past few months. The virus's rapid widespread has led to a proliferation in biomedical research addressing the pandemic and its related topics. One of the essential Knowledge Discovery tools that could help the biomedical research community understand and eventually find a. This project is based on Gene expression dataset from Kaggle. Here Molecular Classification of Cancer by Gene Expression monitoring Dataset is done. This dataset comes from a proof-of-concept study published in 1999 by Golub et al. It showed how new cases of cancer could be classified by gene expression monitoring (via DNA microarray) and. Kaggle contains many machine learning competitions. Many open datasets are available at Kaggle datasets. Amazon Web Services hosts a number of public data sets. The Yahoo Webscope Program is another library of data sets . In general, open data is a good keyword to search for. Ewan Klein also has a nice list of open data resources I will also briefly describe the datasets and their potential applications. This post will be focused on datasets openly available on Kaggle, I will write future posts on more comprehensive datasets and meta-datasets. Gene Expression Dataset. This data set acts as a proof concept for the idea of classifying cancer by measuring gene expression

This dataset is one of 5 datasets of the NIPS 2003 feature selection challenge. 38. Dorothea: DOROTHEA is a drug discovery dataset. Chemical compounds represented by structural molecular features must be classified as active (binding to thrombin) or inactive. This is one of 5 datasets of the NIPS 2003 feature selection challenge. 39 This dataset has been published as a part of Kaggle competition. It has three .csv files, train.csv , test.csv and gender_submission.csv . We are going to work on train.csv data in this tutorial This was a competition hosted on Kaggle. The primary dataset is released by the NYC Taxi and Limousine Commission, which includes pickup time, geo-coordinates, number of passengers, and several other variables. The histogram depicts a few values in the Gene feature occur very commonly in the dataset and more than half of the Gene values.

My New Genetic Algorithm For Time Series - Becoming Human

Gene Expression Dataset: In this module the dataset that the system will run is defined. Sequence of actions to be carried out on those datasets is defined amongst file reading, loading and connecting to dataset repository. The proposed ensemble system has been applied to Colon dataset as the case in the existing system introduced by . In. The Boston Houses Dataset. The Boston Housing Dataset is among the most popular datasets for machine learning projects. It's suitable for pattern recognition projects and is a great way to exercise your ML knowledge. This dataset contains the US Census Service gathered information on the housing in the Boston Mass area and has around 500 cases The dataset consists of a gene expression matrix with 17,258 genes in 391 control cells from healthy donors, and 588 cells from 5 patients with bone marrow failure Leukemia data set This dataset comes from a study of gene expression in two types of acute leukemias, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). Gene expression levels were measured using Affymetrix high density oligonucleotide arrays containing 6817 human genes. A data set containing 72 observations from 3 leukemia types classes Feedback Sign in; Joi


GitHub - mitra052/Cancer-Detection-Kaggle: Molecular

  1. Now, to use Kaggle, you don't only need to understand why you should use it (practice, present your work, network, .), but also all of the things that you can do with it: 1. Datasets. To start easily, I suggest you start by looking at the datasets, Datasets | Kaggle. The kind of tricky thing here is that there is not really any way of.
  2. The dataset provides a variety of details about the several genes of one particular type of organism. The main dataset, (the downloadable files are Genes_relation.{data,test}) contains row data of the following form: Gene ID, Essential, Class, Complex, Phenotype, Motif, Chromosome Number, Function, Localization
  3. This dataset was downloaded from Kaggle . The practicality of this dataset was confirmed by radiologists. The COVID-CT dataset consists of 349 COVID-19 CT images from 216 patients and 397 non-COVID-19 CT images. Figure 5 shows the sample COVID-19 affected CT images from the COVID-CT dataset. By understanding the importance of images and labels.
  4. The model used by Sale A-When is the result of a survival analysis carried out on a large sales data set. Observations. Age of patient at time of operation (numerical) 2. Pclass and sex were significantly correlated with survival rate, Observation: This is similar to the common regression analysis where data-points are uncensored. topic, visit your repo's landing page and selec
  5. I have always used the UCI machine learning repository for practicing my ML algorithms. This site is not confined to bioinformatics but you do get omic data sets. I always believe data is data doesn't matter what field of work you are in, if you a..

Bioinformatics Datasets on Kaggle - Struggle Omic

GitHub - alitakin/Gene_Expression_Predict_Kaggle: ML

7 Time Series Datasets for Machine Learning. Last Updated on August 21, 2019. Machine learning can be applied to time series datasets. These are problems where a numeric or categorical value must be predicted, but the rows of data are ordered by time. Get Certified for Only $299 Combining All Encodings to Create a Consolidated Training Dataset: For each row, I combined the gene, mutation, and text one-hot-encodings to create a consolidated vector representing that information. of 64% and a Multinomial Log Loss of 1.12 which are comparable to the values reported by best performers of the Kaggle Competition I recently started working on an independent data science project using a dataset I found on Kaggle. The object is to build a model that will help classify mushrooms as either poisonous or edible based on a number of visually describable characteristics. — Photo Credit: Gene Taylor. A Ternary Classification. My First Multi-class Python. Dash apps go where Tableau and PowerBI cannot: NLP, object detection, predictive analytics, and more. With 0.5M+ downloads/month, Dash is the new standard for AI & data science apps The dataset consists of gene expressions of melanoma, colon tumour and leukaemia samples. The reason for taking these three sets of samples is that others (non-small cell lung cancer, breast cancer, etc.) have heterogeneous profiles and removing these gives an expected solution of three clear clusters

loss, which is specified by the Kaggle website. 3.1 DATASET The collected our dataset from the Kaggle competition and Memorial Sloan Kettering Cancer Center (MSKCC). The dataset has three parameters: genes, variations and clinical text. In the training set, 9 classes of mutations are given. Ou Multivariate, Text, Domain-Theory . Classification, Clustering . Real . 2500 . 10000 . 201 This dataset hosted over kaggle has information about the number of affected cases, deaths, and recovery from 2019 novel coronavirus. It has multiple csv files, with different features. The good thing about this dataset is that it covers information from across the globe. Therefore, better data analysis can be performed. It is updated regularly The leukemia dataset was taken from a collection of leukemia patient samples reported by Golub et. al., (1999). This dataset often serves as a benchmark for microarray analysis methods. It contains gene expressions corresponding to acute lymphoblast leukemia (ALL) and acute myeloid leukemia (AML) samples from bone marrow and peripheral blood. The dataset consisted of 72 samples: 49 samples of.

Datasets - GenePatter

Hi can you help me understand the meaning of : x = dataset.iloc[:, :-1].values y = dataset.iloc[:, 1].values Acc to the database my features are in first 5 columns and the last column is the response. - Gaurav Singh Nov 16 '17 at 5:3 Fig. 1 is a flowchart reporting the workflow for the construction and analysis of the milk proteome atlas. Table 1 reports the list of the 20 publications on cow milk proteome used to build the atlas. Table 2 reports numbers of GN without duplicate, numbers of datasets (under parenthesis) and the associated references (with publication identifiers from Table 1 in superscript) depending on.

Sign or symptom (T184), Disease or syndrome (T047), Gene or genome (T028), Immunologic factor (T129), Finding (T033), Body part, organ or organ component (T023).[8] The title and abstract sections of all papers in the CORD-19 dataset were processed against the various knowledge sources to extract discrete data from each paper and stored in Welcome to the UC Irvine Machine Learning Repository! We currently maintain 588 data sets as a service to the machine learning community. You may view all data sets through our searchable interface. For a general overview of the Repository, please visit our About page.For information about citing data sets in publications, please read our citation policy

Introduction: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to. The k-means clustering method is an unsupervised machine learning technique used to identify clusters of data objects in a dataset. There are many different types of clustering methods, but k-means is one of the oldest and most approachable.These traits make implementing k-means clustering in Python reasonably straightforward, even for novice programmers and data scientists Introduction. Prostate cancer (CaP) is the second leading cause of cancer death in US males, accounting for an estimated 31,620 deaths in 2019 [].Incidence, morbidity, and mortality rates of CaP vary substantially by race/ethnicity, representing one of the largest cancer disparities by race/ethnicity in the US [2, 3].Elevated CaP rates in men of African descent have also been observed globally []

Colon cancer gene expression data has been obtained from in the data acquisition phase. The datasets are made up of 62 cases (tests) and 2000 genes (attributes) from patients with colon cancer. Among them are 40 tumor biopsies (marked as abnormal) and 22 normal. Colon tumor sample data can be seen in Table 1 Lack of reproducibility of findings has been a criticism of genetic association studies on complex diseases, such as chronic obstructive pulmonary disease (COPD). We selected 257 polymorphisms of 16 genes with reported or potential relationships to COPD and genotyped these variants in a case-control study that included 953 COPD cases and 956 control subjects 1) Kaggle knows how to run a competition. I love how easy it is to set up a team, submit an entry, and get immediate feedback. 2) AzureML OOB is a good place to start and explore different ideas. However, it is obvious that stacked against more traditional teams, it does not do well. 3) Speaking of which Dataset. There are three provided files: - train.csv — the training set - test.csv — the test set - sample_submission.csv — the framework for official competition submissions Th e training dataset contains these columns: - id: a unique numeric identifier for each tweet - text: the actual content in the tweet - keyword: keywords from the tweet manually selected by the competition creators.

GitHub - dharsandip/Classification_of_Cancer_by_Gene

The Hm1 gene (Ullstrup, 1941, 1944) confers specific resistance against a leaf blight and ear mold disease of corn, caused by C. carbonum race 1 (CCR1). The exceptional virulence of race 1 on susceptible hm1 maize is due to production of a . 232 P.J. Balint-Kurti and G.S. Joha Metadata Service. Identifiers.org metadata service enables users to extract Schema.org from landing pages of the original providers by passing in Compact Identifiers Patients with liver disease have been continuously increasing because of excessive consumption of alcohol, inhale of harmful gases, intake of contaminated food, pickles and drugs. The liver has many essential functions, and liver disease presents a number of concerns for the delivery of medical care. Chronic liver disease (CLD) is common long-term conditions in the developed and developing world The hazard ratio for the. predicted high- versus low-risk groups over a 30-year span was 7.2 (95%. CI, 6.9-7.6). In a simulated deployment scenario, the model predicted. new-onset AF at 1 year.

Kaggle Datasets - IT - Engineering - Cloud - Financ

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