Showing 18 of total 18 results (show query)
ramikrispin
coronavirus:The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset
Provides a daily summary of the Coronavirus (COVID-19) cases by state/province. Data source: Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus <https://systems.jhu.edu/research/public-health/ncov/>.
Maintained by Rami Krispin. Last updated 2 years ago.
covid-19covid19covid19-datadataset
67.4 match 499 stars 8.25 score 716 scripts
covid19datahub
COVID19:COVID-19 Data Hub
Unified datasets for a better understanding of COVID-19.
Maintained by Emanuele Guidotti. Last updated 27 days ago.
2019-ncovcoronaviruscovid-19covid-datacovid19-data
11.0 match 252 stars 11.08 score 265 scriptsramikrispin
covid19italy:The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Italy Dataset
Provides a daily summary of the Coronavirus (COVID-19) cases in Italy by country, region and province level. Data source: Presidenza del Consiglio dei Ministri - Dipartimento della Protezione Civile <https://www.protezionecivile.it/>.
Maintained by Rami Krispin. Last updated 2 years ago.
13.1 match 47 stars 6.07 score 25 scripts
mounabelaid
covid19tunisia:Cases of COVID-19 in Tunisia
Data personnally collected about the spread of COVID-19 (SARS-COV-2) in Tunisia.
Maintained by Mouna Belaid. Last updated 4 years ago.
coronaviruscoronavirus-trackingcovid-19covid-19-tunisiacovid-19data
18.5 match 5 stars 3.70 score 5 scripts
jvanschalkwyk
corona:Coronavirus ('Rona') Data Exploration
Manipulate and view coronavirus data and other societally relevant data at a basic level.
Maintained by Jo van Schalkwyk. Last updated 4 years ago.
10.8 match 2.70 score 1 scripts
covid19r
covid19swiss:COVID-19 Cases in Switzerland and Principality of Liechtenstein
Provides a daily summary of the Coronavirus (COVID-19) cases in Switzerland cantons and Principality of Liechtenstein. Data source: Specialist Unit for Open Government Data Canton of Zurich <https://www.zh.ch/de/politik-staat/opendata.html>.
Maintained by Rami Krispin. Last updated 4 years ago.
5.4 match 4.00 score 8 scripts
bioc
DeepPINCS:Protein Interactions and Networks with Compounds based on Sequences using Deep Learning
The identification of novel compound-protein interaction (CPI) is important in drug discovery. Revealing unknown compound-protein interactions is useful to design a new drug for a target protein by screening candidate compounds. The accurate CPI prediction assists in effective drug discovery process. To identify potential CPI effectively, prediction methods based on machine learning and deep learning have been developed. Data for sequences are provided as discrete symbolic data. In the data, compounds are represented as SMILES (simplified molecular-input line-entry system) strings and proteins are sequences in which the characters are amino acids. The outcome is defined as a variable that indicates how strong two molecules interact with each other or whether there is an interaction between them. In this package, a deep-learning based model that takes only sequence information of both compounds and proteins as input and the outcome as output is used to predict CPI. The model is implemented by using compound and protein encoders with useful features. The CPI model also supports other modeling tasks, including protein-protein interaction (PPI), chemical-chemical interaction (CCI), or single compounds and proteins. Although the model is designed for proteins, DNA and RNA can be used if they are represented as sequences.
Maintained by Dongmin Jung. Last updated 5 months ago.
softwarenetworkgraphandnetworkneuralnetworkopenjdk
3.4 match 4.78 score 4 scripts 2 dependents
kjhealy
covdata:COVID-19 Data
COVID-19 related data from the ECDC, the COVID-19 Tracking Project, the New York Times, the Human Mortality Database, and Apple. Packaged for R.
Maintained by Kieran Healy. Last updated 2 years ago.
3.3 match 83 stars 4.73 score 129 scripts
a-roshani
ntsDatasets:Neutrosophic Data Sets
Provides a collection of datasets related to neutrosophic sets for statistical modeling and analysis.
Maintained by Amin Roshani. Last updated 8 months ago.
3.6 match 1 stars 3.78 score
msq-123
CovidMutations:Mutation Analysis and Assay Validation Toolkit for COVID-19 (Coronavirus Disease 2019)
A feasible framework for mutation analysis and reverse transcription polymerase chain reaction (RT-PCR) assay evaluation of COVID-19, including mutation profile visualization, statistics and mutation ratio of each assay. The mutation ratio is conducive to evaluating the coverage of RT-PCR assays in large-sized samples<doi:10.20944/preprints202004.0529.v1>.
Maintained by Shaoqian Ma. Last updated 5 years ago.
2.8 match 4 stars 4.30 score 6 scripts
terminological
arear:Geospatial Convenience Functions and a Supply Demand Catchment Area Generator
Geospatial function collection from the COVID-19 pandemic. The main focus of this was integrating geospatial demographic, hospital capacity and COVID data from England, Scotland, Wales and Northern Ireland, all of which were available on different sites and methods. The UK has a wide range of administrative geographic boundaries for different purposes and moving from different scales and resolutions proved necessary. As the geospatial operations are quite time consuming but don't need to be repeated the ability to cache results of geospatial transformations is useful and embedded into these functions.
Maintained by Robert Challen. Last updated 11 months ago.
2.4 match 4 stars 3.30 score 4 scripts
edonnachie
ICD10gm:Metadata Processing for the German Modification of the ICD-10 Coding System
Provides convenient access to the German modification of the International Classification of Diagnoses, 10th revision (ICD-10-GM). It provides functionality to aid in the identification, specification and historisation of ICD-10 codes. Its intended use is the analysis of routinely collected data in the context of epidemiology, medical research and health services research. The underlying metadata are released by the German Institute for Medical Documentation and Information <https://www.dimdi.de>, and are redistributed in accordance with their license.
Maintained by Ewan Donnachie. Last updated 1 years ago.
bfarmcharlsoncomorbiditiesdiagnosesdimdiicd-10metadataroutinedatenversorgungsforschung
1.3 match 10 stars 5.30 score 20 scripts
thiyangtdata
covid19srilanka:The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data in Sri Lanka
Provides a daily counts of the Coronavirus (COVID19) cases by districts and country. Data source: Epidemiological Unit, Ministry of Health, Sri Lanka <https://www.epid.gov.lk/web/>.
Maintained by Thiyanga S. Talagala. Last updated 2 years ago.
3.3 match 1.70 score 7 scriptsbioc
GenomAutomorphism:Compute the automorphisms between DNA's Abelian group representations
This is a R package to compute the automorphisms between pairwise aligned DNA sequences represented as elements from a Genomic Abelian group. In a general scenario, from genomic regions till the whole genomes from a given population (from any species or close related species) can be algebraically represented as a direct sum of cyclic groups or more specifically Abelian p-groups. Basically, we propose the representation of multiple sequence alignments of length N bp as element of a finite Abelian group created by the direct sum of homocyclic Abelian group of prime-power order.
Maintained by Robersy Sanchez. Last updated 3 months ago.
mathematicalbiologycomparativegenomicsfunctionalgenomicsmultiplesequencealignmentwholegenomegenetic-codegenetic-code-algebragenomegenome-algebra
1.1 match 4.30 score 9 scripts
uclouvain-cbio
rWSBIM1207:Companion Package for WSBIM1207 Course
Companion package for the WSBIM1207 course, distributing data and general documentation, and making course administration easier.
Maintained by Laurent Gatto. Last updated 9 months ago.
1.9 match 2.00 score 7 scripts
mponce0
covid19.analytics:Load and Analyze Live Data from the COVID-19 Pandemic
Load and analyze updated time series worldwide data of reported cases for the Novel Coronavirus Disease (COVID-19) from different sources, including the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository <https://github.com/CSSEGISandData/COVID-19>, "Our World in Data" <https://github.com/owid/> among several others. The datasets reporting the COVID-19 cases are available in two main modalities, as a time series sequences and aggregated data for the last day with greater spatial resolution. Several analysis, visualization and modelling functions are available in the package that will allow the user to compute and visualize total number of cases, total number of changes and growth rate globally or for an specific geographical location, while at the same time generating models using these trends; generate interactive visualizations and generate Susceptible-Infected-Recovered (SIR) model for the disease spread.
Maintained by Marcelo Ponce. Last updated 3 years ago.
covid19covid19-datancov2019sars-cov-2
0.5 match 33 stars 5.52 score 20 scripts
qingyuanzhao
bets.covid19:The BETS Model for Early Epidemic Data
Implements likelihood inference for early epidemic analysis. BETS is short for the four key epidemiological events being modeled: Begin of exposure, End of exposure, time of Transmission, and time of Symptom onset. The package contains a dataset of the trajectory of confirmed cases during the coronavirus disease (COVID-19) early outbreak. More detail of the statistical methods can be found in Zhao et al. (2020) <arXiv:2004.07743>.
Maintained by Qingyuan Zhao. Last updated 5 years ago.
0.5 match 27 stars 4.43 score 2 scripts
