0000000001323196

AUTHOR

Augusto Rendon

showing 3 related works from this author

PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources.

2019

Background Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data. Results In this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTfu…

Databases FactualComputer scienceAnnotationBiological databaseRESTfulcomputer.software_genreNoSQLlcsh:Computer applications to medicine. Medical informaticsBiochemistryDatabase03 medical and health sciencesAnnotationUser-Computer Interface0302 clinical medicineInstallationStructural BiologyVariantMolecular Biologylcsh:QH301-705.5030304 developmental biologycomputer.programming_language0303 health sciencesBiological dataDatabaseApplied MathematicsRepositoryComputational BiologyPython (programming language)CellBaseComputer Science Applicationslcsh:Biology (General)Scripting language030220 oncology & carcinogenesislcsh:R858-859.7Web servicecomputerSoftwarePython
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Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

2011

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns—independent component analysis—to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify maj…

MaleCancer ResearchGene ExpressionGenome-wide association studyGenetic NetworksCoronary Artery Disease[SDV.GEN] Life Sciences [q-bio]/GeneticsCardiovascularMESH: MonocytesMonocytesMESH: HypertensionTranscriptomes0302 clinical medicineMESH: ProteinsMESH: Genetic VariationGenetics (clinical)GeneticsMESH: Aged0303 health scienceseducation.field_of_studyMESH: Middle AgedMESH: Polymorphism Single NucleotideIntracellular Signaling Peptides and ProteinsMESH: Genetic Predisposition to DiseaseGenomicsMESH: Transcription FactorsMiddle AgedMESH: Ribosomal ProteinsMESH: Gene Expression Regulation3. Good healthHypertensionMedicineFemaleMESH: Diabetes Mellitus Type 1Research ArticleAdultRibosomal Proteinslcsh:QH426-470PopulationQuantitative Trait LociLocus (genetics)Single-nucleotide polymorphismBiologyQuantitative trait locusPolymorphism Single Nucleotide03 medical and health sciencesMESH: Gene Expression ProfilingGenome Analysis ToolsGeneticsGenome-Wide Association StudiesHumansGenetic Predisposition to DiseaseGene NetworkseducationMolecular BiologyBiologyEcology Evolution Behavior and SystematicsMESH: Genome Human030304 developmental biologyGenetic associationAdaptor Proteins Signal TransducingAged[SDV.GEN]Life Sciences [q-bio]/GeneticsMESH: HumansGenome HumanGene Expression ProfilingGenetic VariationProteinsHuman GeneticsMESH: AdultAtherosclerosisMESH: MaleMESH: Quantitative Trait LociGene expression profilingCeliac Diseaselcsh:GeneticsDiabetes Mellitus Type 1Gene Expression RegulationExpression quantitative trait lociGenetics of DiseaseMESH: Genome-Wide Association StudyMESH: MuramidaseMuramidaseGenome Expression AnalysisMESH: Female030217 neurology & neurosurgeryMESH: Celiac DiseaseGenome-Wide Association StudyTranscription Factors
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Additional file 1: of PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources

2019

PyCellBase use case. Example of usage of the PyCellBase REST client library. (IPYNB 15 kb)

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