Search results for "Bioinformàtica"

showing 8 items of 8 documents

Phylogenomics Identifies an Ancestral Burst of Gene Duplications Predating the Diversification of Aphidomorpha

2019

Aphids (Aphidoidea) are a diverse group of hemipteran insects that feed on plant phloem sap. A common finding in studies of aphid genomes is the presence of a large number of duplicated genes. However, when these duplications occurred remains unclear, partly due to the high relatedness of sequenced species. To better understand the origin of aphid duplications we sequenced and assembled the genome of Cinara cedri, an early branching lineage (Lachninae) of the Aphididae family. We performed a phylogenomic comparison of this genome with 20 other sequenced genomes, including the available genomes of five other aphids, along with the transcriptomes of two species belonging to Adelgidae (a close…

0106 biological sciences:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Gene duplicationAphidomorphaLineage (evolution)010603 evolutionary biology01 natural sciencesGenomeSyntenyDNA sequencingFilogèniaEvolution Molecular03 medical and health sciencessequencia genómicaSpecies SpecificityPhylogenomicsGene duplicationBioinformaticaGeneticsAdelgidaeAnimalsMolecular BiologyEcology Evolution Behavior and SystematicsDiscoveriesPhylogeny030304 developmental biologySegmental duplication0303 health sciencesAphidbiologyWhole Genome SequencingGene Expression Profilinggene duplicationfood and beveragesHigh-Throughput Nucleotide SequencingAfidomorfabiochemical phenomena metabolism and nutritionbiology.organism_classificationaphidsGenòmicaGene Expression RegulationEvolutionary biologyAphidsInsect ProteinsGenèticaMolecular Biology and Evolution
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Transcriptomic and Genetic Associations between Alzheimer's Disease, Parkinson's Disease, and Cancer.

2021

Simple Summary Epidemiological studies have identified a link between neurodegenerative disorders and a reduced risk of overall cancer. Increases and decreases in the risk of site-specific cancers have also been reported. However, it is still unknown whether these associations arise due to shared genetic and molecular factors or are explained by other phenomena (e.g., biases in epidemiological studies or the use of medication). In this study, we aimed to investigate the potential molecular, genetic, and pharmacological links between Alzheimer’s and Parkinson’s diseases and a large panel of 22 cancer types. To examine the overlapping involvement of genes and pathways, we obtained differentia…

0301 basic medicineOncologyCancer ResearchParkinson's diseaseGenetic correlationsGenome-wide association studyDiseaseComorbidityParkinson Enfermedad de - Aspectos genéticos.chemistry.chemical_compound0302 clinical medicineExemestaneParkinson's disease - Genetic aspects.MedicineParkinsonCáncer - Aspectos genéticos.Càncer -- Aspectes genèticsRC254-282Alzheimer's disease - Genetic aspects.NeurodegenerationNeoplasms. Tumors. Oncology. Including cancer and carcinogensCódigo genético.comorbidityOncology:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]medicine.medical_specialtyGenetic code.Alzheimer Enfermedad de - Aspectos genéticos.Article03 medical and health sciencesInternal medicineParkinson Malaltia dePI3K/AKT/mTOR pathwaygenetic correlationsCancer - Genetic aspects.business.industryCancertranscriptomicmedicine.diseaseComorbidityAlzheimer Malaltia d'030104 developmental biologychemistryTranscriptomicmeta-analysesMeta-analysesNeurodegenerative disordersAlzheimerGene expressionbusiness030217 neurology & neurosurgeryCancers
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Deciphering genomic heterogeneity and the internal composition of tumour activities through a hierarchical factorisation model

2021

Genomic heterogeneity constitutes one of the most distinctive features of cancer diseases, limiting the efficacy and availability of medical treatments. Tumorigenesis emerges as a strongly stochastic process, producing a variable landscape of genomic configurations. In this context, matrix factorisation techniques represent a suitable approach for modelling such complex patterns of variability. In this work, we present a hierarchical factorisation model conceived from a systems biology point of view. The model integrates the topology of molecular pathways, allowing to simultaneously factorise genes and pathways activity matrices. The protocol was evaluated by using simulations, showing a hi…

:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Matrix factorisationComputer scienceBioinformaticsGeneral MathematicsSystems biologyPopulationMatrix factorisationContext (language use)Computational biologyComputational biologyGenomic heterogeneitygenomic heterogeneityFactorizationBioinformàticaSimulació per ordinadorComputer Science (miscellaneous)QA1-939cancerVariabilityeducationEngineering (miscellaneous)Topology (chemistry)Cancereducation.field_of_studyvariabilitymatrix factorisationLimitingbioinformaticsCàncer--Aspectes genèticsGenòmicaBreast--CancerTumorigenesisMathematics
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Client Applications and Server-Side Docker for Management of RNASeq and/or VariantSeq Workflows and Pipelines of the GPRO Suite

2023

The GPRO suite is an in-progress bioinformatic project for -omics data analysis. As part of the continued growth of this project, we introduce a client- and server-side solution for comparative transcriptomics and analysis of variants. The client-side consists of two Java applications called “RNASeq” and “VariantSeq” to manage pipelines and workflows based on the most common command line interface tools for RNA-seq and Variant-seq analysis, respectively. As such, “RNASeq” and “VariantSeq” are coupled with a Linux server infrastructure (named GPRO Server-Side) that hosts all dependencies of each application (scripts, databases, and command line interface software). Implementation of the Serv…

:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]PipelinesArtificial intelligenceRNA sequenceRNASeqGraphical user interfaces (Computer systems)WorkflowsVariantSeqGeneticsInterface environmentsLinux device driversGenomesGenetics (clinical)Server-sideResequencingGenes
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Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

Computer scienceAlgorismesPrediction by partial matchingCompression dissimilaritycomputer.software_genreBiochemistryProtein Structure SecondaryPhylogenetic studiesStructural BiologySequence Analysis ProteinDatabases Proteinlcsh:QH301-705.5Biological dataNCDApplied MathematicsGenomicsClassificationCDComputer Science ApplicationsBenchmarking:Informàtica::Informàtica teòrica [Àrees temàtiques de la UPC]Universal compression dissimilarityArea Under CurveMetric (mathematics)lcsh:R858-859.7Data miningAlgorithmsData compressionResearch Article:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Normalization (statistics)lcsh:Computer applications to medicine. Medical informaticsBioinformatics Sequence Alignment AlgorithmsSet (abstract data type)Similarity (network science)Normalized compression sissimilarityData compression (Computer science)AnimalsHumansAmino Acid SequenceMolecular BiologyBiologyDades -- Compressió (Informàtica)USMUniversal similarity metricProteinsUCDProtein Structure TertiaryData setGenòmicaStatistical classificationlcsh:Biology (General)ROC CurvecomputerSequence AlignmentSoftwareBMC bioinformatics
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Pan-cancer analysis of whole genomes

2020

Publisher's version (útgefin grein)

Maletert promoter mutationsCancer development and immune defence Radboud Institute for Molecular Life Sciences [Radboudumc 2]DNA Mutational AnalysisNormal tissuesystematic analysisGermlineTranscriptome0302 clinical medicineAetiologyCàncerCellular SenescenceCancer0303 health sciencesdna-damageMassive parallel sequencingPan cancerREARRANGEMENTSHigh-Throughput Nucleotide SequencingGenomicsSciences bio-médicales et agricolesTelomereCOMPREHENSIVE3. Good healthTERT PROMOTER MUTATIONSsignatures030220 oncology & carcinogenesisScience & Technology - Other TopicsErfðarannsóknirHuman:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]EvolutionRNA SplicingGenomicsArticleEvolution MolecularStructural variationRC025403 medical and health sciencesSDG 3 - Good Health and Well-beingGeneticgenomicsSYSTEMATIC ANALYSISGeneticsGenomics--Databases.HumansGenetic TestingMolecular BiologySIGNATURESWhole genome sequencing1000 MultidisciplinaryChromothripsisScience & TechnologyRC0254 Neoplasms. Tumors. Oncology (including Cancer)Information DisseminationResearchInstitutes_Networks_Beacons/mcrcPreventionBiology and Life SciencesMolecularOncogenesCloud Computingmedicine.diseaseGenòmicaCompute cloudsMutation570 Life sciences; biologyCOMPREHENSIVE CHARACTERIZATIONGenèticaWhole Genome Sequencing--methodsBackground informationDNA Mutational Analysis ; Evolution ; Genetic / genetics ; Genome ; Genomics ; Germ-Line Mutation / genetics ; High-Throughput Nucleotide Sequencing ; Human / genetics ; Humans ; ICGC/TCGA Pan-Cancer Analysis of Whole Genomes ConsortiumMedizinGenomeWhole-genomeGenome mappingNeoplasms2.1 Biological and endogenous factorsPromoter Regions GeneticCàncer -- Aspectes genèticsTelomeraseGeneticsWomen's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17]MultidisciplinaryChromothripsisGenomeManchester Cancer Research Centregenomics cancer profiling3rd-DAS10124 Institute of Molecular Life SciencesWomen's cancers Radboud Institute for Health Sciences [Radboudumc 17]Multidisciplinary SciencesParallel sequencingICGC/TCGA Pan-Cancer Analysis of Whole Genomes ConsortiumFemaleprofilingMedical GeneticsEngineering sciences. TechnologyBiotechnologyGeneral Science & TechnologyThe Cancer Genome Atlas610 Medicine & healthComputational biologyQH426 GeneticsBiologyConsortium of the International Cancer Genome ConsortiumPromoter RegionsGermline mutationPan-cancer analysisKrabbameinsrannsóknirmedicinecancerddc:610QH426Germ-Line MutationMedicinsk genetikKrabbamein030304 developmental biologyCell ProliferationLANDSCAPEGenome Humancomprehensive characterizationPan-cancer analysis of whole genomesPoint mutationHuman GenomeCancerReproducibility of ResultsSOMATIC MUTATIONSEVOLUTIONCancer sequencing Chromothripsis telomereDNA-DAMAGEMutagenesisPATTERNS3111 BiomedicineCHARACTERIZATION
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The era of reference genomes in conservation genomics

2022

Progress in genome sequencing now enables the large-scale generation of reference genomes. Various international initiatives aim to generate reference genomes representing global biodiversity. These genomes provide unique insights into genomic diversity and architecture, thereby enabling comprehensive analyses of population and functional genomics, and are expected to revolutionize conservation genomics.

QH301 Biology580 Plants (Botany)Genetics -- ResearchEvolutionsbiologibiodiversity conservation; conservation genetics; ERGA; European Reference Genome AtlasConservation genetics; Biodiversity conservation; European Reference Genome Atlas; ERGAAnimal genome mappingudc:630*1GenomeGEERGA[SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE][SDE.BE.BIOD]Environmental Sciences/Biodiversity and Ecology/domain_sde.be.biodERGA ; Biodiversity [MeSH] ; Genomics [MeSH] ; Ecology Evolution Behavior and Systematics ; conservation genetics ; Genome [MeSH] ; biodiversity conservation ; European Reference Genome Atlas3rd-DASGenomicsBiodiversityreferenčni genomi[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][SDE.BE.BEC]Environmental Sciences/Biodiversity and Ecology/domain_sde.be.becChemistry10121 Department of Systematic and Evolutionary BotanygenomikaGE Environmental Sciences:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]biodiverzitetaSettore BIO/18 - GENETICAeducationQH426 GeneticsQH301European Reference Genome AtlasVDP::Matematikk og Naturvitenskap: 400::Basale biofag: 470[SDE.BE.EVO]Environmental Sciences/Biodiversity and Ecology/domain_sde.be.evoGeneticsconservation genetics ; biodiversity conservation ; European Reference Genome Atlas ; ERGAgenomi10211 Zurich-Basel Plant Science CenterGenomesGenetikBiologyQH426Ecology Evolution Behavior and SystematicsEvolutionary BiologyBiodiversity conservation; Conservation genetics; European Reference Genome AtlasAmbientaleEcologíaGenética1105 Ecology Evolution Behavior and Systematicsconservation geneticsWildlife conservation570 Life sciences; biologyHuman medicinebiodiversity conservationAnimal genetics[SDE.BE]Environmental Sciences/Biodiversity and EcologyGenètica
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CROSSMAPPER: estimating cross-mapping rates and optimizing experimental design in multi-species sequencing studies

2020

Motivation Numerous sequencing studies, including transcriptomics of host-pathogen systems, sequencing of hybrid genomes, xenografts, mixed species systems, metagenomics and meta-transcriptomics, involve samples containing genetic material from divergent organisms. A crucial step in these studies is identifying from which organism each sequencing read originated, and the experimental design should be directed to minimize biases caused by cross-mapping of reads to incorrect source genomes. Additionally, pooling of sufficiently different genetic material into a single sequencing library could significantly reduce experimental costs but requires careful planning and assessment of the impact of…

Statistics and Probability:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Computer sciencecomputer.software_genreBiochemistryGenomeTranscriptome03 medical and health sciencesResource (project management)GenomesTranscriptomicsMolecular BiologyOrganismGenòmica -- Informàtica030304 developmental biology0303 health sciences030306 microbiologyHigh-Throughput Nucleotide SequencingGenomicsSequence Analysis DNADNAGenome analysisGenome AnalysisAnàlisis de seqüènciesComputer Science ApplicationsApplications NoteComputational MathematicsComputational Theory and MathematicsCross-mappingResearch DesignMetagenomicsRNAData miningLine (text file)computerSoftwareGenèticaparametres
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