2024
Reading the palimpsest of cell interactions: What questions may we ask of the data?
Pavlicev M, Wagner G. Reading the palimpsest of cell interactions: What questions may we ask of the data? IScience 2024, 27: 109670. PMID: 38665209, PMCID: PMC11043885, DOI: 10.1016/j.isci.2024.109670.Peer-Reviewed Original ResearchCompartmentalization of cellular processesStructure of interaction networksCell interactionsMulticellular organismsIntegrity of cellsCellular processesInteraction networkLevels of structural organizationBiological functionsBiological interpretationCell communicationInteraction dataStructural organizationWealth of dataCellsCoordination of functionsOrganizationHigher levels of structural organizationCompartmentalizationInteraction
2019
Inherited glomerular diseases in the gilded age of genomic advancements
Gulati A, Dahl N, Tufro A. Inherited glomerular diseases in the gilded age of genomic advancements. Pediatric Nephrology 2019, 35: 959-968. PMID: 31049720, PMCID: PMC7184048, DOI: 10.1007/s00467-019-04266-y.Peer-Reviewed Original ResearchConceptsGenomic advancementsHigh-throughput next-generation sequencing technologiesNext-generation sequencing technologiesSingle nucleotide changeSingle nucleotide variationsDisease-causing mutationsDNA variationHuman genomeNext-generation sequencingGenomic informationSequencing technologiesNucleotide variationsAccurate genetic diagnosisNucleotide changesGenetic diagnosisSmall insertionsGenomic knowledgeCytogenetic methodsBiological interpretationMutation spectrumSequencingGenomic medicineGenomeUncertain significanceGlomerular diseaseInferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming
Ohlin M, Scheepers C, Corcoran M, Lees WD, Busse CE, Bagnara D, Thörnqvist L, Bürckert JP, Jackson KJL, Ralph D, Schramm CA, Marthandan N, Breden F, Scott J, Matsen F, Greiff V, Yaari G, Kleinstein SH, Christley S, Sherkow JS, Kossida S, Lefranc MP, van Zelm MC, Watson CT, Collins AM. Inferred Allelic Variants of Immunoglobulin Receptor Genes: A System for Their Evaluation, Documentation, and Naming. Frontiers In Immunology 2019, 10: 435. PMID: 30936866, PMCID: PMC6431624, DOI: 10.3389/fimmu.2019.00435.Peer-Reviewed Original ResearchMeSH KeywordsAllelesBase SequenceDatabases, GeneticDatasets as TopicGene LibraryGenes, ImmunoglobulinGenetic VariationGerm-Line MutationHigh-Throughput Nucleotide SequencingHumansImmunoglobulin Heavy ChainsImmunoglobulin Variable RegionPolymerase Chain ReactionSequence AlignmentSequence Homology, Nucleic AcidTerminology as TopicV(D)J RecombinationVDJ ExonsConceptsGene databaseInternational ImMunoGeneTics information systemAdaptive immune receptor repertoire sequencingLymphocyte receptor genesAllelic variantsGermline genesReceptor geneAIRR CommunityVertebrate speciesGenetic variationIg diversityAIRR-seq dataJ genesIg genesAllelic sequencesGenesIGHV genesEffector moleculesUnprecedented insightsB-cell lineageBiological interpretationT cell receptorReference databaseGene variationRepertoire studies
2017
Corrigendum to “Common cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation” [Biochim. Biophys. Acta 1862(8) (2017) 766–770]
Koelmel J, Ulmer C, Jones C, Yost R, Bowden J. Corrigendum to “Common cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation” [Biochim. Biophys. Acta 1862(8) (2017) 766–770]. Biochimica Et Biophysica Acta (BBA) - Molecular And Cell Biology Of Lipids 2017, 1862: 1024. PMID: 28648965, DOI: 10.1016/j.bbalip.2017.06.013.Peer-Reviewed Original ResearchCommon cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation
Koelmel J, Ulmer C, Jones C, Yost R, Bowden J. Common cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation. Biochimica Et Biophysica Acta (BBA) - Molecular And Cell Biology Of Lipids 2017, 1862: 766-770. PMID: 28263877, PMCID: PMC5584053, DOI: 10.1016/j.bbalip.2017.02.016.Peer-Reviewed Original Research
2006
Bayesian error analysis model for reconstructing transcriptional regulatory networks
Sun N, Carroll RJ, Zhao H. Bayesian error analysis model for reconstructing transcriptional regulatory networks. Proceedings Of The National Academy Of Sciences Of The United States Of America 2006, 103: 7988-7993. PMID: 16702552, PMCID: PMC1472417, DOI: 10.1073/pnas.0600164103.Peer-Reviewed Original ResearchConceptsTranscriptional regulatory networksGene expression dataTranscription regulationRegulatory networksExpression dataProtein-DNA binding dataDNA sequence dataFundamental biological processesYeast cell cycleHigh-throughput technologiesMicroarray gene expression dataBiological experimentsSequence dataGenomic dataBiological processesCell cycleClear biological interpretationThroughput technologiesBiological interpretationMarkov chain Monte CarloBayesian hierarchical model frameworkBiochemical reactionsRegulationLinear system modelHierarchical model framework
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