2019
Visualizing structure and transitions in high-dimensional biological data
Moon KR, van Dijk D, Wang Z, Gigante S, Burkhardt DB, Chen WS, Yim K, Elzen AVD, Hirn MJ, Coifman RR, Ivanova NB, Wolf G, Krishnaswamy S. Visualizing structure and transitions in high-dimensional biological data. Nature Biotechnology 2019, 37: 1482-1492. PMID: 31796933, PMCID: PMC7073148, DOI: 10.1038/s41587-019-0336-3.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencing datasetsSingle-cell RNA sequencingUnique biological insightsRNA sequencing datasetsGerm layer differentiationMain developmental branchesHigh-throughput technologiesGut microbiome dataRNA sequencingUndescribed subpopulationsHigh-dimensional biological dataSequencing datasetsBiological insightsDevelopmental branches
2017
Heterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial)
Dhruva SS, Huang C, Spatz ES, Coppi AC, Warner F, Li SX, Lin H, Xu X, Furberg CD, Davis BR, Pressel SL, Coifman RR, Krumholz HM. Heterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial). Hypertension 2017, 70: 94-102. PMID: 28559399, DOI: 10.1161/hypertensionaha.117.09221.Peer-Reviewed Original ResearchConceptsAntihypertensive therapySystolic blood pressure responseAdverse cardiovascular eventsFavorable initial responseBlood pressure responseHigher hazard ratioCardiovascular eventsCardiovascular outcomesHazard ratioMultivariable adjustmentHeart failureAverage SBPRandomized trialsOdds ratioCardiovascular diseaseSBPStudy participantsRespondersMonthsPressure responseImmediate respondersALLHATEarly responseInitial responseSuperior discrimination
2014
Quantitative Arbor Analytics: Unsupervised Harmonic Co-Clustering of Populations of Brain Cell Arbors Based on L-Measure
Lu Y, Carin L, Coifman R, Shain W, Roysam B. Quantitative Arbor Analytics: Unsupervised Harmonic Co-Clustering of Populations of Brain Cell Arbors Based on L-Measure. Neuroinformatics 2014, 13: 47-63. PMID: 25086878, DOI: 10.1007/s12021-014-9237-2.Peer-Reviewed Original ResearchConceptsCo-clustering methodAnalytics systemSynthetic datasetsThree-dimensional visualizationAnalysis ToolkitHeterogeneous ensembleDistance measureAlgorithmMultivariate data pointsData smoothingData pointsWavelet basisData matrixHarmonic analysis theoryL-measureNeuroMorpho databaseDatasetAnalysis theoryToolkitVisualizationEnsembleRobustnessDatabaseSuperiorityMethodDiffusion methods for aligning medical datasets: Location prediction in CT scan images
Fernández Á, Rabin N, Coifman RR, Eckstein J. Diffusion methods for aligning medical datasets: Location prediction in CT scan images. Medical Image Analysis 2014, 18: 425-432. PMID: 24444669, DOI: 10.1016/j.media.2013.12.009.Peer-Reviewed Original Research
2013
Reply to about the electrophysiological basis of resting state networks
Duncan D, Duckrow RB, Pincus SM, Goncharova I, Hirsch LJ, Spencer DD, Coifman RR, Zaveri HP. Reply to about the electrophysiological basis of resting state networks. Clinical Neurophysiology 2013, 125: 1713-1714. PMID: 24440225, DOI: 10.1016/j.clinph.2013.12.098.Commentaries, Editorials and LettersIntracranial EEG evaluation of relationship within a resting state network
Duncan D, Duckrow RB, Pincus SM, Goncharova I, Hirsch LJ, Spencer DD, Coifman RR, Zaveri HP. Intracranial EEG evaluation of relationship within a resting state network. Clinical Neurophysiology 2013, 124: 1943-1951. PMID: 23790525, DOI: 10.1016/j.clinph.2013.03.028.Peer-Reviewed Original ResearchConceptsDefault mode networkIntracranial EEG evaluationMode networkLocalization-related epilepsyCross-approximate entropyNeuronal involvementHemodynamic measurementsIntracranial EEG recordingsEEG evaluationBackground activityGamma powerFMRI studyIntracranial EEGBrain activityPatientsEEG recordingsLow levelsT2EpilepsyMagnitude squared coherenceT1Identifying preseizure state in intracranial EEG data using diffusion kernels
Duncan D, Talmon R, Zaveri HP, Coifman RR. Identifying preseizure state in intracranial EEG data using diffusion kernels. Mathematical Biosciences And Engineering 2013, 10: 579-590. PMID: 23906137, DOI: 10.3934/mbe.2013.10.579.Peer-Reviewed Original Research
2012
The automated malnutrition assessment
David G, Bernstein LH, Coifman RR. The automated malnutrition assessment. Nutrition 2012, 29: 113-121. PMID: 23116774, DOI: 10.1016/j.nut.2012.04.017.Peer-Reviewed Original Research