2025
scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links
Wang G, Zhao J, Lin Y, Liu T, Zhao Y, Zhao H. scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links. Nature Communications 2025, 16: 4994. PMID: 40442129, PMCID: PMC12122792, DOI: 10.1038/s41467-025-60333-z.Peer-Reviewed Original ResearchConceptsDeep learning frameworkSingle-cell multi-omics researchSingle-cell multi-omics dataLearning frameworkMulti-omics dataGenerative adversarial networkSingle-cell technologiesData alignmentSingle-cell resolutionMulti-omics researchDownstream analysisCellular statesOmics datasetsAdversarial networkNeural networkProteomic profilingCorrelated featuresBiological informationOmics perspectiveDiverse datasetsFeature topologyDisease mechanismsCell embeddingData resourcesRelationship inferenceSIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data
Dong M, Su D, Kluger H, Fan R, Kluger Y. SIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data. Nature Communications 2025, 16: 2990. PMID: 40148341, PMCID: PMC11950362, DOI: 10.1038/s41467-025-58089-7.Peer-Reviewed Original ResearchConceptsOmics dataSpatial omics dataAnalysis of gene expressionSingle-cell resolutionDownstream analysisCellular statesSpatial interaction modelsGerminal center B cellsGene expressionCommunication machineryOmics technologiesIntercellular interactionsSpatial omics technologiesTumor microenvironmentB cellsSpatial dynamicsHuman tonsilsMacrophage stateSpatial effectsA Selective Review of Network Analysis Methods for Gene Expression Data
Li R, Yi H, Ma S. A Selective Review of Network Analysis Methods for Gene Expression Data. Methods In Molecular Biology 2025, 2880: 293-307. PMID: 39900765, DOI: 10.1007/978-1-0716-4276-4_14.Peer-Reviewed Original ResearchConceptsGene expression dataGene expression networksExpression dataDownstream analysisExpression networksGene expressionBiological processesGenesMolecular mechanismsBiological implicationsHigh-throughput profiling techniquesBiological findingsGlobal viewComplex interactionsProfiling techniquesRegulationA new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission
Sobkowiak B, Cudahy P, Chitwood M, Clark T, Colijn C, Grandjean L, Walter K, Crudu V, Cohen T. A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission. Genome Medicine 2025, 17: 8. PMID: 39871355, PMCID: PMC11771024, DOI: 10.1186/s13073-025-01430-y.Peer-Reviewed Original ResearchConceptsShort-read WGS dataWhole-genome sequencingStrain sequencesWGS dataMultiple strainsStrain proportionsMycobacterium tuberculosis populationMixed infectionGenome sequenceBioinformatics pipelineClustering allele frequenciesDownstream analysisAllele frequenciesEvidence of mixed infectionSequenceTuberculosis populationStrainIsolatesIn vitroTransmission clustersMixed samplesAllelesInfectionMycobacterium tuberculosis infectionPathogens
2024
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis
Liu T, Long W, Cao Z, Wang Y, He C, Zhang L, Strittmatter S, Zhao H. CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis. Briefings In Bioinformatics 2024, 26: bbae626. PMID: 39592241, PMCID: PMC11596696, DOI: 10.1093/bib/bbae626.Peer-Reviewed Original ResearchAutomating life science labs at the single-cell level through precise ultrasonic liquid sample ejection: PULSE
Zhang P, Tian Z, Jin K, Yang K, Collyer W, Rufo J, Upreti N, Dong X, Lee L, Huang T. Automating life science labs at the single-cell level through precise ultrasonic liquid sample ejection: PULSE. Microsystems & Nanoengineering 2024, 10: 172. PMID: 39567484, PMCID: PMC11579414, DOI: 10.1038/s41378-024-00798-y.Peer-Reviewed Original ResearchSingle-cell levelSingle cellsAutomated solutionPreserving cell integrityGenotype dataPhenotypic dataDownstream analysisBarcoding experimentsPrecision gatesBiomedical researchTiter platesBiocompatible mannerLife science labsDeterministic arraysBiological experimentsCell integritySpeed rangeBarcodingPulsePulse platformAutomation technologyDynamic analysisCellsSDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original ResearchSemi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies
Shyr D, Dey R, Li X, Zhou H, Boerwinkle E, Buyske S, Daly M, Gibbs R, Hall I, Matise T, Reeves C, Stitziel N, Zody M, Neale B, Lin X. Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies. American Journal Of Human Genetics 2024, 111: 2129-2138. PMID: 39270648, PMCID: PMC11480788, DOI: 10.1016/j.ajhg.2024.08.018.Peer-Reviewed Original ResearchHardy-Weinberg equilibriumWhole-genome sequencing studiesWhole-genome sequencingHomogeneous ancestryWGS studiesDownstream analysisAssociation analysisPresence of population structureAncestry groupsGenetic ancestry groupsPopulation structureSequencing studiesSelf-reported raceGenetic researchQuality variantsAncestrySubsets of samplesProgram centersVariantsIncreasing diversityHeterogeneous sampleAncestralAssociationGeneticsSequenceHuman genetics and epigenetics of alcohol use disorder
Zhou H, Gelernter J. Human genetics and epigenetics of alcohol use disorder. Journal Of Clinical Investigation 2024, 134: e172885. PMID: 39145449, PMCID: PMC11324314, DOI: 10.1172/jci172885.Peer-Reviewed Original ResearchConceptsEpigenome-wide association studiesEWAS studiesPower of GWASTranscriptome-wide associationGenome-wide scanAlcohol use disorderWhole-genome sequencingDrug-gene interactionsSingle-cell sequencingAssociation studiesDownstream analysisHuman geneticsGenetic variantsEpigenetic risk factorsVariant functionEpigenetic changesSpatial transcriptomicsUse disorderEpigeneticsDisease risk predictionGenetic correlationsDiversity of populationGeneticsComplex etiologyEnvironmental factorsA method for sampling the living wood microbiome
Arnold W, Gewirtzman J, Raymond P, Bradford M, Butler C, Peccia J. A method for sampling the living wood microbiome. Methods In Ecology And Evolution 2024, 15: 1084-1096. DOI: 10.1111/2041-210x.14311.Peer-Reviewed Original ResearchGlobal microbial ecologyExtraction of nucleic acidsGlobal biogeochemical cyclesTree microbiomeUnique taxaEndophytic microbiomeDiverse taxaDownstream analysisTree speciesMicrobiomeBiogeochemical cyclesMicrobial lifeTaxaDiverse environmentsNucleic acidsMicrobial analysisEcosystem healthSpeciesMethane cycleTreesEndophytesWoodNicheLeavesEcosystemPhotosensitive Nanoprobes for Rapid High Purity Isolation and Size‐Specific Enrichment of Synthetic and Extracellular Vesicle Subpopulations
Weerakkody J, Tseng T, Topper M, Thoduvayil S, Radhakrishnan A, Pincet F, Kyriakides T, Gunasekara R, Ramakrishnan S. Photosensitive Nanoprobes for Rapid High Purity Isolation and Size‐Specific Enrichment of Synthetic and Extracellular Vesicle Subpopulations. Advanced Functional Materials 2024, 34 PMID: 39372670, PMCID: PMC11452007, DOI: 10.1002/adfm.202400390.Peer-Reviewed Original ResearchExtracellular vesicle subpopulationsVesicle subpopulationsIsolation of vesiclesPurity extracellular vesiclesRelease of vesiclesAnalysis of nucleic acidsNear-native formLarge-scale isolationLipid nanoprobesDownstream analysisPurity isolationEfficient isolationVesiclesSynthetic vesiclesNucleic acidsExtracellular vesiclesIsolation methodIsolatesBiomarker discoveryExposure to lightSubpopulationsEnrichmentProteinComplex biological mediaCleavageMass Spectrometry-Compatible Elution Technique Enables an Improved Mucin-Selective Enrichment Strategy to Probe the Mucinome
Mahoney K, Chang V, Lucas T, Maruszko K, Malaker S. Mass Spectrometry-Compatible Elution Technique Enables an Improved Mucin-Selective Enrichment Strategy to Probe the Mucinome. Analytical Chemistry 2024, 96: 5242-5250. PMID: 38512228, PMCID: PMC12050071, DOI: 10.1021/acs.analchem.3c05762.Peer-Reviewed Original ResearchMucin-domain glycoproteinsO-glycopeptidesGlycopeptide signalsIn-gel digestionMass spectrometryElution conditionsSolid supportBinding moietyElution stepDownstream analysisO-glycosylationIn-gelBiological functionsElutionHuman serumEnrichment strategyCell linesMoietyEffective isolationSpectrometryCatalyticallyGlycoproteinSampling requirementsGlycopeptidesStcEPatient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning
Pak D, Liu M, Kim T, Liang L, Caballero A, Onofrey J, Ahn S, Xu Y, McKay R, Sun W, Gleason R, Duncan J. Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning. IEEE Transactions On Medical Imaging 2024, 43: 203-215. PMID: 37432807, PMCID: PMC10764002, DOI: 10.1109/tmi.2023.3294128.Peer-Reviewed Original ResearchConceptsFinite element analysisDeep learning methodsSpatial accuracyElement analysisDeep learningStress estimationLearning methodsSimulation accuracyDeployment simulationHigh spatial accuracyThin structuresMesh generationVolumetric meshingDeformation energyGeometry modelingVolumetric meshMesh qualityElement qualitySimultaneous optimizationMain noveltyBiomechanics studiesMeshModeling characteristicsAccuracyDownstream analysis
2023
Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available
Dadashkarimi J, Karbasi A, Liang Q, Rosenblatt M, Noble S, Foster M, Rodriguez R, Adkinson B, Ye J, Sun H, Camp C, Farruggia M, Tejavibulya L, Dai W, Jiang R, Pollatou A, Scheinost D. Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available. Medical Image Analysis 2023, 88: 102864. PMID: 37352650, PMCID: PMC10526726, DOI: 10.1016/j.media.2023.102864.Peer-Reviewed Original ResearchConceptsDifferent atlasesRaw data accessWeb applicationData accessOpen source dataSource codePatient privacyOptimal transportRaw dataStorage concernsLarge-scale data collection effortsOriginal counterpartsExtensive setData collection effortsProcessing effortPredictive modelNeuroimaging dataDownstream analysisPrivacyAtlasesCollection effortsComputationalTime seriesDatasetConnectomePCSK6 and Survival in Idiopathic Pulmonary Fibrosis
Oldham J, Allen R, Lorenzo-Salazar J, Molyneaux P, Ma S, Joseph C, Kim J, Guillen-Guio B, Hernández-Beeftink T, Kropski J, Huang Y, Lee C, Adegunsoye A, Pugashetti J, Linderholm A, Vo V, Strek M, Jou J, Muñoz-Barrera A, Rubio-Rodriguez L, Hubbard R, Hirani N, Whyte M, Hart S, Nicholson A, Lancaster L, Parfrey H, Rassl D, Wallace W, Valenzi E, Zhang Y, Mychaleckyj J, Stockwell A, Kaminski N, Wolters P, Molina-Molina M, Banovich N, Fahy W, Martinez F, Hall I, Tobin M, Maher T, Blackwell T, Yaspan B, Jenkins R, Flores C, Wain L, Noth I. PCSK6 and Survival in Idiopathic Pulmonary Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2023, 207: 1515-1524. PMID: 36780644, PMCID: PMC10263132, DOI: 10.1164/rccm.202205-0845oc.Peer-Reviewed Original ResearchConceptsGenome-wide significanceTransplantation-free survivalIdiopathic pulmonary fibrosisStage IIPF survivalDownstream analysisPulmonary fibrosisIPF progressionWide association studyPeripheral blood gene expressionProportional hazards regressionStage II casesLimited treatment optionsStage I casesBlood gene expressionGene expressionAssociation studiesMolecular determinantsHazards regressionTreatment optionsPlasma concentrationsLung parenchymaConsistent effect directionMolecular driversProteinConnectome-based machine learning models are vulnerable to subtle data manipulations
Rosenblatt M, Rodriguez R, Westwater M, Dai W, Horien C, Greene A, Constable R, Noble S, Scheinost D. Connectome-based machine learning models are vulnerable to subtle data manipulations. Patterns 2023, 4: 100756. PMID: 37521052, PMCID: PMC10382940, DOI: 10.1016/j.patter.2023.100756.Peer-Reviewed Original ResearchData manipulationNoise attacksPrediction performanceMachine learning modelsManipulated dataLearning modelHigh trustworthinessConnectome dataTrustworthinessAttacksModel performancePredictive modelDownstream analysisPerformanceAcademic researchMachineRobustnessModelConnectomeConnectome-based modelsFunctional connectomeManipulation
2022
Translator: A Transfer Learning Approach to Facilitate Single-Cell ATAC-Seq Data Analysis from Reference Dataset
Xu S, Skarica M, Hwang A, Dai Y, Lee C, Girgenti MJ, Zhang J. Translator: A Transfer Learning Approach to Facilitate Single-Cell ATAC-Seq Data Analysis from Reference Dataset. Journal Of Computational Biology 2022, 29: 619-633. PMID: 35584295, PMCID: PMC9464368, DOI: 10.1089/cmb.2021.0596.Peer-Reviewed Original ResearchConceptsGraphic Processing Units ParallelismComplex feature interactionsDeep learning frameworkFree software packageFeature interactionsUltra-high dimensionalityLearning frameworkSoftware packageComputational efficiencySeq data analysisScATAC-seq dataDatasetReference datasetReference dataData analysisDownstream analysisCell representationRepresentationParallelismLow signalTranslatorsClusteringDimensionalityNoise ratioNonlinear relationshipNormalizing and denoising protein expression data from droplet-based single cell profiling
Mulè M, Martins A, Tsang J. Normalizing and denoising protein expression data from droplet-based single cell profiling. Nature Communications 2022, 13: 2099. PMID: 35440536, PMCID: PMC9018908, DOI: 10.1038/s41467-022-29356-8.Peer-Reviewed Original ResearchConceptsProtein expression dataSingle-cell profiling methodsExpression dataSingle-cell profilingOligo-conjugated antibodiesTechnical noiseProtein populationCITE-seqCellular heterogeneityComprehensive dissectionDownstream analysisCell profilingDSBsSingle cellsProtein levelsProtein expressionCell populationsOpen-source R packageProfiling methodProtein countsEmpty dropletsR packageComputational analysisCellsBiological variationDissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain
Marsh SE, Walker AJ, Kamath T, Dissing-Olesen L, Hammond TR, de Soysa TY, Young AMH, Murphy S, Abdulraouf A, Nadaf N, Dufort C, Walker AC, Lucca LE, Kozareva V, Vanderburg C, Hong S, Bulstrode H, Hutchinson PJ, Gaffney DJ, Hafler DA, Franklin RJM, Macosko EZ, Stevens B. Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain. Nature Neuroscience 2022, 25: 306-316. PMID: 35260865, PMCID: PMC11645269, DOI: 10.1038/s41593-022-01022-8.Peer-Reviewed Original ResearchConceptsSingle-cell sequencing experimentsCell type diversitySingle-cell sequencingRNA-sequencing datasetsGene expression changesGene expression signaturesVivo gene expressionTranscriptional profilesGene expressionExpression changesSequencing experimentsGlial signaturesDownstream analysisExpression signaturesTissue typesSingle cell suspensionsOptimal cell yieldIntact tissueHuman tissuesCell yieldEnzymatic dissociationHuman samplesTissue digestionPostmortem human samplesTissue
2021
Privacy-preserving genotype imputation in a trusted execution environment
Dokmai N, Kockan C, Zhu K, Wang X, Sahinalp S, Cho H. Privacy-preserving genotype imputation in a trusted execution environment. Cell Systems 2021, 12: 983-993.e7. PMID: 34450045, PMCID: PMC8542641, DOI: 10.1016/j.cels.2021.08.001.Peer-Reviewed Original ResearchConceptsTrusted Execution EnvironmentExecution environmentHardware-based solutionsSide-channel attacksIntel SGXEnhanced securityPrivacy concernsAnalysis servicesImputation ServerServer limitData resourcesImputation algorithmSGXServerImputation softwareGenomic data resourcesImputation accuracyGenotype imputationImputation strategiesServicesDownstream analysisScalabilityImputationEssential toolSecurity
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