Mercedeh Javanbakht Movassagh
Associate Research ScientistDownloadHi-Res Photo
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Appointments
Neurosurgery
Primary
Contact Info
About
Titles
Associate Research Scientist
Biography
Dr. Movassagh is an Associate Research Scientist with a focus on infectious disease computational biology and bioinformatics, at Yale School of Medicine. She got her BS from University of Virginia, Masters in Biochemistry and Bioinformatics from George Washington University and PhD from University of Massachusetts Medical School in Computational Biology and Bioinformatics. Her post-doctoral fellow ship was at Harvard School of Public Health and Dana Farber Cancer Institute departments of Biostatistics and Data science respectively with a focus on infectious disease computational biology and global public health in under resourced communities and countries. She is also interested in investigating the role of pathogens in development of diseases in neonates, and children such as but not limited to neonatal sepsis, post infectious hydrocephalus, Burkitt Lymphoma and diarrhea using computational biology and bioinformatics analysis and methods development.
Appointments
Neurosurgery
Associate Research ScientistPrimary
Other Departments & Organizations
- Neurosurgery
- Schiff Lab
- Slayman House Affiliates
Education & Training
- MS
- George Washington University, Biochemistry and Bioinformatics
- PhD
- University of Massachusetts Medical School , Computational Biology and Bioinformatics
- BS
- University of Virginia, Biology
Research
Overview
Detailed expertise and methods development:
Development of computational and statistical methods for infectious disease genomics and sequencing data analysis (mirTarRnaSeq, mbQTL, VDJdive, RNA2DNAlign and PathSeeker).
Machine learning (Random Forest, SVMs, Topic Models, Clustering, Elastic Nets, Regressions, etc).
Next generation sequencing (NGS) analysis (RNA, microRNA (miRNA), whole genome sequencing (WGS), microbiome sequencing (16s rRNA) and T cell receptor (TCR) single cell sequencing.
Population genetics and ancestry analysis for WGS.
Genome wide association studies (GWAS).
Scalable processing of sparse sequencing data such as microbiome data.
Detailed Research interests:
Infectious disease (microbial, viral, parasitic and fungal), neonatal sepsis, hydrocephalus, RNAs and ncRNAs, computational biology, metagenomics, bioinformatics and biostatistics, machine learning, tropical medicine, global public health, and pathogenic cancers such as Burkitt Lymphoma, and interplay of host and human microbiome.
Medical Subject Headings (MeSH)
Bacteria; Biostatistics; Blood-Borne Pathogens; Computational Biology; Democratic Republic of the Congo; Global Health; Haiti; Host Microbial Interactions; Host-Parasite Interactions; Machine Learning; Malaria; Malaria, Cerebral; Malaria, Falciparum; Metagenomics; Parasites; Public Health; Tanzania; Trypanosoma; Uganda; Vietnam; Viruses
ORCID
0000-0001-7690-0230- View Lab Website
Schiff Lab
Research at a Glance
Yale Co-Authors
Frequent collaborators of Mercedeh Javanbakht Movassagh's published research.
Publications Timeline
A big-picture view of Mercedeh Javanbakht Movassagh's research output by year.
Research Interests
Research topics Mercedeh Javanbakht Movassagh is interested in exploring.
Steven Schiff, MD, PhD, FACS
Joseph N Paulson, PhD
Ronald Mulondo
Andrew J Whalen
22Publications
299Citations
Uganda
Computational Biology
Bacteria
Publications
2023
mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
Movassagh M, Schiff S, Paulson J. mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation. Bioinformatics 2023, 39: btad565. PMID: 37707523, PMCID: PMC10516520, DOI: 10.1093/bioinformatics/btad565.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSingle nucleotide variationsRNA sequencingMicrobial abundance dataQuantitative trait lociSingle nucleotide polymorphism dataRibosomal RNA sequencingField of genomicsWhole-genome sequencingEvidence of interplayMutational profileTrait lociMicrobial communitiesMicrobial abundancePolymorphism dataMicrobial populationsGenome sequencingAbundance dataFirst R packageHuman geneticsBioconductor packageGenetic variantsMicrobiome dataSequencingR packageAbundancePaenibacillus spp infection among infants with postinfectious hydrocephalus in Uganda: an observational case-control study
Morton S, Hehnly C, Burgoine K, Ssentongo P, Ericson J, Kumar M, Hagmann C, Fronterre C, Smith J, Movassagh M, Streck N, Bebell L, Bazira J, Kumbakumba E, Bajunirwe F, Mulondo R, Mbabazi-Kabachelor E, Nsubuga B, Natukwatsa D, Nalule E, Magombe J, Erickson T, Ngonzi J, Ochora M, Olupot-Olupot P, Onen J, Ssenyonga P, Mugamba J, Warf B, Kulkarni A, Lane J, Whalen A, Zhang L, Sheldon K, Meier F, Kiwanuka J, Broach J, Paulson J, Schiff S. Paenibacillus spp infection among infants with postinfectious hydrocephalus in Uganda: an observational case-control study. The Lancet Microbe 2023, 4: e601-e611. PMID: 37348522, PMCID: PMC10529524, DOI: 10.1016/s2666-5247(23)00106-4.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMother-newborn pairsPostinfectious hydrocephalusCerebrospinal fluidNeonatal sepsisSpp infectionUgandan infantsMaternal bloodObservational case-control studyHospital OfficeInfant's cerebrospinal fluidBurden of morbidityCase-control studyRoute of infectionSubset of participantsMaternal feverCranial ultrasoundNeonatal infectionSepsis cohortOptimise treatmentTransplacental transmissionCord bloodObservational studyPlacental samplesSepsisHydrocephalusNeonatal Paenibacilliosis: Paenibacillus Infection as a Novel Cause of Sepsis in Term Neonates With High Risk of Sequelae in Uganda
Ericson J, Burgoine K, Kumbakumba E, Ochora M, Hehnly C, Bajunirwe F, Bazira J, Fronterre C, Hagmann C, Kulkarni A, Kumar M, Magombe J, Mbabazi-Kabachelor E, Morton S, Movassagh M, Mugamba J, Mulondo R, Natukwatsa D, Kaaya B, Olupot-Olupot P, Onen J, Sheldon K, Smith J, Ssentongo P, Ssenyonga P, Warf B, Wegoye E, Zhang L, Kiwanuka J, Paulson J, Broach J, Schiff S. Neonatal Paenibacilliosis: Paenibacillus Infection as a Novel Cause of Sepsis in Term Neonates With High Risk of Sequelae in Uganda. Clinical Infectious Diseases 2023, 77: 768-775. PMID: 37279589, PMCID: PMC10495130, DOI: 10.1093/cid/ciad337.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsNeonatal sepsisPostinfectious hydrocephalusCerebrospinal fluidSigns of sepsisFull-term neonatesOptimal antibiotic treatmentUgandan referral hospitalQuantitative polymerase chain reactionNeonatal characteristicsClinical sepsisTerm neonatesUnderdiagnosed causeAntibiotic choiceMedian ageReferral hospitalUgandan hospitalNeurodevelopmental impairmentAdverse outcomesSpecimen typesAntibiotic treatmentPolymerase chain reactionClinical signsUnusual pathogensSepsisHigh risk
2022
1328. Paenibacillosis: An Emerging Cause of Neonatal Sepsis and Postinfectious Hydrocephalus
Ericson J, Burgoine K, Hehnly C, Kumbakumba E, Ochora M, Bajunirwe F, Bazira J, Fronterre C, Hagmann C, Kulkarni A, Kumar M, Magombe J, Mbabazi-Kabachelor E, Morton S, Movassagh M, Mugamba J, Mulondo R, Muwanguzi A, Natukwatsa D, Kaaya B, Olupot-Olupot P, Onen J, Sheldon K, Smith J, Ssentongo P, Ssenyonga P, Warf B, Wegoye E, Zhang L, Broach J, Kiwanuka J, Paulson J, Schiff S. 1328. Paenibacillosis: An Emerging Cause of Neonatal Sepsis and Postinfectious Hydrocephalus. Open Forum Infectious Diseases 2022, 9: ofac492.1158. PMCID: PMC9752957, DOI: 10.1093/ofid/ofac492.1158.Peer-Reviewed Original ResearchAltmetricConceptsNeonatal sepsisPostinfectious hydrocephalusPolymerase chain reactionSigns of sepsisCommon presenting signsAntibiotic susceptibility testingQuantitative polymerase chain reactionUnderrecognized causeIntravenous ampicillinMedian agePresenting signUgandan hospitalNeurodevelopmental impairmentBest regimenNeonatal mortalityRRNA sequencingAdverse outcomesBirth characteristicsMost neonatesOptimal treatmentClinical signsSepsisBeta-lactamase genesCerebrospinal fluidAdditional survivorB.3 Activated gene pathways in post-infectious hydrocephalus (PIH):: proteogenomics and the PIH expressome
Isaacs A, Morton S, Movassagh M, Zhang Q, Hehnly C, Zhang L, Morales D, Townsend R, Limbrick D, Paulson J, Schiff S. B.3 Activated gene pathways in post-infectious hydrocephalus (PIH):: proteogenomics and the PIH expressome. Canadian Journal Of Neurological Sciences / Journal Canadien Des Sciences Neurologiques 2022, 49: s5-s5. DOI: 10.1017/cjn.2022.98.Peer-Reviewed Original ResearchAltmetricConceptsProteins/genesGene pathwaysDifferential expressionIntegration of proteomicsGene networksOxidative stressGene setsProteogenomicsMolecular mechanismsPaenibacillus sppMolecular identificationPost-infectious hydrocephalusGenesDNA sequencingNovel insightsPathogenetic bacteriaProteomicsRNAseqViral pathogensPathwayHost responseExpressionExpressomeCerebrospinal fluidImmune systemDisentangling the genetic basis of rhizosphere microbiome assembly in tomato
Oyserman B, Flores S, Griffioen T, Pan X, van der Wijk E, Pronk L, Lokhorst W, Nurfikari A, Paulson J, Movassagh M, Stopnisek N, Kupczok A, Cordovez V, Carrión V, Ligterink W, Snoek B, Medema M, Raaijmakers J. Disentangling the genetic basis of rhizosphere microbiome assembly in tomato. Nature Communications 2022, 13: 3228. PMID: 35710629, PMCID: PMC9203511, DOI: 10.1038/s41467-022-30849-9.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsMicrobiome assemblyGenetic basisRhizosphere microbiome assemblyMetagenome-assembled genomesGene content analysisQuantitative trait lociDomestication sweepsDomesticated tomatoRhizosphere microbiomePutative plantPlant geneticsTrait lociBacterial genesPlant growthHybrid populationsQuantitative traitsBreeding programsMbp regionGenetic variation associatesPlant polysaccharidesDifferential recruitmentTomatoStreptomycesTraitsPivotal rolemirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis
Movassagh M, Morton S, Hehnly C, Smith J, Doan T, Irizarry R, Broach J, Schiff S, Bailey J, Paulson J. mirTarRnaSeq: An R/Bioconductor Statistical Package for miRNA-mRNA Target Identification and Interaction Analysis. BMC Genomics 2022, 23: 439. PMID: 35698050, PMCID: PMC9191533, DOI: 10.1186/s12864-022-08558-w.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSARS-CoV-2 infectionLung epithelial cellsEpithelial cellsHuman lung epithelial cellsSARS-CoV-2NK cellsStatistical PackageEBV miRNAsT cellsImmune pathwaysB cellsClinical relevanceSample cohortCD34 cellsStomach adenocarcinomaEndothelial cellsTime pointsInfectionCOVID-19CellsCD4AdenocarcinomaPatientsCD19Cytokines
2021
C.3 Activated Gene Pathways in Post-Infectious Hydrocephalus (PIH): Proteogenomics and the PIH Expressome
Isaacs A, Morton S, Movassagh M, Zhang Q, Hehnly C, Zhang L, Morales D, Townsend R, Limbrick D, Paulson J, Schiff S. C.3 Activated Gene Pathways in Post-Infectious Hydrocephalus (PIH): Proteogenomics and the PIH Expressome. Canadian Journal Of Neurological Sciences / Journal Canadien Des Sciences Neurologiques 2021, 48: s18-s19. DOI: 10.1017/cjn.2021.279.Peer-Reviewed Original ResearchConceptsProteins/genesGene pathwaysDifferential expressionIntegration of proteomicsGene networksOxidative stressGene setsProteogenomicsMolecular mechanismsPaenibacillus sppMolecular identificationPost-infectious hydrocephalusGenesDNA sequencingNovel insightsPathogenetic bacteriaProteomicsRNAseqViral pathogensPathwayHost responseExpressionExpressomeCerebrospinal fluidImmune systemSCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data
Prashant N, Alomran N, Chen Y, Liu H, Bousounis P, Movassagh M, Edwards N, Horvath A. SCReadCounts: estimation of cell-level SNVs expression from scRNA-seq data. BMC Genomics 2021, 22: 689. PMID: 34551708, PMCID: PMC8459565, DOI: 10.1186/s12864-021-07974-8.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsSomatic mutationsNovel somatic mutationsBackgroundRecent studiesVariant allele fractionIntra-tumoral heterogeneityVariant allelesNeuroblastoma samplesCell-level expressionCancer studiesExpression signaturesAllele fractionRegions of KRASNormal cellsType of studySmall proportionCellsExpressionVaginal microbiome topic modeling of laboring Ugandan women with and without fever
Movassagh M, Bebell L, Burgoine K, Hehnly C, Zhang L, Moran K, Sheldon K, Sinnar S, Mbabazi-Kabachelor E, Kumbakumba E, Bazira J, Ochora M, Mulondo R, Nsubuga B, Weeks A, Gladstone M, Olupot-Olupot P, Ngonzi J, Roberts D, Meier F, Irizarry R, Broach J, Schiff S, Paulson J. Vaginal microbiome topic modeling of laboring Ugandan women with and without fever. Npj Biofilms And Microbiomes 2021, 7: 75. PMID: 34508087, PMCID: PMC8433417, DOI: 10.1038/s41522-021-00244-1.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsIntrapartum feverClinical variablesHigh prevalenceVaginal microbiomeUgandan womenLonger labour durationMaternal clinical featuresYoung maternal ageDuration of pregnancyOnset of laborMicrobial communitiesVaginal microbial communitiesAfebrile mothersFebrile mothersPeripartum courseMaternal feverNeonatal outcomesLabor durationClinical featuresMaternal ageVaginal microbesFeverOutcome riskVeillonella genusMicrobiome influences
Academic Achievements & Community Involvement
honor 2023 Hydrocephalus Association Innovator Award
International AwardHydrocephalus Association and Rudi Schulte Research InstituteDetails11/01/2023