Gwênlyn Glusman, PhD

Principal Scientist

Dr. Gwênlyn Glusman is a Principal Scientist at the Institute for Systems Biology. She received her PhD in computational genomics from the Weizmann Institute of Sciences. Her graduate work focused on the genomic structure and evolution of the olfactory receptor gene superfamily.

Glusman uses computational approaches to investigate genome structure, function and evolution, and to study disease and wellness genetics. She has developed novel algorithms for gene discovery, for the interpretation of large-scale transcriptomic and genomic data, for family genomics, and for analysis, modeling and visualization of complex data.

PhD, Biology, Weizmann Institute, 2002

Computational Genomics and Transcriptomics

Qin, G., Narsinh, K., Wei, Q., Roach, J. C., Joshi, A., Goetz, S. L., Moxon, S. T., Brush, M. H., Xu, C., Yao, Y., Glen, A. K., Morris, E. D., Ralevski, A., Roper, R., Belhu, B., Zhang, Y., Shmulevich, I., Hadlock, J., & Glusman, G. (2024). Generating Biomedical Knowledge Graphs from Knowledge Bases, Registries, and Multiomic Data. bioRxiv. https://doi.org/10.1101/2024.11.14.623648 Cite Download

Don, J., Schork, A. J., Glusman, G., Rappaport, N., Cummings, S. R., Duggan, D., Raju, A., Hellberg, K.-L. G., Gunn, S., Monti, S., Perls, T., Lapidus, J., Goetz, L. H., Sebastiani, P., & Schork, N. J. (2024). The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank. GeroScience. https://doi.org/10.1007/s11357-024-01107-1 Cite Download

Fecho, K., Bizon, C., Issabekova, T., Moxon, S., Thessen, A. E., Abdollahi, S., Baranzini, S. E., Belhu, B., Byrd, W. E., Chung, L., Crouse, A., Duby, M. P., Ferguson, S., Foksinska, A., Forero, L., Friedman, J., Gardner, V., Glusman, G., Hadlock, J., … Biomedical Data Translator Consortium. (2023). An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges. Journal of Clinical and Translational Science, 7(1), e214. https://doi.org/10.1017/cts.2023.619 Cite Download

Roach, J. C., Rapozo, M. K., Hara, J., Glusman, G., Lovejoy, J., Shankle, W. R., Hood, L., & COCOA Consortium: (2023). A Remotely Coached Multimodal Lifestyle Intervention for Alzheimer’s Disease Ameliorates Functional and Cognitive Outcomes. Journal of Alzheimer’s Disease: JAD, 96(2), 591–607. https://doi.org/10.3233/JAD-230403 Cite

Pflieger, L., Watanabe, K., Robinson, M., Glusman, G., Lapidus, J., Fiehn, O., Moritz, R., & Rappaport, N. (2023). PROSPECTIVE MULTI-OMIC ANALYSIS OF HUMAN LONGEVITY COHORTS IDENTIFIES ANALYTE NETWORKS ASSOCIATED WITH LONGEVITY. Innovation in Aging, 7(Suppl 1), 691–692. https://doi.org/10.1093/geroni/igad104.2245 Cite Download

Watanabe, K., Wilmanski, T., Baloni, P., Robinson, M., Garcia, G. G., Hoopmann, M. R., Midha, M. K., Baxter, D. H., Maes, M., Morrone, S. R., Crebs, K. M., Kapil, C., Kusebauch, U., Wiedrick, J., Lapidus, J., Pflieger, L., Lausted, C., Roach, J. C., Glusman, G., … Rappaport, N. (2023). Lifespan-extending interventions induce consistent patterns of fatty acid oxidation in mouse livers. Communications Biology, 6(1), 768. https://doi.org/10.1038/s42003-023-05128-y Cite

Watanabe, K., Wilmanski, T., Baloni, P., Robinson, M., Garcia, G. G., Hoopmann, M. R., Midha, M. K., Baxter, D. H., Maes, M., Morrone, S. R., Crebs, K. M., Kapil, C., Kusebauch, U., Wiedrick, J., Lapidus, J., Lovejoy, J. C., Magis, A. T., Lausted, C., Roach, J. C., … Rappaport, N. (2022). Systems-level patterns in biological processes are changed under prolongevity interventions and across biological age. medRxiv. https://doi.org/10.1101/2022.07.11.22277435 Cite Download

Unni, D. R., Moxon, S. A. T., Bada, M., Brush, M., Bruskiewich, R., Caufield, J. H., Clemons, P. A., Dancik, V., Dumontier, M., Fecho, K., Glusman, G., Hadlock, J. J., Harris, N. L., Joshi, A., Putman, T., Qin, G., Ramsey, S. A., Shefchek, K. A., Solbrig, H., … Biomedical Data Translator Consortium. (2022). Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science. Clinical and Translational Science, 15(8), 1848–1855. https://doi.org/10.1111/cts.13302 Cite Download

Robinson, M., Joshi, A., Vidyarthi, A., Maccoun, M., Rangavajjhala, S., & Glusman, G. (2022). Quality control of large genome datasets. HGG Advances, 3(3), 100123. https://doi.org/10.1016/j.xhgg.2022.100123 Cite Download

Roach, J. C., Edens, L., Markewych, D. R., Rapozo, M. K., Hara, J., Glusman, G., Funk, C., Bramen, J., Baloni, P., Shankle, W. R., & Hood, L. (2022). A multimodal intervention for Alzheimer’s disease results in multifaceted systemic effects reflected in blood and ameliorates functional and cognitive outcomes. medRxiv. https://doi.org/10.1101/2022.09.27.22280385 Cite Download

Fecho, K., Thessen, A. E., Baranzini, S. E., Bizon, C., Hadlock, J. J., Huang, S., Roper, R. T., Southall, N., Ta, C., Watkins, P. B., Williams, M. D., Xu, H., Byrd, W., Dančík, V., Duby, M. P., Dumontier, M., Glusman, G., Harris, N. L., Hinderer, E. W., … Biomedical Data Translator Consortium. (2022). Progress toward a universal biomedical data translator. Clinical and Translational Science. https://doi.org/10.1111/cts.13301 Cite

Corpas, M., Beck, S., Glusman, G., & Shabani, M. (2021). Editorial: Personal Genomes: Accessing, Sharing, and Interpretation. Frontiers in Genetics, 12, 687584. https://doi.org/10.3389/fgene.2021.687584 Cite Download

Wilmanski, T., Diener, C., Rappaport, N., Patwardhan, S., Wiedrick, J., Lapidus, J., Earls, J. C., Zimmer, A., Glusman, G., Robinson, M., Yurkovich, J. T., Kado, D. M., Cauley, J. A., Zmuda, J., Lane, N. E., Magis, A. T., Lovejoy, J. C., Hood, L., Gibbons, S. M., … Price, N. D. (2021). Gut microbiome pattern reflects healthy ageing and predicts survival in humans. Nature Metabolism, 3(2), 274–286. https://doi.org/10.1038/s42255-021-00348-0 Cite

Funk, C. C., Casella, A. M., Jung, S., Richards, M. A., Rodriguez, A., Shannon, P., Donovan-Maiye, R., Heavner, B., Chard, K., Xiao, Y., Glusman, G., Ertekin-Taner, N., Golde, T. E., Toga, A., Hood, L., Van Horn, J. D., Kesselman, C., Foster, I., Madduri, R., … Ament, S. A. (2020). Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types. Cell Reports, 32(7), 108029. https://doi.org/10.1016/j.celrep.2020.108029 Cite Download

Zhou, Y., Qin, S., Sun, M., Tang, L., Yan, X., Kim, T.-K., Caballero, J., Glusman, G., Brunkow, M. E., Soloski, M. J., Rebman, A. W., Scavarda, C., Cooper, D., Omenn, G. S., Moritz, R. L., Wormser, G. P., Price, N. D., Aucott, J. N., & Hood, L. (2019). Measurement of Organ-Specific and Acute-Phase Blood Protein Levels in Early Lyme Disease. Journal of Proteome Research. https://doi.org/10.1021/acs.jproteome.9b00569 Cite Download

Fecho, K., Ahalt, S. C., Arunachalam, S., Champion, J., Chute, C. G., Davis, S., Gersing, K., Glusman, G., Hadlock, J., Lee, J., Pfaff, E., Robinson, M., Sid, E., Ta, C., Xu, H., Zhu, R., Zhu, Q., Peden, D. B., & Biomedical Data Translator Consortium. (2019). Sex, obesity, diabetes, and exposure to particulate matter among patients with severe asthma: Scientific insights from a comparative analysis of open clinical data sources during a five-day hackathon. Journal of Biomedical Informatics, 100, 103325. https://doi.org/10.1016/j.jbi.2019.103325 Cite

Rubin, I. R., & Glusman, G. (2019). Opportunities and Challenges in Interpreting and Sharing Personal Genomes. Genes, 10(9). https://doi.org/10.3390/genes10090643 Cite Download

Ahalt, S. C., Chute, C. G., Fecho, K., Glusman, G., Hadlock, J., Taylor, C. O., Pfaff, E. R., Robinson, P. N., Solbrig, H., Ta, C., Tatonetti, N., Weng, C., & Biomedical Data Translator Consortium. (2019). Clinical Data: Sources and Types, Regulatory Constraints, Applications. Clinical and Translational Science. https://doi.org/10.1111/cts.12638 Cite Download

Wu, Z., Liu, W., Jin, X., Ji, H., Wang, H., Glusman, G., Robinson, M., Liu, L., Ruan, J., & Gao, S. (2019). NormExpression: An R Package to Normalize Gene Expression Data Using Evaluated Methods. Frontiers in Genetics, 10, 400. https://doi.org/10.3389/fgene.2019.00400 Cite Download

Knijnenburg, T. A., Vockley, J. G., Chambwe, N., Gibbs, D. L., Humphries, C., Huddleston, K. C., Klein, E., Kothiyal, P., Tasseff, R., Dhankani, V., Bodian, D. L., Wong, W. S. W., Glusman, G., Mauldin, D. E., Miller, M., Slagel, J., Elasady, S., Roach, J. C., Kramer, R., … Niederhuber, J. E. (2019). Genomic and molecular characterization of preterm birth. Proceedings of the National Academy of Sciences of the United States of America, 116(12), 5819–5827. https://doi.org/10.1073/pnas.1716314116 Cite Download

Madduri, R., Chard, K., D’Arcy, M., Jung, S. C., Rodriguez, A., Sulakhe, D., Deutsch, E., Funk, C., Heavner, B., Richards, M., Shannon, P., Glusman, G., Price, N., Kesselman, C., & Foster, I. (2019). Reproducible big data science: A case study in continuous FAIRness. PloS One, 14(4), e0213013. https://doi.org/10.1371/journal.pone.0213013 Cite Download

Goldmann, J. M., Wong, W. S. W., Pinelli, M., Farrah, T., Bodian, D., Stittrich, A. B., Glusman, G., Vissers, L. E. L. M., Hoischen, A., Roach, J. C., Vockley, J. G., Veltman, J. A., Solomon, B. D., Gilissen, C., & Niederhuber, J. E. (2018). Author Correction: Parent-of-origin-specific signatures of de novo mutations. Nature Genetics, 50(11), 1615. https://doi.org/10.1038/s41588-018-0226-5 Cite

Magis, A. T., Earls, J. C., Glusman, G., Omenn, G. S., Lovejoy, J. C., Price, N. D., & Hood, L. (2018). Reply to “Precision medicine in the clouds.” Nature Biotechnology, 36(8), 680–682. https://doi.org/10.1038/nbt.4211 Cite

Joesch-Cohen, L. M., Robinson, M., Jabbari, N., Lausted, C. G., & Glusman, G. (2018). Novel metrics for quantifying bacterial genome composition skews. BMC Genomics, 19(1), 528. https://doi.org/10.1186/s12864-018-4913-5 Cite

Trachana, K., Bargaje, R., Glusman, G., Price, N. D., Huang, S., & Hood, L. E. (2018). Taking Systems Medicine to Heart. Circulation Research, 122(9), 1276–1289. https://doi.org/10.1161/CIRCRESAHA.117.310999 Cite

Jabbari, N., Glusman, G., Joesch-Cohen, L. M., Reddy, P. J., Moritz, R. L., Hood, L., & Lausted, C. G. (2018). Whole genome sequence and comparative analysis of Borrelia burgdorferi MM1. PLOS ONE, 13(6), e0198135. https://doi.org/10.1371/journal.pone.0198135 Cite Download

Robinson, M., Hadlock, J., Yu, J., Khatamian, A., Aravkin, A. Y., Deutsch, E. W., Price, N. D., Huang, S., & Glusman, G. (2018). Fast and simple comparison of semi-structured data, with emphasis on electronic health records. BioRxiv, 293183. https://doi.org/10.1101/293183 Cite Download

Deutsch, E., Kramer, R., Ames, J., Bauman, A., Campbell, D. S., Chard, K., Clark, K., D’Arcy, M., Dinov, I., Donovan, R., Foster, I., Heavner, B. D., Hood, L. E., Kesselman, C., Madduri, R., Mi, H., Muruganujan, A., Pa, J., Price, N. D., … Glusman, G. (2018). BDQC: a general-purpose analytics tool for domain-blind validation of Big Data. BioRxiv, 258822. https://doi.org/10.1101/258822 Cite Download

Glusman, G., Mauldin, D. E., Hood, L. E., & Robinson, M. (2017). Ultrafast comparison of personal genomes. BioRxiv, 130807. https://doi.org/10.1101/130807 Cite Download

Glusman, G., Rose, P. W., Prlić, A., Dougherty, J., Duarte, J. M., Hoffman, A. S., Barton, G. J., Bendixen, E., Bergquist, T., Bock, C., Brunk, E., Buljan, M., Burley, S. K., Cai, B., Carter, H., Gao, J., Godzik, A., Heuer, M., Hicks, M., … Deutsch, E. W. (2017). Mapping genetic variations to three-dimensional protein structures to enhance variant interpretation: a proposed framework. Genome Medicine, 9(1), 113. https://doi.org/10.1186/s13073-017-0509-y Cite

Robinson, M., & Glusman, G. (2017). Genotype fingerprints enable fast and private comparison of genetic testing results for research and direct-to-consumer applications. BioRxiv, 208025. https://doi.org/10.1101/208025 Cite Download

Glusman, G., Mauldin, D. E., Hood, L. E., & Robinson, M. (2017). Ultrafast Comparison of Personal Genomes via Precomputed Genome Fingerprints. Frontiers in Genetics, 8, 136. https://doi.org/10.3389/fgene.2017.00136 Cite

Joesch-Cohen, L. M., & Glusman, G. (2017). Differences between the genomes of lymphoblastoid cell lines and blood-derived samples. Advances in Genomics and Genetics, 7, 1–9. https://doi.org/10.2147/AGG.S128824 Cite

Joesch-Cohen, L. M., Robinson, M., Jabbari, N., Lausted, C., & Glusman, G. (2017). Novel metrics for quantifying bacterial genome composition skews. BioRxiv, 176370. https://doi.org/10.1101/176370 Cite Download

Glusman, G. (2017). A Data-Rich Longitudinal Wellness Study for the Digital Age: Fixing a Broken Medical System Requires Data About Each Patient. IEEE Pulse, 8(4), 11–14. https://doi.org/10.1109/MPUL.2016.2647038 Cite

Price, N. D., Magis, A. T., Earls, J. C., Glusman, G., Levy, R., Lausted, C., McDonald, D. T., Kusebauch, U., Moss, C. L., Zhou, Y., Qin, S., Moritz, R. L., Brogaard, K., Omenn, G. S., Lovejoy, J. C., & Hood, L. (2017). A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nature Biotechnology. https://doi.org/10.1038/nbt.3870 Cite

Hu, H., Petousi, N., Glusman, G., Yu, Y., Bohlender, R., Tashi, T., Downie, J. M., Roach, J. C., Cole, A. M., Lorenzo, F. R., Rogers, A. R., Brunkow, M. E., Cavalleri, G., Hood, L., Alpatty, S. M., Prchal, J. T., Jorde, L. B., Robbins, P. A., Simonson, T. S., & Huff, C. D. (2017). Evolutionary history of Tibetans inferred from whole-genome sequencing. PLoS Genetics, 13(4), e1006675. https://doi.org/10.1371/journal.pgen.1006675 Cite

McDonald, D., Glusman, G., & Price, N. D. (2016). Personalized nutrition through big data. Nature Biotechnology, 34(2), 152–154. https://doi.org/10.1038/nbt.3476 Cite

Stittrich, A. B., Ashworth, J., Shi, M., Robinson, M., Mauldin, D., Brunkow, M. E., Biswas, S., Kim, J.-M., Kwon, K.-S., Jung, J. U., Galas, D., Serikawa, K., Duerr, R. H., Guthery, S. L., Peschon, J., Hood, L., Roach, J. C., & Glusman, G. (2016). Genomic architecture of inflammatory bowel disease in five families with multiple affected individuals. Human Genome Variation, 3, 15060. https://doi.org/10.1038/hgv.2015.60 Cite

Goldmann, J. M., Wong, W. S. W., Pinelli, M., Farrah, T., Bodian, D., Stittrich, A. B., Glusman, G., Vissers, L. E. L. M., Hoischen, A., Roach, J. C., Vockley, J. G., Veltman, J. A., Solomon, B. D., Gilissen, C., & Niederhuber, J. E. (2016). Parent-of-origin-specific signatures of de novo mutations. Nature Genetics. https://doi.org/10.1038/ng.3597 Cite

Qin, S., Zhou, Y., Gray, L., Kusebauch, U., McEvoy, L., Antoine, D. J., Hampson, L., Park, K. B., Campbell, D., Caballero, J., Glusman, G., Yan, X., Kim, T.-K., Yuan, Y., Wang, K., Rowen, L., Moritz, R. L., Omenn, G. S., Pirmohamed, M., & Hood, L. (2016). Identification of Organ-Enriched Protein Biomarkers of Acute Liver Injury by Targeted Quantitative Proteomics of Blood in Acetaminophen- and Carbon-Tetrachloride-Treated Mouse Models and Acetaminophen Overdose Patients. Journal of Proteome Research. https://doi.org/10.1021/acs.jproteome.6b00547 Cite

Dinov, I. D., Heavner, B., Tang, M., Glusman, G., Chard, K., Darcy, M., Madduri, R., Pa, J., Spino, C., Kesselman, C., Foster, I., Deutsch, E. W., Price, N. D., Van Horn, J. D., Ames, J., Clark, K., Hood, L., Hampstead, B. M., Dauer, W., & Toga, A. W. (2016). Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations. PloS One, 11(8), e0157077. https://doi.org/10.1371/journal.pone.0157077 Cite

Lalli, M. A., Bettcher, B. M., Arcila, M. L., Garcia, G., Guzman, C., Madrigal, L., Ramirez, L., Acosta-Uribe, J., Baena, A., Wojta, K. J., Coppola, G., Fitch, R., de Both, M. D., Huentelman, M. J., Reiman, E. M., Brunkow, M. E., Glusman, G., Roach, J. C., Kao, A. W., … Kosik, K. S. (2015). Whole-genome sequencing suggests a chemokine gene cluster that modifies age at onset in familial Alzheimer’s disease. Molecular Psychiatry, 20, 1294–1300. https://doi.org/10.1038/mp.2015.131 Cite

Toga, A. W., Foster, I., Kesselman, C., Madduri, R., Chard, K., Deutsch, E. W., Price, N. D., Glusman, G., Heavner, B. D., Dinov, I. D., Ames, J., Van Horn, J., Kramer, R., & Hood, L. (2015). Big biomedical data as the key resource for discovery science. Journal of the American Medical Informatics Association : JAMIA, 22(6), 1126–1131. https://doi.org/10.1093/jamia/ocv077 Cite

Meester, J. A., Southgate, L., Stittrich, A. B., Venselaar, H., Beekmans, S. J., den Hollander, N., Bijlsma, E. K., Helderman-van den Enden, A., Verheij, J. B., Glusman, G., Roach, J. C., Lehman, A., Patel, M. S., de Vries, B. B., Ruivenkamp, C., Itin, P., Prescott, K., Clarke, S., Trembath, R., … Wuyts, W. (2015). Heterozygous Loss-of-Function Mutations in DLL4 Cause Adams-Oliver Syndrome. American Journal of Human Genetics, 97, 475–482. https://doi.org/10.1016/j.ajhg.2015.07.015 Cite

He, Y., Zeng, K., Zhang, X., Chen, Q., Wu, J., Li, H., Zhou, Y., Glusman, G., Roach, J., Etheridge, A., Qing, S., Tian, Q., Lee, I., Tian, X., Wang, X., Wu, Z., Hood, L., Ding, Y., & Wang, K. (2015). A gain-of-function mutation in TRPV3 causes focal palmoplantar keratoderma in a Chinese family. The Journal of Investigative Dermatology, 135(3), 907–909. https://doi.org/10.1038/jid.2014.429 Cite

Viollet, L., Glusman, G., Murphy, K. J., Newcomb, T. M., Reyna, S. P., Sweney, M., Nelson, B., Andermann, F., Andermann, E., Acsadi, G., Barbano, R. L., Brown, C., Brunkow, M. E., Chugani, H. T., Cheyette, S. R., Collins, A., DeBrosse, S. D., Galas, D., Friedman, J., … Swoboda, K. J. (2015). Alternating Hemiplegia of Childhood: Retrospective Genetic Study and Genotype-Phenotype Correlations in 187 Subjects from the US AHCF Registry. PLoS One, 10, e0127045. https://doi.org/10.1371/journal.pone.0127045 Cite

Ament, S. A., Szelinger, S., Glusman, G., Ashworth, J., Hou, L., Akula, N., Shekhtman, T., Badner, J. A., Brunkow, M. E., Mauldin, D. E., Stittrich, A.-B., Rouleau, K., Detera-Wadleigh, S. D., Nurnberger, J. I. J., Edenberg, H. J., Gershon, E. S., Schork, N., Price, N. D., Gelinas, R., … Roach, J. C. (2015). Rare variants in neuronal excitability genes influence risk for bipolar disorder. Proceedings of the National Academy of Sciences of the United States of America, 112(11), 3576–3581. https://doi.org/10.1073/pnas.1424958112 Cite

Glusman, G., Severson, A., Dhankani, V., Robinson, M., Farrah, T., Mauldin, D. E., Stittrich, A. B., Ament, S. A., Roach, J. C., Brunkow, M. E., Bodian, D. L., Vockley, J. G., Shmulevich, I., Niederhuber, J. E., & Hood, L. (2015). Identification of copy number variants in whole-genome data using Reference Coverage Profiles. Frontiers in Genetics, 6, 45. Cite