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Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE.

Science advances

Phongpreecha T, Gajera CR, Liu CC, Vijayaragavan K, Chang AL, Becker M, Fallahzadeh R, Fernandez R, Postupna N, Sherfield E, Tebaykin D, Latimer C, Shively CA, Register TC, Craft S, Montine KS, Fox EJ, Poston KL, Keene CD, Angelo M, Bendall SC, Aghaeepour N, Montine TJ.
PMID: 34910503
Sci Adv. 2021 Dec 17;7(51):eabk0473. doi: 10.1126/sciadv.abk0473. Epub 2021 Dec 15.

[Figure: see text].

Cite
Phongpreecha T, Gajera CR, Liu CC, et al. Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE. Sci Adv. 2021;7(51):eabk0473doi: 10.1126/sciadv.abk0473.
Phongpreecha, T., Gajera, C. R., Liu, C. C., Vijayaragavan, K., Chang, A. L., Becker, M., Fallahzadeh, R., Fernandez, R., Postupna, N., Sherfield, E., Tebaykin, D., Latimer, C., Shively, C. A., Register, T. C., Craft, S., Montine, K. S., Fox, E. J., Poston, K. L., Keene, C. D., Angelo, M., Bendall, S. C., Aghaeepour, N., & Montine, T. J. (2021). Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE. Science advances, 7(51), eabk0473. https://doi.org/10.1126/sciadv.abk0473
Phongpreecha, Thanaphong, et al. "Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE." Science advances vol. 7,51 (2021): eabk0473. doi: https://doi.org/10.1126/sciadv.abk0473
Phongpreecha T, Gajera CR, Liu CC, Vijayaragavan K, Chang AL, Becker M, Fallahzadeh R, Fernandez R, Postupna N, Sherfield E, Tebaykin D, Latimer C, Shively CA, Register TC, Craft S, Montine KS, Fox EJ, Poston KL, Keene CD, Angelo M, Bendall SC, Aghaeepour N, Montine TJ. Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE. Sci Adv. 2021 Dec 17;7(51):eabk0473. doi: 10.1126/sciadv.abk0473. Epub 2021 Dec 15. PMID: 34910503.
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Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions.

Nature machine intelligence

Culos A, Tsai AS, Stanley N, Becker M, Ghaemi MS, McIlwain DR, Fallahzadeh R, Tanada A, Nassar H, Espinosa C, Xenochristou M, Ganio E, Peterson L, Han X, Stelzer IA, Ando K, Gaudilliere D, Phongpreecha T, Marić I, Chang AL, Shaw GM, Stevenson DK, Bendall S, Davis KL, Fantl W, Nolan GP, Hastie T, Tibshirani R, Angst MS, Gaudilliere B, Aghaeepour N.
PMID: 33294774
Nat Mach Intell. 2020 Oct;2(10):619-628. doi: 10.1038/s42256-020-00232-8. Epub 2020 Oct 12.

The dense network of interconnected cellular signalling responses that are quantifiable in peripheral immune cells provides a wealth of actionable immunological insights. Although high-throughput single-cell profiling techniques, including polychromatic flow and mass cytometry, have matured to a point that...

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Culos A, Tsai AS, Stanley N, et al. Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nat Mach Intell. 2020;2(10):619-628doi: 10.1038/s42256-020-00232-8.
Culos, A., Tsai, A. S., Stanley, N., Becker, M., Ghaemi, M. S., McIlwain, D. R., Fallahzadeh, R., Tanada, A., Nassar, H., Espinosa, C., Xenochristou, M., Ganio, E., Peterson, L., Han, X., Stelzer, I. A., Ando, K., Gaudilliere, D., Phongpreecha, T., Marić, I., Chang, A. L., Shaw, G. M., Stevenson, D. K., Bendall, S., Davis, K. L., Fantl, W., Nolan, G. P., Hastie, T., Tibshirani, R., Angst, M. S., Gaudilliere, B., & Aghaeepour, N. (2020). Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nature machine intelligence, 2(10), 619-628. https://doi.org/10.1038/s42256-020-00232-8
Culos, Anthony, et al. "Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions." Nature machine intelligence vol. 2,10 (2020): 619-628. doi: https://doi.org/10.1038/s42256-020-00232-8
Culos A, Tsai AS, Stanley N, Becker M, Ghaemi MS, McIlwain DR, Fallahzadeh R, Tanada A, Nassar H, Espinosa C, Xenochristou M, Ganio E, Peterson L, Han X, Stelzer IA, Ando K, Gaudilliere D, Phongpreecha T, Marić I, Chang AL, Shaw GM, Stevenson DK, Bendall S, Davis KL, Fantl W, Nolan GP, Hastie T, Tibshirani R, Angst MS, Gaudilliere B, Aghaeepour N. Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions. Nat Mach Intell. 2020 Oct;2(10):619-628. doi: 10.1038/s42256-020-00232-8. Epub 2020 Oct 12. PMID: 33294774; PMCID: PMC7720904.
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Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes.

Current opinion in critical care

Verdonk F, Einhaus J, Tsai AS, Hedou J, Choisy B, Gaudilliere D, Kin C, Aghaeepour N, Angst MS, Gaudilliere B.
PMID: 34545029
Curr Opin Crit Care. 2021 Dec 01;27(6):717-725. doi: 10.1097/MCC.0000000000000883.

PURPOSE OF REVIEW: Postoperative complications including infections, cognitive impairment, and protracted recovery occur in one-third of the 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on our healthcare system. However, the...

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Verdonk F, Einhaus J, Tsai AS, et al. Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes. Curr Opin Crit Care. 2021;27(6):717-725doi: 10.1097/MCC.0000000000000883.
Verdonk, F., Einhaus, J., Tsai, A. S., Hedou, J., Choisy, B., Gaudilliere, D., Kin, C., Aghaeepour, N., Angst, M. S., & Gaudilliere, B. (2021). Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes. Current opinion in critical care, 27(6), 717-725. https://doi.org/10.1097/MCC.0000000000000883
Verdonk, Franck, et al. "Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes." Current opinion in critical care vol. 27,6 (2021): 717-725. doi: https://doi.org/10.1097/MCC.0000000000000883
Verdonk F, Einhaus J, Tsai AS, Hedou J, Choisy B, Gaudilliere D, Kin C, Aghaeepour N, Angst MS, Gaudilliere B. Measuring the human immune response to surgery: multiomics for the prediction of postoperative outcomes. Curr Opin Crit Care. 2021 Dec 01;27(6):717-725. doi: 10.1097/MCC.0000000000000883. PMID: 34545029; PMCID: PMC8585713.
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Efficient adjustable light couplers of integrated III-V nanowire emitters on silicon waveguides based on ring resonators.

Optics letters

Aghaeipour M, Kasper L, Herranz J, Geelhaar L, Bruns J.
PMID: 32870836
Opt Lett. 2020 Sep 01;45(17):4702-4705. doi: 10.1364/OL.398930.

The development of integrated vertical III-V nanowire (NW) stimulated emitters in silicon photonics while achieving an efficient light coupling through vertical III-V NW lasers into horizontal optical silicon waveguides is demanding. This is mainly due to the directionality and...

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Aghaeipour M, Kasper L, Herranz J, et al. Efficient adjustable light couplers of integrated III-V nanowire emitters on silicon waveguides based on ring resonators. Opt Lett. 2020;45(17):4702-4705doi: 10.1364/OL.398930.
Aghaeipour, M., Kasper, L., Herranz, J., Geelhaar, L., & Bruns, J. (2020). Efficient adjustable light couplers of integrated III-V nanowire emitters on silicon waveguides based on ring resonators. Optics letters, 45(17), 4702-4705. https://doi.org/10.1364/OL.398930
Aghaeipour, Mahtab, et al. "Efficient adjustable light couplers of integrated III-V nanowire emitters on silicon waveguides based on ring resonators." Optics letters vol. 45,17 (2020): 4702-4705. doi: https://doi.org/10.1364/OL.398930
Aghaeipour M, Kasper L, Herranz J, Geelhaar L, Bruns J. Efficient adjustable light couplers of integrated III-V nanowire emitters on silicon waveguides based on ring resonators. Opt Lett. 2020 Sep 01;45(17):4702-4705. doi: 10.1364/OL.398930. PMID: 32870836.
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Multivariate prediction of dementia in Parkinson's disease.

NPJ Parkinson's disease

Phongpreecha T, Cholerton B, Mata IF, Zabetian CP, Poston KL, Aghaeepour N, Tian L, Quinn JF, Chung KA, Hiller AL, Hu SC, Edwards KL, Montine TJ.
PMID: 32885039
NPJ Parkinsons Dis. 2020 Aug 25;6:20. doi: 10.1038/s41531-020-00121-2. eCollection 2020.

Cognitive impairment in Parkinson's disease (PD) is pervasive with potentially devastating effects. Identification of those at risk for cognitive decline is vital to identify and implement appropriate interventions. Robust multivariate approaches, including fixed-effect, mixed-effect, and multitask learning models, were...

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Phongpreecha T, Cholerton B, Mata IF, et al. Multivariate prediction of dementia in Parkinson's disease. NPJ Parkinsons Dis. 2020;6:20doi: 10.1038/s41531-020-00121-2.
Phongpreecha, T., Cholerton, B., Mata, I. F., Zabetian, C. P., Poston, K. L., Aghaeepour, N., Tian, L., Quinn, J. F., Chung, K. A., Hiller, A. L., Hu, S. C., Edwards, K. L., & Montine, T. J. (2020). Multivariate prediction of dementia in Parkinson's disease. NPJ Parkinson's disease, 620. https://doi.org/10.1038/s41531-020-00121-2
Phongpreecha, Thanaphong, et al. "Multivariate prediction of dementia in Parkinson's disease." NPJ Parkinson's disease vol. 6 (2020): 20. doi: https://doi.org/10.1038/s41531-020-00121-2
Phongpreecha T, Cholerton B, Mata IF, Zabetian CP, Poston KL, Aghaeepour N, Tian L, Quinn JF, Chung KA, Hiller AL, Hu SC, Edwards KL, Montine TJ. Multivariate prediction of dementia in Parkinson's disease. NPJ Parkinsons Dis. 2020 Aug 25;6:20. doi: 10.1038/s41531-020-00121-2. eCollection 2020. PMID: 32885039; PMCID: PMC7447766.
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An immune clock of human pregnancy.

Science immunology

Aghaeepour N, Ganio EA, Mcilwain D, Tsai AS, Tingle M, Van Gassen S, Gaudilliere DK, Baca Q, McNeil L, Okada R, Ghaemi MS, Furman D, Wong RJ, Winn VD, Druzin ML, El-Sayed YY, Quaintance C, Gibbs R, Darmstadt GL, Shaw GM, Stevenson DK, Tibshirani R, Nolan GP, Lewis DB, Angst MS, Gaudilliere B.
PMID: 28864494
Sci Immunol. 2017 Sep 01;2(15). doi: 10.1126/sciimmunol.aan2946.

The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all...

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Aghaeepour N, Ganio EA, Mcilwain D, et al. An immune clock of human pregnancy. Sci Immunol. 2017;2(15)doi: 10.1126/sciimmunol.aan2946.
Aghaeepour, N., Ganio, E. A., Mcilwain, D., Tsai, A. S., Tingle, M., Van Gassen, S., Gaudilliere, D. K., Baca, Q., McNeil, L., Okada, R., Ghaemi, M. S., Furman, D., Wong, R. J., Winn, V. D., Druzin, M. L., El-Sayed, Y. Y., Quaintance, C., Gibbs, R., Darmstadt, G. L., Shaw, G. M., Stevenson, D. K., Tibshirani, R., Nolan, G. P., Lewis, D. B., Angst, M. S., & Gaudilliere, B. (2017). An immune clock of human pregnancy. Science immunology, 2(15), . https://doi.org/10.1126/sciimmunol.aan2946
Aghaeepour, Nima, et al. "An immune clock of human pregnancy." Science immunology vol. 2,15 (2017). doi: https://doi.org/10.1126/sciimmunol.aan2946
Aghaeepour N, Ganio EA, Mcilwain D, Tsai AS, Tingle M, Van Gassen S, Gaudilliere DK, Baca Q, McNeil L, Okada R, Ghaemi MS, Furman D, Wong RJ, Winn VD, Druzin ML, El-Sayed YY, Quaintance C, Gibbs R, Darmstadt GL, Shaw GM, Stevenson DK, Tibshirani R, Nolan GP, Lewis DB, Angst MS, Gaudilliere B. An immune clock of human pregnancy. Sci Immunol. 2017 Sep 01;2(15). doi: 10.1126/sciimmunol.aan2946. PMID: 28864494; PMCID: PMC5701281.
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Computational analysis optimizes the flow cytometric evaluation for lymphoma.

Cytometry. Part B, Clinical cytometry

Craig FE, Brinkman RR, Eyck ST, Aghaeepour N.
PMID: 23873623
Cytometry B Clin Cytom. 2013 Jul 19; doi: 10.1002/cytob.21115. Epub 2013 Jul 19.

Background: Although many clinical laboratories are adopting higher color flow cytometric assays, the approach to optimizing panel design and data analysis is often traditional and subjective. In order to address the question "What is the best flow cytometric strategy...

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Craig FE, Brinkman RR, Eyck ST, et al. Computational analysis optimizes the flow cytometric evaluation for lymphoma. Cytometry B Clin Cytom. 2013;doi: 10.1002/cytob.21115.
Craig, F. E., Brinkman, R. R., Eyck, S. T., & Aghaeepour, N. (2013). Computational analysis optimizes the flow cytometric evaluation for lymphoma. Cytometry. Part B, Clinical cytometry, . https://doi.org/10.1002/cytob.21115
Craig, Fiona E, et al. "Computational analysis optimizes the flow cytometric evaluation for lymphoma." Cytometry. Part B, Clinical cytometry vol. (2013). doi: https://doi.org/10.1002/cytob.21115
Craig FE, Brinkman RR, Eyck ST, Aghaeepour N. Computational analysis optimizes the flow cytometric evaluation for lymphoma. Cytometry B Clin Cytom. 2013 Jul 19; doi: 10.1002/cytob.21115. Epub 2013 Jul 19. PMID: 23873623.
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Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE.

Science advances

Phongpreecha T, Gajera CR, Liu CC, Vijayaragavan K, Chang AL, Becker M, Fallahzadeh R, Fernandez R, Postupna N, Sherfield E, Tebaykin D, Latimer C, Shively CA, Register TC, Craft S, Montine KS, Fox EJ, Poston KL, Keene CD, Angelo M, Bendall SC, Aghaeepour N, Montine TJ.
PMID: 34910503
Sci Adv. 2021 Dec 17;7(51):eabk0473. doi: 10.1126/sciadv.abk0473. Epub 2021 Dec 15.

[Figure: see text].

Cite
Phongpreecha T, Gajera CR, Liu CC, et al. Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE. Sci Adv. 2021;7(51):eabk0473doi: 10.1126/sciadv.abk0473.
Phongpreecha, T., Gajera, C. R., Liu, C. C., Vijayaragavan, K., Chang, A. L., Becker, M., Fallahzadeh, R., Fernandez, R., Postupna, N., Sherfield, E., Tebaykin, D., Latimer, C., Shively, C. A., Register, T. C., Craft, S., Montine, K. S., Fox, E. J., Poston, K. L., Keene, C. D., Angelo, M., Bendall, S. C., Aghaeepour, N., & Montine, T. J. (2021). Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE. Science advances, 7(51), eabk0473. https://doi.org/10.1126/sciadv.abk0473
Phongpreecha, Thanaphong, et al. "Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE." Science advances vol. 7,51 (2021): eabk0473. doi: https://doi.org/10.1126/sciadv.abk0473
Phongpreecha T, Gajera CR, Liu CC, Vijayaragavan K, Chang AL, Becker M, Fallahzadeh R, Fernandez R, Postupna N, Sherfield E, Tebaykin D, Latimer C, Shively CA, Register TC, Craft S, Montine KS, Fox EJ, Poston KL, Keene CD, Angelo M, Bendall SC, Aghaeepour N, Montine TJ. Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE. Sci Adv. 2021 Dec 17;7(51):eabk0473. doi: 10.1126/sciadv.abk0473. Epub 2021 Dec 15. PMID: 34910503; PMCID: PMC8673771.
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A Peripheral Immune Signature of Labor Induction.

Frontiers in immunology

Ando K, Hédou JJ, Feyaerts D, Han X, Ganio EA, Tsai ES, Peterson LS, Verdonk F, Tsai AS, Marić I, Wong RJ, Angst MS, Aghaeepour N, Stevenson DK, Blumenfeld YJ, Sultan P, Carvalho B, Stelzer IA, Gaudillière B.
PMID: 34566984
Front Immunol. 2021 Sep 09;12:725989. doi: 10.3389/fimmu.2021.725989. eCollection 2021.

Approximately 1 in 4 pregnant women in the United States undergo labor induction. The onset and establishment of labor, particularly induced labor, is a complex and dynamic process influenced by multiple endocrine, inflammatory, and mechanical factors as well as...

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Ando K, Hédou JJ, Feyaerts D, et al. A Peripheral Immune Signature of Labor Induction. Front Immunol. 2021;12:725989doi: 10.3389/fimmu.2021.725989.
Ando, K., Hédou, J. J., Feyaerts, D., Han, X., Ganio, E. A., Tsai, E. S., Peterson, L. S., Verdonk, F., Tsai, A. S., Marić, I., Wong, R. J., Angst, M. S., Aghaeepour, N., Stevenson, D. K., Blumenfeld, Y. J., Sultan, P., Carvalho, B., Stelzer, I. A., & Gaudillière, B. (2021). A Peripheral Immune Signature of Labor Induction. Frontiers in immunology, 12725989. https://doi.org/10.3389/fimmu.2021.725989
Ando, Kazuo, et al. "A Peripheral Immune Signature of Labor Induction." Frontiers in immunology vol. 12 (2021): 725989. doi: https://doi.org/10.3389/fimmu.2021.725989
Ando K, Hédou JJ, Feyaerts D, Han X, Ganio EA, Tsai ES, Peterson LS, Verdonk F, Tsai AS, Marić I, Wong RJ, Angst MS, Aghaeepour N, Stevenson DK, Blumenfeld YJ, Sultan P, Carvalho B, Stelzer IA, Gaudillière B. A Peripheral Immune Signature of Labor Induction. Front Immunol. 2021 Sep 09;12:725989. doi: 10.3389/fimmu.2021.725989. eCollection 2021. PMID: 34566984; PMCID: PMC8458888.
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Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth.

Cell reports. Medicine

Tarca AL, Pataki BÁ, Romero R, Sirota M, Guan Y, Kutum R, Gomez-Lopez N, Done B, Bhatti G, Yu T, Andreoletti G, Chaiworapongsa T, Hassan SS, Hsu CD, Aghaeepour N, Stolovitzky G, Csabai I, Costello JC.
PMID: 34195686
Cell Rep Med. 2021 Jun 15;2(6):100323. doi: 10.1016/j.xcrm.2021.100323. eCollection 2021 Jun 15.

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models...

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Tarca AL, Pataki BÁ, Romero R, et al. Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth. Cell Rep Med. 2021;2(6):100323doi: 10.1016/j.xcrm.2021.100323.
Tarca, A. L., Pataki, B. �. �., Romero, R., Sirota, M., Guan, Y., Kutum, R., Gomez-Lopez, N., Done, B., Bhatti, G., Yu, T., Andreoletti, G., Chaiworapongsa, T., Hassan, S. S., Hsu, C. D., Aghaeepour, N., Stolovitzky, G., Csabai, I., & Costello, J. C. (2021). Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth. Cell reports. Medicine, 2(6), 100323. https://doi.org/10.1016/j.xcrm.2021.100323
Tarca, Adi L, et al. "Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth." Cell reports. Medicine vol. 2,6 (2021): 100323. doi: https://doi.org/10.1016/j.xcrm.2021.100323
Tarca AL, Pataki BÁ, Romero R, Sirota M, Guan Y, Kutum R, Gomez-Lopez N, Done B, Bhatti G, Yu T, Andreoletti G, Chaiworapongsa T, Hassan SS, Hsu CD, Aghaeepour N, Stolovitzky G, Csabai I, Costello JC. Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth. Cell Rep Med. 2021 Jun 15;2(6):100323. doi: 10.1016/j.xcrm.2021.100323. eCollection 2021 Jun 15. PMID: 34195686; PMCID: PMC8233692.
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Prevalence of human papillomavirus (HPV) in oral mucosal lesions in Iran: A systematic review and meta-analysis.

Journal of medical virology

Aghaeipour F, Salehiniya H, Abbaszadeh H.
PMID: 34180541
J Med Virol. 2021 Nov;93(11):6089-6099. doi: 10.1002/jmv.27161. Epub 2021 Jul 06.

The role of human papillomavirus (HPV) in the development of oral lesions is controversial. There has been no comprehensive study about HPV prevalence in Iran. This systematic review and meta-analysis were aimed at finding HPV prevalence of oral lesions...

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Aghaeipour F, Salehiniya H, Abbaszadeh H. Prevalence of human papillomavirus (HPV) in oral mucosal lesions in Iran: A systematic review and meta-analysis. J Med Virol. 2021;93(11):6089-6099doi: 10.1002/jmv.27161.
Aghaeipour, F., Salehiniya, H., & Abbaszadeh, H. (2021). Prevalence of human papillomavirus (HPV) in oral mucosal lesions in Iran: A systematic review and meta-analysis. Journal of medical virology, 93(11), 6089-6099. https://doi.org/10.1002/jmv.27161
Aghaeipour, Farideh, et al. "Prevalence of human papillomavirus (HPV) in oral mucosal lesions in Iran: A systematic review and meta-analysis." Journal of medical virology vol. 93,11 (2021): 6089-6099. doi: https://doi.org/10.1002/jmv.27161
Aghaeipour F, Salehiniya H, Abbaszadeh H. Prevalence of human papillomavirus (HPV) in oral mucosal lesions in Iran: A systematic review and meta-analysis. J Med Virol. 2021 Nov;93(11):6089-6099. doi: 10.1002/jmv.27161. Epub 2021 Jul 06. PMID: 34180541.
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Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease.

Open forum infectious diseases

Ward RA, Aghaeepour N, Bhattacharyya RP, Clish CB, Gaudillière B, Hacohen N, Mansour MK, Mudd PA, Pasupneti S, Presti RM, Rhee EP, Sen P, Spec A, Tam JM, Villani AC, Woolley AE, Hsu JL, Vyas JM.
PMID: 34805429
Open Forum Infect Dis. 2021 Sep 25;8(11):ofab483. doi: 10.1093/ofid/ofab483. eCollection 2021 Nov.

The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to...

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Ward RA, Aghaeepour N, Bhattacharyya RP, et al. Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease. Open Forum Infect Dis. 2021;8(11):ofab483doi: 10.1093/ofid/ofab483.
Ward, R. A., Aghaeepour, N., Bhattacharyya, R. P., Clish, C. B., Gaudillière, B., Hacohen, N., Mansour, M. K., Mudd, P. A., Pasupneti, S., Presti, R. M., Rhee, E. P., Sen, P., Spec, A., Tam, J. M., Villani, A. C., Woolley, A. E., Hsu, J. L., & Vyas, J. M. (2021). Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease. Open forum infectious diseases, 8(11), ofab483. https://doi.org/10.1093/ofid/ofab483
Ward, Rebecca A, et al. "Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease." Open forum infectious diseases vol. 8,11 (2021): ofab483. doi: https://doi.org/10.1093/ofid/ofab483
Ward RA, Aghaeepour N, Bhattacharyya RP, Clish CB, Gaudillière B, Hacohen N, Mansour MK, Mudd PA, Pasupneti S, Presti RM, Rhee EP, Sen P, Spec A, Tam JM, Villani AC, Woolley AE, Hsu JL, Vyas JM. Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease. Open Forum Infect Dis. 2021 Sep 25;8(11):ofab483. doi: 10.1093/ofid/ofab483. eCollection 2021 Nov. PMID: 34805429; PMCID: PMC8598922.
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Showing 25 to 36 of 47 entries