Price, Nathan D.

Multiple early factors anticipate post-acute COVID-19 sequelae

Su, Y., Yuan, D., Chen, D. G., Ng, R. H., Wang, K., Choi, J., Li, S., Hong, S., Zhang, R., Xie, J., et al. (2022) · Cell

Long-Term Effects of COVID-19COVID-19 Clinical Research Studies

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A community-driven global reconstruction of human metabolism

Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., Haraldsdottir, H., Mo, M. L., Rolfsson, O., Stobbe, M. D., et al. (2013) · Nature Biotechnology

Microbial Metabolic Engineering and BioproductionBioinformatics and Genomic Networks

Cited by 1,019

Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease

ARUK Consortium, Sims, R., GERAD/PERADES, C., van der Lee, S. J., Naj, A. C., Bellenguez, C., Badarinarayan, N., Jakobsdottir, J., Kunkle, B. W., Boland, A., et al. (2017) · Nature Genetics

Alzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration Mechanisms

Cited by 1,012

Multiscale Analysis of Independent Alzheimer’s Cohorts Finds Disruption of Molecular, Genetic, and Clinical Networks by Human Herpesvirus

Readhead, B., Haure-Mirande, J.-V., Funk, C. C., Richards, M. A., Shannon, P., Haroutunian, V., Sano, M., Liang, W. S., Beckmann, N. D., Price, N. D., et al. (2018) · Neuron

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 708

MEMOTE for standardized genome-scale metabolic model testing

Lieven, C., Beber, M. E., Olivier, B. G., Bergmann, F. T., Ataman, M., Babaei, P., Bartell, J. A., Blank, L. M., Chauhan, S., Correia, K., et al. (2020) · Nature Biotechnology

Microbial Metabolic Engineering and BioproductionGene Regulatory Network Analysis

Cited by 509

Human whole genome genotype and transcriptome data for Alzheimer’s and other neurodegenerative diseases

Allen, M., Carrasquillo, M. M., Funk, C., Heavner, B. D., Zou, F., Younkin, C. S., Burgess, J. D., Chai, H.-S., Crook, J., Eddy, J. A., et al. (2016) · Scientific Data

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 439

A wellness study of 108 individuals using personal, dense, dynamic data clouds

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., et al. (2017) · Nature Biotechnology

Health, Environment, Cognitive AgingBioinformatics and Genomic Networks

Cited by 427

IL-10 Alters Immunoproteostasis in APP Mice, Increasing Plaque Burden and Worsening Cognitive Behavior

Chakrabarty, P., Li, A., Ceballos-Diaz, C., Eddy, J. A., Funk, C. C., Moore, B., DiNunno, N., Rosario, A. M., Cruz, P. E., Verbeeck, C., et al. (2015) · Neuron

Alzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration Mechanisms

Cited by 354

Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions

Sieberts, S. K., Perumal, T. M., Carrasquillo, M. M., Allen, M., Reddy, J. S., Hoffman, G. E., Dang, K. K., Calley, J., Ebert, P. J., Eddy, J., et al. (2020) · Scientific Data

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 318

Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models

Wan, Y.-W., Al-Ouran, R., Mangleburg, C. G., Perumal, T. M., Lee, T. V., Allison, K., Swarup, V., Funk, C. C., Gaiteri, C., Allen, M., et al. (2020) · Cell Reports

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 295

A systems approach to prion disease

Hwang, D., Lee, I. Y., Yoo, H., Gehlenborg, N., Cho, J., Petritis, B., Baxter, D., Pitstick, R., Young, R., Spicer, D., et al. (2009) · Molecular Systems Biology

Prion Diseases and Protein MisfoldingAlzheimer's disease research and treatments

Cited by 287

Systems cancer medicine: towards realization of predictive, preventive, personalized and participatory (P4) medicine

Tian, Q., Price, N. D., & Hood, L. (2012) · Journal of Internal Medicine

Cancer Genomics and DiagnosticsBioinformatics and Genomic Networks

Cited by 224

Measuring Aging and Identifying Aging Phenotypes in Cancer Survivors

Guida, J. L., Ahles, T. A., Belsky, D., Campisi, J., Cohen, H. J., DeGregori, J., Fuldner, R., Ferrucci, L., Gallicchio, L., Gavrilov, L., et al. (2019) · JNCI: Journal of the National Cancer Institute

Cancer survivorship and careFrailty in Older Adults

Cited by 216

Amyloid-β 11 C-PiB-PET imaging results from 2 randomized bapineuzumab phase 3 AD trials

Liu, E., Schmidt, M. E., Margolin, R., Sperling, R., Koeppe, R., Mason, N. S., Klunk, W. E., Mathis, C. A., Salloway, S., Fox, N. C., et al. (2015) · Neurology

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 151

Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate

Palii, C. G., Cheng, Q., Gillespie, M. A., Shannon, P., Mazurczyk, M., Napolitani, G., Price, N. D., Ranish, J. A., Morrissey, E., Higgs, D. R., et al. (2019) · Cell Stem Cell

Hematopoietic Stem Cell TransplantationAdvanced Proteomics Techniques and Applications

Cited by 148

Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

Dinov, I. D., Heavner, B., Tang, M., Glusman, G., Chard, K., Darcy, M., Madduri, R., Pa, J., Spino, C., Kesselman, C., et al. (2016) · PLOS ONE

Artificial Intelligence in HealthcareParkinson's Disease Mechanisms and Treatments

Cited by 145

Conserved brain myelination networks are altered in Alzheimer’s and other neurodegenerative diseases

Allen, M., Wang, X., Burgess, J. D., Watzlawik, J., Serie, D. J., Younkin, C. S., Nguyen, T., Malphrus, K. G., Lincoln, S., Carrasquillo, M. M., et al. (2018) · Alzheimer's & Dementia

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 143

Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis

Gillespie, M. A., Palii, C. G., Sanchez-Taltavull, D., Shannon, P., Longabaugh, W. J. R., Downes, D. J., Sivaraman, K., Espinoza, H. M., Hughes, J. R., Price, N. D., et al. (2020) · Molecular Cell

Gene Regulatory Network AnalysisGenomics and Chromatin Dynamics

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Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder

The PTSD Systems Biology Consortium, Dean, K. R., Hammamieh, R., Mellon, S. H., Abu-Amara, D., Flory, J. D., Guffanti, G., Wang, K., Daigle, B. J., Gautam, A., et al. (2020) · Molecular Psychiatry

Posttraumatic Stress Disorder ResearchTraumatic Brain Injury Research

Cited by 101

A refined genome‐scale reconstruction of Chlamydomonas metabolism provides a platform for systems‐level analyses

Imam, S., Schäuble, S., Valenzuela, J., López García de Lomana, A., Carter, W., Price, N. D., & Baliga, N. S. (2015) · The Plant Journal

Microbial Metabolic Engineering and BioproductionAlgal biology and biofuel production

Cited by 96

Heterogeneity in protein expression induces metabolic variability in a modeled Escherichia coli population

Labhsetwar, P., Cole, J. A., Roberts, E., Price, N. D., & Luthey-Schulten, Z. A. (2013) · Proceedings of the National Academy of Sciences

Microbial Metabolic Engineering and BioproductionGene Regulatory Network Analysis

Cited by 94

Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer’s disease resilience

Initiative, F. T. A. D. N., Ridge, P. G., Karch, C. M., Hsu, S., Arano, I., Teerlink, C. C., Ebbert, M. T. W., Gonzalez Murcia, J. D., Farnham, J. M., Damato, A. R., et al. (2017) · Genome Medicine

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 83

From taxonomy to metabolic output: what factors define gut microbiome health?

Wilmanski, T., Rappaport, N., Diener, C., Gibbons, S. M., & Price, N. D. (2021) · Gut Microbes

Gut microbiota and healthOral microbiology and periodontitis research

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A candidate regulatory variant at the TREM gene cluster associates with decreased Alzheimer's disease risk and increased TREML1 and TREM2 brain gene expression

Carrasquillo, M. M., Allen, M., Burgess, J. D., Wang, X., Strickland, S. L., Aryal, S., Siuda, J., Kachadoorian, M. L., Medway, C., Younkin, C. S., et al. (2017) · Alzheimer's & Dementia

Alzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

Cited by 58