Team Lead, Data Science & Biostatistics
Team Lead, Data Science & Biostatistics

Biography

Lisa Bramer is team lead for the Datascience and Biostatistics group within the Biological Sciences Division. Her experience includes statistical modeling, experimental design, spatial statistics, time series analysis, hierarchical models, Bayesian statistics, statistical/machine learning, data visualization, and data mining.

Bramer’s current research is focused on the application and development of statistical and machine learning methods for biological data, particularly mass spectrometry omics data and streaming data analytics. She is particularly interested in exploratory data analysis and visualization for big data, data integration, and machine learning (particularly when multiple heterogeneous data sources are available), and development of robust software packages for biological data processing. 

Disciplines and Skills

  • Anomaly detection
  • Bayesian statistics
  • Big data analytics
  • Biostatistics
  • Computational biology
  • Data analysis
  • Data mining
  • Data science
  • Data visualization
  • Experimental design
  • LaTeX
  • Machine learning
  • Predictive modeling
  • Python
  • R
  • Spatial modeling
  • Statistical modeling
  • Statistics
  • Time series analysis

Education

  • PhD in Statistics, Iowa State University
  • MS in Statistics, Iowa State University
  • BA in Psychology, Purdue University
  • BS in Mathematics, Purdue University

Publications

2020

  • Bramer L.M., A.M. White, K.G. Stratton, A.M. Thompson, D.M. Claborne, K.S. Hofmockel, and L. McCue. 2020. "ftmsRanalysis: An R package for exploratory data analysis and interactive visualization of FT-MS data." PLoS Computational Biology 16, no. 3:Article No. e1007654. PNNL-SA-152118. doi:10.1371/journal.pcbi.1007654
  • Khare S., G.M. Deloid, R.M. Molina, K. Gokulan, S.P. Couvillion, K.J. Bloodsworth, and E.K. Eder, et al. 2020. "Effects of ingested nanocellulose on intestinal microbiota and homeostasis in Wistar Han rats." NanoImpact 18. PNNL-SA-149247. doi:10.1016/j.impact.2020.100216
  • Leier H.C., J.B. Weinstein, J.E. Kyle, J. Lee, L.M. Bramer, K.G. Stratton, and D. Kempthorne, et al. 2020. "A global lipid map defines a network essential for Zika virus replication." Nature Communications 11, no. 3652. PNNL-SA-139745. doi:10.1101/2020.01.27.910919
  • Piehowski P.D., Y. Zhu, L.M. Bramer, K.G. Stratton, R. Zhao, D.J. Orton, and R.J. Moore, et al. 2020. "Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-µm spatial resolution." Nature Communications 11, no. 1:Article No. 8. PNNL-SA-138884. doi:10.1038/s41467-019-13858-z
  • Zhao Q., S.J. Callister, A.M. Thompson, R.K. Kukkadapu, M. Tfaily, L.M. Bramer, and N. Qafoku, et al. 2020. "Strong mineralogic control of soil organic matter composition in response to nutrient addition across diverse grassland sites." Science of Total Environment 736. PNNL-SA-144529. doi:10.1016/j.scitotenv.2020.137839

2019

  • Bramer L.M., K.G. Stratton, A.M. White, A.A. Bleeker, M.A. Kobold, K.M. Waters, and T.O. Metz, et al. 2019. "P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data." Journal of Proteome Research 18, no. 3:1426-1432. PNNL-SA-140572. doi:10.1021/acs.jproteome.8b00840
  • Challacombe J., J. Challacombe, C.N. Hesse, L.M. Bramer, L. McCue, M.S. Lipton, and S.O. Purvine, et al. 2019. "Genomes and Secretomes of Ascomycota Fungi Reveal Diverse Functions in Plant Biomass Decomposition and Pathogenesis." BMC Genomics 20, no. 1:Article No. 976. PNNL-SA-140986. doi:10.1186/s12864-019-6358-x
  • Mehdi B.L., A. Stevens, L. Kovarik, N. Jiang, H.S. Mehta, A.V. Liyu, and S.M. Reehl, et al. 2019. "Controlling the Spatio-Temporal Dose Distribution During STEM Imaging by Subsampled Acquisition: In-Situ Observations of Kinetic Processes in Liquids." Applied Physics Letters 115, no. 6:Article Number 063102. PNNL-SA-145156. doi:10.1063/1.5096595
  • Messier K.P., L.G. Tidwell, C. Ghetu, D. Rohlman, R.P. Scott, L.M. Bramer, and H.M. Dixon, et al. 2019. "Indoor versus Outdoor Air Quality During Wildfires." Environmental Science & Technology Letters 6, no. 12:696-701. PNNL-SA-147722. doi:10.1021/acs.estlett.9b00599
  • Mitchell H.D., A.J. Eisfeld, K.G. Stratton, N.C. Heller, L.M. Bramer, J. Wen, and J.E. McDermott, et al. 2019. "The Role of EGFR in Influenza Pathogenicity: Multiple Network-based Approaches To Identify a Key Regulator of Non-Lethal Infections." Frontiers in Cell and Developmental Biology 7. PNNL-SA-142083. doi:10.3389/fcell.2019.00200
  • Sharon G., N.J. Cruz, D. Kang, M. Gandal, B. Wang, Y. Kim, and E.M. Zink, et al. 2019. "Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice." Cell 177, no. 6:1600-1618. PNNL-SA-131563. doi:10.1016/j.cell.2019.05.004
  • Stanfill B.A., S.M. Reehl, L.M. Bramer, E.S. Nakayasu, S.S. Rich, T.O. Metz, and M. Rewers, et al. 2019. "Extending Classification Algorithms to Case-Control Studies." Biomedical Engineering and Computational Biology 10. PNNL-SA-135302. doi:10.1177/1179597219858954
  • Stratton K.G., B.M. Webb-Robertson, L. McCue, B.A. Stanfill, D.M. Claborne, I.G. Godinez, and T. Johansen, et al. 2019. "pmartR: Quality Control and Statistics for Mass Spectrometry-Based Biological Data." Journal of Proteome Research 18, no. 3:1418-1425. PNNL-SA-123105. doi:10.1021/acs.jproteome.8b00760
  • Whidbey C., N.C. Sadler, R.N. Nair, R.F. Volk, A.J. DeLeon, L.M. Bramer, and S.J. Fansler, et al. 2019. "A Probe-Enabled Approach for the Selective Isolation and Characterization of Functionally Active Subpopulations in the Gut Microbiome." Journal of the American Chemical Society 141, no. 1:42-47. PNNL-SA-127532. doi:10.1021/jacs.8b09668

2018

  • Bottos E.M., D.W. Kennedy, E.B. Romero, S.J. Fansler, J.M. Brown, L.M. Bramer, and R.K. Chu, et al. 2018. "Dispersal Limitation and Thermodynamic Constraints Govern Spatial Structure of Permafrost Microbial Communities." FEMS Microbiology Ecology 94, no. 8:fiy110. PNNL-SA-130968. doi:10.1093/femsec/fiy110
  • Burrows S.M., A. Dasgupta, S.M. Reehl, L.M. Bramer, P. Ma, P.J. Rasch, and Y. Qian. 2018. "Characterizing the relative importance assigned to physical variables by climate scientists when assessing atmospheric climate model fidelity." Advances in Atmospheric Sciences 35, no. 9:1101-1113. PNNL-SA-129346. doi:10.1007/s00376-018-7300-x
  • Liu C., L.M. Bramer, B.M. Webb-Robertson, K. Waugh, M. Rewers, and Q. Zhang. 2018. "Temporal Expression Profiling of Plasma Proteins Reveals Oxidative Stress in Early Stages of Type 1 Diabetes Progression." Journal of Proteomics 172. PNNL-SA-125485. doi:10.1016/j.jprot.2017.10.004
  • Roy Chowdhury T., L.M. Bramer, D.W. Hoyt, Y. Kim, T.O. Metz, L. McCue, and H.L. Diefenderfer, et al. 2018. "Temporal dynamics of CO2 and CH4 loss potentials in response to rapid hydrological shifts in tidal freshwater wetland soils." Ecological Engineering 114. PNNL-SA-123359. doi:10.1016/j.ecoleng.2017.06.041
  • Stanfill B.A., E.S. Nakayasu, L.M. Bramer, A.M. Thompson, C.K. Ansong, T. Clauss, and M.A. Gritsenko, et al. 2018. "Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data." Molecular and Cellular Proteomics 17, no. 9:1824-1836. PNNL-SA-129934. doi:10.1074/mcp.RA118.000648

2017

  • Bramer L.M., J. Rounds, C.D. Burleyson, D.C. Fortin, J.E. Hathaway, J.S. Rice, and I.P. Kraucunas. 2017. "Evaluating Penalized Logistic Regression Models to Predict Heat-Related Electric Grid Stress Days." Applied Energy 205. PNNL-SA-126567. doi:10.1016/j.apenergy.2017.09.087
  • Graham E.B., M.M. Tfaily, A.R. Crump, A.E. Goldman, L.M. Bramer, E.V. Arntzen, and E.B. Romero, et al. 2017. "Carbon inputs from riparian vegetation limit oxidation of physically bound organic carbon via biochemical and thermodynamic processes." Journal of Geophysical Research. Biogeosciences 122, no. 12:3188-3205. PNNL-SA-125144. doi:10.1002/2017JG003967
  • Halfvarson J., C.J. Brislawn, R. Lamendella, Y. Vazquez-Baeza, W.A. Walters, L.M. Bramer, and M. D'Amato, et al. 2017. "Dynamics of the Human Gut Microbiome in Inflammatory Bowel Disease." Nature Microbiology 2, no. 5:Article No. 17004. PNNL-SA-122629. doi:10.1038/nmicrobiol.2017.4
  • Liu C., L.M. Bramer, B.M. Webb-Robertson, K. Waugh, M. Rewers, and Q. Zhang. 2017. "Temporal profiles of plasma proteome during childhood development." Journal of Proteomics 152. PNNL-SA-122850. doi:10.1016/j.jprot.2016.11.016
  • Madeen E.P., C.V. Lohr, H. You, L.E. Siddens, S.K. Krueger, R.H. Dashwood, and F.J. Gonzalez, et al. 2017. "Dibenzo[def,p]chrysene transplacental carcinogenesis in wild-type, Cyp1b1 knockout, and CYP1B1 humanized mice." Molecular Carcinogenesis 56, no. 1:163-171. PNWD-SA-10523. doi:10.1002/mc.22480
  • Webb-Robertson B.M., L.M. Bramer, J.L. Jensen, M.A. Kobold, K.G. Stratton, A.M. White, and K.D. Rodland. 2017. "P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets." Cancer Research 77, no. 21:e47-e50. PNNL-SA-123730. doi:10.1158/0008-5472.CAN-17-0335

2016

  • Webb-Robertson B.M., L.M. Bramer, S.M. Reehl, T.O. Metz, Q. Zhang, M. Rewers, and B. Frohnert. 2016. "ROFI - The use of Repeated Optimization for Feature Interpretation." In International Conference on Computational Science and Computational Intelligence (CSCI 2016), December 15-17, 206, Las Vegas, Nevada, edited by HR Arabnia, L Deligiannidis and M Yang. Piscataway, New Jersey:IEEE. PNWD-SA-10276. doi:10.1109/CSCI.2016.0013

2015

  • Amidan B.G., A.M. Venzin, and L.M. Bramer. 2015. Multiple Lines of Evidence. PNNL-24245. Richland, WA: Pacific Northwest National Laboratory. Multiple Lines of Evidence
  • Bramer L.M., S. Chatterjee, A.E. Holmes, S.M. Robinson, S.F. Bradley, and B.M. Webb-Robertson. 2015. "A Machine Learning Approach for Business Intelligence Analysis using Commercial Shipping Transaction Data." In The 11th International Conference on Data Mining (DMIN 2015), July 27-30, 2015, Las Vegas, Nevada, 162-167. Athens, Georgia:CSREA Press. PNNL-SA-110014.
  • Lafontaine S., J. Schrlau, J. Butler, Y. Jia, B.L. Harper, S.G. Harris, and L.M. Bramer, et al. 2015. "RELATIVE INFLUENCE OF TRANS-PACIFIC AND REGIONAL ATMOSPHERIC TRANSPORT OF PAHS IN THE PACIFIC NORTHWEST, U.S." Environmental Science & Technology 49, no. 23:13807-13816. PNWD-SA-10478. doi:10.1021/acs.est.5b00800
  • Siddens L.K., K.L. Bunde, T.A. Harper Jr., T.J. McQuistan, C.V. Lohr, L.M. Bramer, and K.M. Waters, et al. 2015. "Cytochrome P450 1b1 in Polycyclic Aromatic Hydrocarbon (PAH)-Induced Skin Carcinogenesis: Tumorigenicity of Individual PAHs and Coal-Tar Extract, DNA Adduction and Expression of Select Genes in the Cyp1b1 Knockout Mouse Toxicology and Applied Pharmacology." Toxicology and Applied Pharmacology 287, no. 2:149-160. PNWD-SA-10455. doi:10.1016/j.taap.2015.05.019
  • Townsend P., Q. Zhang, J. Shapiro, B.M. Webb-Robertson, L.M. Bramer, A.A. Schepmoes, and K.K. Weitz, et al. 2015. "Serum Proteome Profiles in Stricturing Crohn’s Disease: A pilot study." Inflammatory Bowel Diseases 21, no. 8:1935-41. PNNL-SA-108499. doi:10.1097/MIB.0000000000000445

2014

  • Matzke B.D., L.L. Newburn, J.E. Hathaway, L.M. Bramer, J.E. Wilson, S.T. Dowson, and L.H. Sego, et al. 2014. Visual Sample Plan Version 7.0 User's Guide. PNNL-23211. Richland, WA: Pacific Northwest National Laboratory. Visual Sample Plan Version 7.0 User's Guide
  • Webb-Robertson B.M., M.M. Matzke, S. Datta, S.H. Payne, J. Kang, L.M. Bramer, and C.D. Nicora, et al. 2014. "Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements." Molecular and Cellular Proteomics 13, no. 12:3639-3646. PNNL-SA-95335. doi:10.1074/mcp.M113.030932