As IMCI grows and matures, we are seeing more and more research articles being published. Here’s our growing list of publications that cite CMCI P20GM104420.

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Badsha, M. B., & Fu, A. Q. (2019). Learning Causal Biological Networks With the Principle of Mendelian Randomization. Frontiers in genetics10, 460. doi:10.3389/fgene.2019.00460

Badsha, M.B., Li, R., Liu, B. et al. (2020). Imputation of single-cell gene expression with an autoencoder neural networkQuant Biol., 8(1):78-94. doi:10.1007/s40484-019-0192-7

Baumgaertner, B., Carlisle, J. E., & Justwan, F. (2018). The influence of political ideology and trust on willingness to vaccinate. PloS one13(1), e0191728. doi:10.1371/journal.pone.0191728

Baumgaertner, B. O., Fetros, P. A., Krone, S. M., & Tyson, R. C. (2018). Spatial opinion dynamics and the effects of two types of mixing. Physical review. E98(2-1), 022310. doi:10.1103/PhysRevE.98.022310

Baumgaertner, B., Ridenhour, B. J., Justwan, F., Carlisle, J. E., & Miller, C. R. (2020). Risk of disease and willingness to vaccinate in the United States: A population-based surveyPLoS medicine17(10), e1003354.

Baumgaertner, B. O., Tyson, R. T., & Krone, S. M. (2016). Opinion strength influences the spatial dynamics of opinion formationThe Journal of mathematical sociology40(4), 207–218. doi:10.1080/0022250X.2016.1205049

Belsare A, Gompper M, Keller B, Sumners J, Hansen L, Millspaugh J. Size matters: Sample size assessments for chronic wasting disease surveillance using an agent-based modeling frameworkMethodsX. 2020;7:100953. Published 2020 Jun 11. doi:10.1016/j.mex.2020.100953

Belsare, Aniruddha V., Gompper, Matthew E., Keller, Barbara, Sumners, Jason, Hansen, Lonnie, Millspaugh, Joshua J. (2020). An agent-based framework for improving wildlife disease surveillance: A case study of chronic wasting disease in Missouri white-tailed deer. Ecological Modelling, 417, 108919. doi:10.1016/j.ecolmodel.2019.108919

Belsare, A., & Vanak, A. T. (2020). Modelling the challenges of managing free-ranging dog populations. Scientific reports10(1), 18874.

Brown CJ, Mtui D, Oswald BP, Van Leuven JT, Vallender EJ, Schultz-Darken N, Ross CN, Tardif, SD, Austad, SN & Forney, LJ. Comparative genomics of Bifidobacterium species isolated from marmosets and humansAm J Primatol. 2019;81(10-11):e983. doi:10.1002/ajp.22983

Brown, C. J., Quates, C. J., Mirabzadeh, C. A., Miller, C. R., Wichman, H. A., Miura, T. A., & Ytreberg, F. M. (2016). New Perspectives on Ebola Virus EvolutionPloS one11(8), e0160410. doi:10.1371/journal.pone.0160410

Bull, J. J., Christensen, K. A., Scott, C., Jack, B. R., Crandall, C. J., & Krone, S. M. (2018). Phage-Bacterial Dynamics with Spatial Structure: Self Organization around Phage Sinks Can Promote Increased Cell Densities. Antibiotics (Basel, Switzerland)7(1), 8. doi:10.3390/antibiotics7010008

Bull, J. J., Nuismer SL, Antia R. (2019). Recombinant vector vaccine evolutionPLoS Comput Biol. 2019;15(7):e1006857. Published 2019 Jul 19. doi:10.1371/journal.pcbi.1006857

Bull J. J., Remien, C. H., Gomulkiewicz, R., & Krone, S. M. (2019). Spatial structure undermines parasite suppression by gene drive cargoPeerJ. 2019;7:e7921. Published 2019 Oct 29. doi:10.7717/peerj.7921

Bull, J. J., Remien, C. H., & Krone, S. M. (2019). Gene-drive-mediated extinction is thwarted by population structure and evolution of sib mating. Evolution, medicine, and public health2019(1), 66–81. doi:10.1093/emph/eoz014

Buzbas, E. O., & Verdu, P. (2018). Inference on admixture fractions in a mechanistic model of recurrent admixture. Theoretical population biology122, 149–157. doi:10.1016/j.tpb.2018.03.006

Chiarelli, T. J., Grieshaber, N. A., Omsland, A., Remien, C. H., & Grieshaber, S. S. (2020). Single-Inclusion Kinetics of Chlamydia trachomatis DevelopmentmSystems5(5), e00689-20.

Crabtree, A. M., Kizer, E. A., Hunter, S. S., Van Leuven, J. T., New, D. D., Fagnan, M. W., & Rowley, P. A. (2019). A Rapid Method for Sequencing Double-Stranded RNAs Purified from Yeasts and the Identification of a Potent K1 Killer Toxin Isolated from Saccharomyces cerevisiaeViruses11(1), 70. doi:10.3390/v11010070

Damase, T. R., & Allen, P. B. (2019). Idiosyncrasies of thermofluorimetric aptamer binding assays. BioTechniques66(3), 121–127. Advance online publication. doi:10.2144/btn-2018-0128

Damase, T.R., & Allen, P.B. (2019). Designed and Evolved Nucleic Acid Nanotechnology: Contrast and Complementarity. Bioconjugate Chem, 30(1):2-12. doi:10.1021/acs.bioconjchem.8b00810

Damase, T. R., Ellington, A. D., & Allen, P.B. (2017). Purification of single-stranded DNA by co-polymerization with acrylamide and electrophoresis. BioTechniques, 62(6), 275-282. doi: 10.2144/000114557

Damase, T. R., Miura, T. A., Parent, C. E., & Allen, P. B. (2018). Application of the Open qPCR Instrument for the in Vitro Selection of DNA Aptamers against Epidermal Growth Factor Receptor and Drosophila C Virus. ACS combinatorial science20(2), 45–54. doi:10.1021/acscombsci.7b00138

Devezer, B., Nardin, L. G., Baumgaertner, B., & Buzbas, E. O. (2019). Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity. PloS one14(5), e0216125. doi:10.1371/journal.pone.0216125

Dutta, R., Xing, T., Swanson, C., Heltborg, J., & Murdoch, G. K. (2018). Comparison of flow and gas washout characteristics between pressure control and high-frequency percussive ventilation using a test lung. Physiological measurement39(3), 035001. doi:10.1088/1361-6579/aaaaa2

Faber MS, Van Leuven JT, Ederer MM, Sapozhnikov Y, Wilson ZL, Wichman HA, Whitehead TA, Miller CR. (2020). Saturation Mutagenesis Genome Engineering of Infective ΦX174 Bacteriophage via Unamplified Oligo Pools and Golden Gate AssemblyACS Synth Biol., 9(1):125-131. doi:10.1021/acssynbio.9b00411

Fan, H, Su, B, Ma, C., Rowley, P. A., & Jayaram, M. A Bipartite Thermodynamic-kinetic Contribution By an Activating Mutation to RDF-independent Excision By a Phage Serine IntegraseNucleic Acids Research, vol. 48, no. 12, 2020, pp. 6413-6430. doi:10.1093/nar/gkaa401

Ferguson, J. M., & Buzbas, E. O. (2018). Inference from the stationary distribution of allele frequencies in a family of Wright-Fisher models with two levels of genetic variability. Theoretical population biology122, 78–87. doi:10.1016/j.tpb.2018.03.004

Ferguson, J., Miura, T., & Miller, C. R. (2019). A two-stage experimental design for dilution assays. Biometrics. In press. 2019;75(3):1009-1016. doi:10.1111/biom.13032

Ferguson, J. M., Reichert, B. E., Fletcher, R. J., Jr, & Jager, H. I. (2017). Detecting population-environmental interactions with mismatched time series dataEcology98(11), 2813–2822. doi:10.1002/ecy.1966

Fredericks LR, Lee MD, Roslund CR, Crabtree AM, Allen PB, Rowley PA. The design and implementation of restraint devices for the injection of pathogenic microorganisms into Galleria mellonellaPLoS One. 2020;15(7):e0230767. Published 2020 Jul 30. doi:10.1371/journal.pone.0230767

Garry, D. J., Ellington, A. D., Molineux, I. J., & Bull, J. J. (2018). Viral attenuation by engineered protein fragmentation. Virus evolution4(1), vey017. doi:10.1093/ve/vey017

Gao F. (2019). A Probabilistic Characterization of Negative Definite FunctionsHigh dimensional probability74, 41–53.

Gao, F. C., & Lai, M. J. (2020). A New H2 Regularity Condition of the Solution to Dirichlet Problem of the Poisson Equation and Its ApplicationsActa mathematica Sinica, English series36(1), 21–39.

Gomulkiewicz, R., Krone, S. M., & Remien, C. H. (2017). Evolution and the duration of a doomed population. Evolutionary applications10(5), 471–484. doi:10.1111/eva.12467

Gonzalez, A. J., Ijezie, E. C., Balemba, O. B., & Miura, T. A. (2018). Attenuation of Influenza A Virus Disease Severity by Viral Coinfection in a Mouse Model. Journal of virology92(23), e00881-18. doi:10.1128/JVI.00881-18

Gonzalez, T. R., Martin, K. P., Barnes, J. E., Patel, J. S., & Ytreberg, F. M. (2020). Assessment of software methods for estimating protein-protein relative binding affinities. PloS one15(12), e0240573.

González-González, A., Hug, S. M., Rodríguez-Verdugo, A., Patel, J. S., & Gaut, B. S. (2017). Adaptive Mutations in RNA Polymerase and the Transcriptional Terminator Rho Have Similar Effects on Escherichia coli Gene Expression. Molecular biology and evolution34(11), 2839–2855. doi:10.1093/molbev/msx216

Hezarjaribi N, Dutta R, Xing T, Murdoch GK, Mazrouee S, Mortazavi BJ, Ghasemzadeh H. (2018). Monitoring Lung Mechanics during Mechanical Ventilation using Machine Learning Algorithms. Conference Proceeding IEEE, Engineering in Medicine and Biology Society, 2018, 1160-1163. doi: 10.1109/EMBC.2018.8512483

Hopkins, J. B., 3rd, Ferguson, J. M., Tyers, D. B., & Kurle, C. M. (2017). Selecting the best stable isotope mixing model to estimate grizzly bear diets in the Greater Yellowstone EcosystemPloS one12(5), e0174903. doi:10.1371/journal.pone.0174903

Issaka Salia, O., & Mitchell, D. M. (2020). Bioinformatic analysis and functional predictions of selected regeneration-associated transcripts expressed by zebrafish microgliaBMC genomics21(1), 870.

Justwan, F., Baumgaertner, B, Carlisle, J., Carson, E., & Kizer, J. (2019). The effect of trust and proximity on vaccine propensity. PloS one. 2019;14(8):e0220658. Published 2019 Aug 28. doi:10.1371/journal.pone.0220658

Justwan, F., Baumgaertner, B., Carlisle, J. E., Clark, A. K., & Clark, M. (2018). Social media echo chambers and satisfaction with democracy among Democrats and Republicans in the aftermath of the 2016 US elections. Journal of elections, public opinion and parties28(4), 424–442. doi:10.1080/17457289.2018.1434784

Krey, Karol L., Blubaugh Carmen K., Van Leuven, James T., Snyder, William E. (2019). Organic Soils Control Beetle Survival While Competitors Limit Aphid Population GrowthEnvironmental Entomology, 48(6), 1323–1330. doi:10.1093/ee/nvz100

Krey, K. L., Nabity, P. D., Blubaugh, C. K., Fu, Z., Van Leuven, J. T., Reganold, J. P., Berim, A., Gang, D. R., Jensen, A. S., & Snyder, W. E. (2020). Organic Farming Sharpens Plant Defenses in the FieldFrontiers in sustainable food systems4, 97.

Liao, Y., Vakanski, A., & Xian, M. (2020). A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesIEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(2):468-477. doi:10.1109/TNSRE.2020.2966249

Liao, Y., Vakanski, A., Xian, M., & Freer, P.E. (2020). A Review of Computational Approaches for Evaluation of Rehabilitation Exercises. Computers in Biology and Medicine, Volume 119, 103687.

Lee, J. A., Riazi, S., Nemati, S., Bazurto, J. V., Vasdekis, A. E., Ridenhour, B. J., … Marx, C. J. (2019). Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations. PLoS genetics15(11), e1008458. doi:10.1371/journal.pgen.1008458

Li, L., & Vakanski, A. (2018). Generative Adversarial Networks for Generation and Classification of Physical Rehabilitation Movement Episodes. International journal of machine learning and computing8(5), 428–436.

Majmudar, J., Krone, S., Baumgaertner, B., & Tyson, R. (2019). Voter Models and External Influence. The Journal of Mathematical Sociology. In press.

Martin, Kyle P., MacKenzie, Shannon M., Barnes, Jason W., & Ytreberg, F. Marty. (2020). Protein stability in Titan’s subsurface water ocean. Astrobiology, 20(2), 190-198. doi:10.1089/ast.2018.1972.

Miller, C. R., (2019). The treacheries of adaptation. Science, 366(6464), 418-419. doi:10.1126/science.aaz5189.

Miller, C. R., Johnson, E. L., Burke, A. Z., Martin, K. P., Miura, T. A., Wichman, H. A., Brown, C. J., Ytreberg, F. M. (2016). Initiating a watch list for Ebola virus antibody escape mutationsPeerJ4, e1674. doi:10.7717/peerj.1674

Miller, C. R., Van Leuven, J. T., Wichman, H. A., & Joyce, P. (2018). Selecting among three basic fitness landscape models: Additive, multiplicative and stickbreakingTheoretical population biology122, 97–109. doi:10.1016/j.tpb.2017.10.006

Mirabzadeh, C. A., & Ytreberg, F. M. (2020). Implementation of adaptive integration method for free energy calculations in molecular systemsPeerJ. Computer science6, e264.

Miura, Tanya. (2019). Respiratory Epithelial Cells as Master Communicators during Viral Infections. Current Clinical Microbiology Reports. 2019;6(1):10-17. doi:10.1007/s40588-019-0111-8

Musilova, Z., Cortesi, F., Matschiner, M., Davies, W. I. L., Patel, J.S., Stieb, S.M., de Busserolles, F., Malmstrøm, M., Tørresen, O. K., Brown, C. J., Mountford, J. K., Hanel, R., Stenkamp, D. L., Jakobsen, K.S., Carleton, K.L., Jentoft, S, Marshall, J., & Salzburger, W. (2019). Vision using multiple distinct rod opsins in deep-sea fishes. Science, 364(6440), 588-592. doi:10.1126/science.aav4632.

Nardin, L. G., Miller, C. R., Ridenhour, B. J., Krone, S. M., Joyce, P., & Baumgaertner, B. O. (2016). Planning horizon affects prophylactic decision-making and epidemic dynamics. PeerJ4, e2678. doi:10.7717/peerj.2678

Patel, D., Kuyucak, S., Doupnik, C.A. (2020). Structural determinants mediating tertiaphin block of neuronal Kir3.2 channels. Biochemistry, 59(7):836-850. doi:10.1021/acs.biochem.9b01098.

Patel, D., Barnes, J. E., Davies, W., Stenkamp, D. L., & Patel, J. S. (2020). Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbancePLoS computational biology16(10), e1008212.

Patel, J. S., Brown, C. J., Ytreberg, F. M., & Stenkamp, D. L. (2018). Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations. PLoS computational biology14(1), e1005974. doi:10.1371/journal.pcbi.1005974

Patel, J. S., Quates, C. J., Johnson, E. L., & Ytreberg, F. M. (2019). Expanding the watch list for potential Ebola virus antibody escape mutations. PloS one14(3), e0211093. doi:10.1371/journal.pone.0211093

Patel, J. S., & Ytreberg, F. M. (2018). Fast Calculation of Protein-Protein Binding Free Energies Using Umbrella Sampling with a Coarse-Grained Model. Journal of chemical theory and computation14(2), 991–997. doi:10.1021/acs.jctc.7b00660

Rowley, P. A., Patterson, K., Sandmeyer, S. B., & Sawyer, S. L. (2018). Control of yeast retrotransposons mediated through nucleoporin evolution. PLoS genetics14(4), e1007325. doi:10.1371/journal.pgen.1007325

Ridenhour, B. J., Brooker, S. L., Williams, J. E., Van Leuven, J. T., Miller, A. W., Dearing, M. D., & Remien, C. H. (2017). Modeling time-series data from microbial communitiesThe ISME journal11(11), 2526–2537. doi:10.1038/ismej.2017.107

Shareef, B., Xian, M., & Vakanski, A. (2020). STAN: SMALL TUMOR-AWARE NETWORK FOR BREAST ULTRASOUND IMAGE SEGMENTATIONProceedings. IEEE International Symposium on Biomedical Imaging2020, 1469–1473.

Suchar, V. A., Aziz, N., Bowe, A., Burke, A., & Wiest, M. M. (2018). An Exploration of the Spatiotemporal and Demographic Patterns of Ebola Virus Disease Epidemic in West Africa Using Open Access Data Sources. Applied geography (Sevenoaks, England)90, 272–281. doi:10.1016/j.apgeog.2017.10.003

Tyson, R., Baumgaertner, B., Hamilton, S., Lo, A., Krone, S. (2020). The timing and nature of behavioural responses affect the course of an epidemic. Bulletin of Mathematical Biology, Jan 14;82(1):14. doi:10.1007/s11538-019-00684-z.

Vakanski, A., Ferguson, J. M., & Lee, S. (2016). Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural NetworksJournal of physiotherapy & physical rehabilitation1(4), 118.

Vakanski, A., Ferguson, J. M., & Lee, S. (2017). Metrics for Performance Evaluation of Patient Exercises during Physical TherapyInternational journal of physical medicine & rehabilitation5(3), 403. doi:10.4172/2329-9096.1000403

Vakanski, A., Jun, H. P., Paul, D., & Baker, R. (2018). A Data Set of Human Body Movements for Physical Rehabilitation Exercises. Data3(1), 2. doi:10.3390/data3010002

Vakanski, A., Xian, M., & Freer, P.E. (2020). Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images.
Ultrasound in Medicine & Biology, 46(10): 2819-2833

Van Leuven, J. T., Mao, M., Xing, D. D., Bennett, G. M., & McCutcheon, J. P. (2019). Cicada Endosymbionts Have tRNAs That Are Correctly Processed Despite Having Genomes That Do Not Encode All of the tRNA Processing Machinery. mBio10(3), e01950-18. doi:10.1128/mBio.01950-18

Van Leuven, J. T., Ridenhour, B. J., Gonzalez, A. J., Miller, C. R., & Miura, T. A. (2017). Lung epithelial cells have virus-specific and shared gene expression responses to infection by diverse respiratory virusesPloS one12(6), e0178408. doi:10.1371/journal.pone.0178408

Vasdekis, A. E., Alanazi, H., Silverman, A. M., Williams, C. J., Canul, A. J., Cliff, J. B., Dohnalkova, A. C., Stephanopoulos, G. (2019). Eliciting the impacts of cellular noise on metabolic trade-offs by quantitative mass imaging. Nature communications10(1), 848. doi:10.1038/s41467-019-08717-w

Vasdekis, A. E., Silverman, A. M., & Stephanopoulos, G. (2017). Exploiting Bioprocessing Fluctuations to Elicit the Mechanistics of De Novo Lipogenesis in Yarrowia lipolyticaPloS one12(1), e0168889. doi:10.1371/journal.pone.0168889

Wang, H., Xian, M., & Vakanski, A. (2020). BENDING LOSS REGULARIZED NETWORK FOR NUCLEI SEGMENTATION IN HISTOPATHOLOGY IMAGESProceedings. IEEE International Symposium on Biomedical Imaging2020, 258–262.

Wichman, H. A., Scott, L. A., Howell, E. K., Martinez, A. R., Yang, L., & Baker, R. (2019) Flying around in the genome: characterization of LINE-1 in Chiroptera. Spec Publ Tex Tech Univ Mus. 2019;71:379-392.

Williams, C., Vakanski, A., Lee, S., Paul., D. (2019). Assessment of physical rehabilitation movements through dimensionality reduction and statistical modeling. Medical Engineering & Physics, Dec,74:13-22. doi:10.1016/j.medengphy.2019.10.003.

Yang, J., Naik, N., Patel, J. S., Wylie, C. S., Gu, W., Huang, J., Ytreberg, F. M., Naik, M. T., Weinreich, D. M., & Rubenstein, B. M. Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitnessPLoS One. 2020;15(5):e0233509. Published 2020 May 29. doi:10.1371/journal.pone.0233509

Yang, L., Scott, L., & Wichman, H. A. (2019). Tracing the history of LINE and SINE extinction in sigmodontine rodents. Mobile DNA10, 22. doi:10.1186/s13100-019-0164-5

Publications listed here were supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number P20GM104420. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.