Publications that used computational resources at MARCC FY17  (101 publications) Disclaimer: very incomplete list

 

  1. Stevens, R. J.A.M., Martinez-Tossas, L. A., Meneveau, C. Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments. Renewable Energy. Submitted
  2. Martinez-Tossas, L. A., Churchfield, M., Meneveau, C. Optimal smoothing length scale foractuator line models of wind turbine blades. To appear in Wind Energy. Accepted.
  3. Howland, M. F., Bossuyt, J., Martinez-Tossas, L. A., Meyers, J., Meneveau, C. (2016).Wake structure in actuator disk models of wind turbines in yaw underuniform inflow conditions. Journal of Renewable and Sustainable Energy, 8(4). Published.
  4. Martinez-Tossas, L. A., Churchfield, M., Meneveau, C., A Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force. Projection. Munich: The Science of Making Torque from Wind (TORQUE 2016). Submitted.
  5. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control. Munich: The Science of Making Torque from Wind (TORQUE 2016). Submitted.
  6. Martinez-Tossas, L. A., Stevens, R. J.A.M., Meneveau, C. (2016)., Wind Turbine Large-Eddy Simulations on Very Coarse Grid Resolutions using an Actuator Line Model (pp. AIAA 2016-1261). San Diego, CA: 34th Wind Energy Symposium (2016), AIAA SciTech. Published
  7. Thomas, V., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, A Predictive Model for Wind Farms Using Dynamic Mode Decomposition, Abstract: G35.00002 in Session G35: Turbulence: Wakes, The American Physical Society, Portland, OR. (November 21, 2016).
  8. Bretheim, J., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, Extending the restricted nonlinear model for wall-turbulence to high Reynolds numbers, Abstract: G33.00001 in Session G33: Turbulent Boundary Layers: Walls and Modeling, The American Physical Society, Portland, OR. (November 21, 2016).
  9. Shapiro, C., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, A simple dynamic wake model for time dependent wind turbine yaw, Abstract: D2.00001 in Session D2: Wind Turbines: Simulations, The American Physical Society, Portland, OR. (November 20, 2016)
  10. Martinez-Tossas, L. A., Churchfield, M. J., Meneveau, C., 69th Annual Meeting of the APS Division of Fluid Dynamics, “An actuator line model simulation with optimal body force projection length scales, Abstract: D2.00003 at Session D2: Wind Turbines: Simulations,” The American Physical Society, Portland, OR. (November 20, 2016).
  11. Shapiro, C. (Presenter & Author), Meneveau, C. (Author Only), Gayme, D. (Author Only), 1000 Island Energy Research Forum, “Wind Farm Control for Power Grid Frequency Regulation,” Alexandria Bay, NY. (October 29, 2016).
  12. Martinez-Tossas, L. A., Churchfield, M. J., Meneveau, C., The Science of Making Torque from Wind (TORQUE 2016), “Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force Projection,” accepted for presentation, Munich, Germany. (October 5, 2016)
  13. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., The Science of Making Torque from Wind TORQUE 2016), “Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control,” accepted for presentation, Munich, Germany. (October 5, 2016)
  14. Bretheim, J., Meneveau, C., Gayme, D., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “A Restricted Nonlinear Large-Eddy Simulation Model For Wall-Bounded Turbulence,” Contributed talk, Montreal, Canada. (August 21, 2016).
  15. Meneveau, C., WindFarms in Complex Terrain, “Modeling boundary layer flow over fractal-like, multi-scale terrain in large eddy simulations,” Plenary Speaker, Euromech Colloquium, KTH, Stockholm, Sweden. (June 8, 2016).
  16. Bretheim, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “A Restricted Nonlinear Large Eddy Simulation Model for Turbulent Boundary Layers and Wind Farm Applications,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  17. Gayme, D., Meneveau, C., WindFarms 2016 Meeting, “Reduced order modeling for wind farm design and control,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  18. Thomas, V., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Reduced order models of wind farms using Dynamic Mode Decomposition,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  19. Shapiro, C., Meneveau, C., Gayme, D. (2016). A simple dynamic wake model for time dependent wind turbine yaw (abstract only)., Bulletin of the American Physical Society, Div. of Fluid Dynamics (20th ed., vol. 61, pp. 97). Published.
  20. C. J. Harman, A. S. Ward, and A. Ball (2016), How does reach-scale stream-hyporheic transport vary with discharge? Insights from rSAS analysis of sequential tracer injections in a headwater mountain stream, Water Resources Research, 52, 7130–7150, doi:10.1002/2016WR018832.
  21. Kim, M., L. Pangle, C. Cardoso, M. Lora, T. Volkmann, Y. Wang, C. J. Harman, and P. Troch (2016), Transit time distributions and StorAge Selection functions in a sloping soil lysimeter with time-varying flow paths: Direct observation of internal and external transport variability, Water Resources Research, 52, 7105–7129, doi:10.1002/2016WR018620.
  22. Deng D; Arevalo HJ; Prakosa A; Callans DJ; Trayanova N, A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction, Europace 
  23. Karathanos TV, Boyle PM, Trayanova N. Light-based approaches to cardiac arrhythmia research: From basic science to translational applications. Clin Med Insights Cardiol. 10(Suppl 1):47-60, 2016. 
  24. Chang KC, Trayanova N. Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation. Sci Rep Nov 4;6:36395. doi: 10.1038/srep36395, 2016
  25. Priest JR, Gawad C, Kahlig KM, Yu JK, O’Hara T, Boyle PM, Rajamani S, Clark MJ, Garcia ST, Ceresnak S, Harris J, Boyle S, Dewey FE, Malloy-Walton L, Dunn K, Grove M, Perez MV, Neff NF, Chen R, Maeda K, Dubin A, Belardinelli L, West J, Antolik C, Macaya D, Quertermous T, Trayanova N, Quake SR, Ashley EA. Early somatic mosaicism is a rare cause of long-QT syndrome, Proc Natl Acad Sci U S A. 113:11555-11560, 2016 (accompanied by a press release; story picked up bya number of national and international new outlets; featured video on PNAS webpage).
  26. Bruegmann T, Boyle PM, Vogt CC, Karathanos TV, Arevalo HJ, Fleischmann BK, Trayanova N, Sasse P. Optogenetic defibrillation terminates ventricular arrhythmia in mouse hearts and human simulations, J Clin Invest. 126:3894-3904, 2016 (accompanied by a press release and a video on YouTube and Facebook from JHU; story picked up by a number of national and international new outlets, including an interview by the Economist, and TV news by a number of TV channels around the country).
  27. HJ Arevalo, F Vadakkumpadan, E Guallar, A Jebb, P Malamas, KC Wu, N Trayanova. Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models. Nature Communications. May 10;7:11437. doi: 10.1038/ncomms11437, 2016 (accompanied by a press release from JHU; story picked up by over 60 national and international new outlets, including an article in the Guardian and an interview on BBC. Chosen as Nature’s featured article, and accompanied by a review in Nature Reviews Cardiology)
  28. Zahid S, Whyte KN, Schwarz EL, Blake RC 3rd, Boyle PM, Chrispin J, Prakosa A, Ipek EG, Pashakhanloo F, Halperin HR, Calkins H, Berger RD, Nazarian S, Trayanova N. Feasibility of using patient-specific models and the “minimum cut” algorithm to predict optimal ablation targets for left atrial flutter. Heart Rhythm. 13:1687-1698, 2016
  29. Trayanova N, Chang KC. How computer simulations of the human heart can improve anti-arrhythmia therapy. J Physiol. 594:2483-2502, 2016.
  30. Zahid S, Cochet H, Boyle PM, Schwarz EL, Whyte KN, Vigmond EJ, Dubois R, Hocini M, Haïssaguerre M, Jaïs P,  Trayanova N. Patient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern, Cardiovasc Res. 110(3):443-454, 2016
  31. Karathanos TV, PM Boyle, JD Bayer, D Wang, N Trayanova, Opsin Spectral Sensitivity Determines the Effectiveness of Optogenetic Termination of Ventricular Fibrillation in the Human Heart: A Simulation Study, J Physiol 2016 Mar 4. doi: 10.1113/JP271739. [Epub ahead of print]
  32. Ukwatta E, Arevalo H, Li K, Yuan J, Qiu W, Malamas P, Wu KC, Trayanova N, Vadakkumpadan F. Myocardial Infarct Segmentation from Magnetic Resonance Images for Personalized Modeling of Cardiac Electrophysiology, IEEE Trans 
  33. Stevens, R. J. A. M., Gayme, D. F., Meneveau, C. (2016). Generalized Coupled Wake Boundary Layer Model: Applications and Comparisons with Field and LES Datafor Two Real Wind-Farms. Wind Energy, 19(11). Published
  34. Stevens, R. J. A. M., Gayme, D., Meneveau, C. (2016). Effects of turbine spacing on the power output of extended wind-farms. Wind Energy, 19(2), 359-370. Published.
  35. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., Model-Based Receding Horizon Control of Wind Farms for Secondary Frequency Regulation. Proc. of the American Control Conference.
  36. Gayme, D. (2016)., Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control (5th ed., vol. 753, pp. 052012).
    Journal of Physics: Conference Series. Published.
  37. Gayme, D. (Guest Speaker), Offshore Wind IGERT Seminar Series, “New directions in wind farm modeling and control,” University of Massachusetts Amherst. (December 1, 2016). Invited.
  38. Gayme, D., 10th Annual Trans-Atlantic Infraday Conference, “Finding new markets for wind energy: Exploiting wind farm flow physics to enable more cost effective secondary frequency regulation with wind,” Federal Energy Regulatory Commission, Washington, DC. (November 10, 2016). Invited.
  39. Gayme, D. (Guest Speaker), Mechanical and Aerospace Engineering Colloquium, “The restricted nonlinear model: a minimal model for self-sustaining turbulence in wall bounded shear flows,” Cornell University, New York. (September 27, 2016). Invited.
  40. Gayme, D. (Guest Speaker), Department of Aerospace and Mechanical Engineering Seminar Series, “The Restricted Nonlinear System: A Minimal Model for Self-Sustaining Turbulence in Wall Bounded Shear Flows,” University of Notre Dame. (September 13, 2016). Invited.
  41. Gayme, D. (Presenter & Author), Thomas, V. (Author Only), Mini- Symposium on Bypass Transition, “Restricted Nonlinear Roll/Streak Dynamics in Plane Couette Flow,” 24th International Congress of Theoretical and Applied Mechanics (ICTAM), Montreal, Quebec. (August 22, 2016). Invited.
  42. Gayme, D. (Presenter & Author), Shapiro, C. (Author Only), Meyers, J. (Author Only), (Author Only), Symposium on Experiments and Simulations in Fluid Dynamics Research, “Model-based wind farm control for power grid frequency regulation,” Queens University, Kingston, ON, Candada. (August 19, 2016). Invited.
  43. Gayme, D. (Presenter Only), FREEDM Systems Center Special Seminar, “Management of energy resources for flexible and efficient power systems,” Electrical and Computer Engineering, North Carolina State University. (February 19, 2016). Invited.
  44. Thomas, V., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “A Predictive Model for Wind Farms Using Dynamic Mode Decomposition, Abstract: G35.00002 in Session G35: Turbulence: Wakes,” The American Physical Society, Portland, OR. (November 21, 2016).
  45. Bretheim, J., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “Extending the restricted nonlinear model for wall-turbulence to high Reynolds numbers, Abstract: G33.00001 in Session G33: Turbulent Boundary Layers: Walls and Modeling,” The American Physical Society, Portland, OR. (November 21, 2016).
  46. Shapiro, C., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “A simple dynamic wake model for time dependent wind turbine yaw, Abstract: D2.00001 in Session D2: Wind Turbines: Simulations,” The American Physical Society, Portland, OR. (November 20, 2016).
  47. Shapiro, C. (Presenter & Author), Meneveau, C. (Author Only), Gayme, D. (Author Only), 1000 Island Energy Research Forum, “Wind Farm Control for Power Grid Frequency Regulation,” Alexandria Bay, NY. (October 29, 2016).
  48. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., The Science of Making Torque from Wind (TORQUE 2016), “Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control,” accepted for presentation, Munich, Germany. (October 5, 2016).
  49. Bretheim, J., Meneveau, C., Gayme, D., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “A Restricted Nonlinear Large-Eddy Simulation Model For Wall-Bounded Turbulence,” Contributed talk, Montreal, Canada. (August 21, 2016).
  50. Stevens, R. J.A.M., Martinez-Tossas, L. A., Gayme, D., Meneveau, C., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “Simulation and modeling of extended wind farms,” Contributed talk,, Montreal, Canada. (August 21, 2016).
  51. Stevens, R. J. A. M. (Presenter & Author), Gayme, D. (Author Only), Meyers, J. (Author Only), Meneveau, C., EUROMECH Colloquium 576, Wind Farms in Complex Terrains, “LES Studies of Wind Farms Including Wide Turbine Spacings and Comparisons with the CWBL Engineering Model,” EUROMECH, KTH Royal Institute of Technology, Stockholm. (June 2016).
  52. Gayme, D. (Presenter & Author), Shapiro, C. (Author Only), Meyers, J. (Author Only), Meneveau, C. (Author Only), EUROMECH Colloquium 576, Wind Farms in Complex Terrains, “Using LES to Develop and Validate Model-Based Wind Farm Control,” EUROMECH, KTH Royal Institute of Technology, Stockholm. (June 2016).
  53. Bretheim, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “A Restricted Nonlinear Large Eddy Simulation Model for Turbulent Boundary Layers and Wind Farm Applications,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  54. Gayme, D., Meneveau, C., WindFarms 2016 Meeting, “Reduced order modeling for wind farm design and control,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  55. Thomas, V., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Reduced order models of wind farms using Dynamic Mode Decomposition,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  56. Shapiro, C., Bauweraerts, P., Meyers, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Model-based receding horizon control of wind farms for secondary frequency regulation,” The University of Texas at Dallas, Richardson, TX. (May 23, 2016).
  57. Mo A, Luo C, Davis FP, Mukamel EA, Henry GL, Nery JR, Urich MA, Picard S, Lister R, Eddy SR, Beer MA, Ecker JR, and Nathans J, Epigenomic landscapes of retinal rods and cones. eLife 5, e11613 (2016).
  58. Ghandi M, Mohammad-Noori M, Ghareghani N, Lee D, Garraway L, and Beer MA, gkmSVM, an R package for gapped-kmer SVM. Bioinformatics 10.1093/bioinformatics/btw203 (2016).
  59. Migeon BR, Beer MA, and Bjornsson HT, Embryonic loss of human females with partial trisomy 19 identifies region critical for the single active X. Plos ONE 12 (4), e0170403 (2017).
  60. Kreimer A, Zeng H, Edwards M, Guo Y, Tian K, Shin S, Welch R, Wainberg M, Mohan R, Sinnott-Armstrong N, Li Y, Amin T, Goke J, Mueller N, Kellis, M, Kundaje A, Beer MA, Keles S, Gifford D, and Yosef N, Predicting Gene Expression in Massively Parallel Reporter Assays: A Comparative Study. Human Mutation (2017).
  61. Cheng CS, Gate RE, Siba A, Tabaka M, Lituiev D, Subramaniam M, Hougen KL, Shamim M, Wortman I, Aiden AP, Machol I, Feng T, De Jager PL, Chang H, Lieberman Aiden E, Benoist C, Beer MA, Ye CJ, Regev A, Genetic determinants of chromatin accessibility and gene regulation in T cell activation across human individuals, Nature Genetics under review, bioRxiv, 090241 (2017).
  62. Beer MA, Predicting Enhancer Activity and Variant Impact using gkm-SVM.  Human Mutation (2017).
  63. Xie F and Xu Y#, NDPP-Mix: Nested Dirichlet Process-Determinantal Point Process Mixture Model. Submitted
  64. Li Y, Dinalankara W, Marchionni L, Kochel C, Nirschl T, Drake C, and Xu Y#, BayRepulsive: A Bayesian Repulsive Deconvolution Model for Inferring Tumor Heterogeneity. Submitted 
  65. Xie F and Xu Y#, Bayesian Repulsive Gaussian Mixture Model. Submitted 
  66. Xie F, Zhou M, and Xu Y#, BayCount: A Bayesian Decomposition Method for Inferring Tumor Heterogeneity using RNA-Seq Counts. Submitted 
  67. Xu Y, Xu Y, and Saria S, Bayesian Estimation of Individualized Treatment-Response Curves in Populations with Heterogeneous Treatment Effects. Journal ofMachine Learning Research. In Press.
  68. Xu Y, Xu Y, and Saria S, A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series. Proceedings of the 1st Machine Learning for Healthcare Conference. 2016, 282-300. 
  69. DiPietro, Robert, et al. “Recognizing surgical activities with recurrent neural networks.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer International Publishing, 2016.
  70. DiPietro, Robert, Christian Rupprecht, Nassir Navab, and Gregory D. Hager. “Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies.” arXiv preprint arXiv:1702.07805 (2017).
  71. Chi Li, Han Xiao, Keisuke Tateno, Federico Tombari, Nassir Navab, and Gregory D Hager. Incremental scene understanding on dense slam. In International Conference on Intelligent Robots and Systems (IROS), 2016
  72. Chi Li, Jonathan Boheren, Eric Carlson, and Gregory D Hager. Hierarchical semantic parsing for object pose estimation in densely cluttered scenes. In International Conference on Robotics Automation (ICRA), 2016
  73. Chi Li, Austin Reiter, and Gregory D Hager. Beyond spatial pooling: Fine-grained representation learning in multiple domains. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 4913–4922, 2015
  74. Chi Li, Jonathan Boheren, and Gregory D Hager. Bridging the robot perception gap with mid-level vision. In International Symposium on Robotics Research (ISRR), 2015
  75. Chi Li, Le Lu, Gregory D Hager, Jianyu Tang, and Hanzi Wang. Robust object tracking in crowd dynamic scenes using explicit stereo depth. In Asian Conference on Computer Vision (ACCV), pages 71–85. Springer, 2012
  76. Billings S.D. et al. (2016) Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm. In: Ourselin S., Joskowicz L., Sabuncu M., Unal G., Wells W. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2016. MICCAI 2016. Lecture Notes in Computer Science, vol 9902. Springer, Cham 16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
  77. Luo, R, Schatz, MC, Salzberg, SL (2017) GigaScience doi: https://doi.org/10.1093/gigascience/gix045
  78. Cerizza, D., Sekiguchi, W., Tsukahara, T., Zaki, T., Hasegawa, Y. (2016). Reconstruction of scalar source intensity based on sensor signal in turbulent
    channel flow. Flow, Turbulence & Combustion!!!, 97(4), 1211–1233. Published.
  79. Lee, J., Zaki, T. Video: A computational laboratory for the study of transitional and turbulent boundary layers., 68th Annual Meeting of the APS Division of Fluid Dynamics – Gallery of Fluid Motion. American Physical Society (APS). Published
  80. Zaki, T., Big Data Joint Workshop, “A Big-Data Computational Laboratory for the Optimization of Olfactory Search Algorithms in Turbulent Environments, Japan Science and Technology Agency and National Science Foundation, Tokyo, Japan. (2016). Invited.
  81. Zaki, T., CSME International Congress, “High-fidelity simulations and predictive theory of boundary-layer transition, The Canadian Society for Mechanical Engineers (CSME), Kelowna, Canada. (June 2016). Invited.
  82. Zaki, T., “Boundary layer transition beneath free-stream turbulence: Linear precursors of nonlinear breakdown, Fluid Mechanics Unit, Okinawa Institute of Technology, Japan. (May 2016). Invited.
  83. Zaki, T., “Primary and secondary instabilities of transitional boundary layers beneath free-stream turbulence, Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Japan. (May 2016). Invited.
  84. Zaki, T., “Linear analysis and nonlinear simulations of boundary-layer transition,” Department of Mechanical Engineering, University of Texas at Dallas. (March 2016). Invited.
  85. Wang, Q., Hasegawa, Y., Meneveau, C., Zaki, T., 69th Annual Meeting of the APS Division of Fluid Dynamics, Adjoint-optimization algorithm for spatial reconstruction of a scalar source, Abstract: L7.00008 in Session L7: Flow Control: Feedback, System and Model Identification,”” The American “Physical Society, Portland, OR. (November 21, 2016).”
  86. Lee, J., Zaki, T., 24th ICTAM Conference, “Turbulent/non-turbulent interface in transitional and turbulent boundary layers, The International Congress of Theoretical and Applied Mechanics, Montreal, Canada. (August 2016).
  87. Nicolaou, L., Materials for Extreme Dynamic Environments – Army Cooperative Research Agreement, Microme- chanical Model of the Rate-dependent and Temperature-dependent of Highly Oriented Polyethy- lene Fibers, 1/1/2014 – 12/1/2017, $283,504, PI: T. D. Nguyen.
  88. Cereceda, D., Graham-Brady, L. & Daphalapurkar, N. (2017). “Modeling dynamic fragmentation of heterogeneous structural materials,” International Journal of Impact Engineering, 99:85-101.
  89. Cereceda, D., Kats, D., Daphalapurkar, N. & Graham-Brady, L. (2017). “A
    micro-mechanical modeling approach for dynamic fragmentation in brittle
    multi-phase materials,” International Journal of Solids & Structures,
    under review.
  90. Bhaduri, A. & Graham-Brady, L. (2017). “A gradient based adaptive sparse grid collocation method for uncertainty propagation,” Probabilistic Engineering Mechanics, under review.
  91. Preheim SP, Olesen SW, Spencer SJ, Materna A, Varadharajan C, Blackburn M, Friedman  J, Rodriguez J, Hemond H and Alm EJ. 2016. Surveys, simulation, and single-cell assays relate function and phylogeny in a natural ecosystem. Nature Microbiology 1:16130
  92. Nellore A, Jaffe AE, Fortin JP, Alquicira-Hernández J, Collado-Torres L, Wang S, Phillips RA, Karbhari N, Hansen KD, Langmead B, Leek JT. Human splicing diversity and the extent of unannotated splice junctions across human RNA-seq samples on the Sequence Read Archive . Genome Biology. 2016, 17:266.
  93. Nellore A, Collado-Torres L, Jaffe AE, Alquicira-Hernández J, Wilks C, Pritt J, Morton J, Leek JT, Langmead B. Rail-RNA: Scalable analysis of RNA-seq splicing and coverage. Bioinformatics. 2016 Sep 4. Advance access.
  94. Nellore A, Wilks C, Hansen KD, Leek JT, Langmead B. Rail-dbGaP: analyzing dbGaP-protected data in the cloud with Amazon Elastic MapReduce. Bioinformatics. 2016 Aug 15;32(16):2551-3.
  95. Langmead B. A tandem simulation framework for predicting mapping quality. bioRxiv doi: 10.1101/103952. (In press at Genome Biology)
  96. Wilks C, Gaddipati P, Nellore A, Langmead B. Snaptron: querying and visualizing splicing across tens of thousands of RNA-seq samples. bioRxiv doi: 10.1101/097881. (In revision at Bioinformatics)
  97. D. Raciti, L. Cao, K.  J. T. Livi, P. F. Rottmann, X. Tang, C. Li, Z. Hicks, Kit H. Bowen , K.  J. Hemker, T. Mueller, and C. Wang,Low-Overpotential Electroreduction of Carbon Monoxide Using Copper Nanowires” ACS Catalysis 2017, 4467–4472 (2017)  http://dx.doi.org/10.1021/acscatal.7b01124
  98. L. Cao and T. Mueller, “Theoretical Insights into the Effects of Oxidation and Mo-Doping on the Structure and Stability of Pt–Ni Nanoparticles” Nano Letters 16, 7748–7754 (2016).
    http://dx.doi.org/10.1021/acs.nanolett.6b03867
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  102. Y. Wang, A. J. Sierakowski, and A. Prosperetti. Fully-resolved simulation of particulate flows with particles-fluid heat transfer. J. Comp. Phys. 350 (2017) 638-656. doi.org/10/1016/j.jcp.2017.07.44