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Past NIMBioS Postdoctoral Fellow

Daniel Ryan

D. Ryan photo. Dates: August 2011 – June 2014
Project Title: Investigating the effects of movement strategies on the population dynamics of multi-trophic ecological communities

Daniel Ryan (Ph.D. Mathematics, Univ. of Miami, 2011) investigated the role of non-random dispersal strategies in ecological systems and the effects of these dispersal strategies on species distribution and community composition. Ryan used various types of models, including partial differential equations, integro-differential equations (for kernel based dispersal schemes), and individual based models. The models were used to investigate questions about evolutionary stability of movement strategies, stability of coexistence states in multi-trophic communities, and the effects of inhomogeneous environments on species distributions.

Additional work completed during the NIMBioS postdoctoral fellowship included two computationally-focused side projects. The first project developed an algorithm for the in silico design of a specialized library of gene variants that systematically vary codon usage patterns by synonymous substitution. The resulting library of genes should be useful to experimentally test hypotheses about the effects of codon usage bias on gene expression. The library is designed so that it can be assembled in a simultaneous, combinatorial fashion via Gibson Isothermal Assembly. This results in huge savings compared to assembling each gene in the library separately.

The second project used a neural network model to predict mortality risk for intensive care unit (ICU) patients in a hospital. The model takes information collected about the patients in the first 48 hours for their stay in the ICU and uses this to predict a risk of mortality for the remainder of their stay in the hospital. Accurate risk assessment for incoming patients can help to improve both quality of care and improve evaluation of treatment effectiveness.

Following his postdoctoral fellowship, Ryan took a position as a database administrator.

NIMBioS Seminar: Non-random dispersal in intraguild predation communities

Feature Story: Measures of movement: Postdoc explores behavior of movement

Video Interview: Measures of movement

Publications while at NIMBioS

Ryan D, Cantrell RS. 2015. Avoidance behavior in intraguild predation communities: A cross-diffusion model. Discrete and Continuous Dynamical Systems, 35(4): 1641-1663.

Cantrell RS, Cosner C, Lou Y, Ryan D. 2012. Evolutionary stability of ideal free dispersal strategies: A nonlocal dispersal model. Canadian Applied Mathematics Quarterly, 20(2012): 15-38. [Online]

Federico P, Gross LJ, Lenhart S, Ryan D. 2013. Optimal control in individual-based models: Implications from aggregated methods. The American Naturalist, 181(1): 64-77. [Online]

Ryan D, Cantrell RS. Avoidance Behavior in Intraguild Predation Communities: A Cross-diffusion Model. Submitted.

Ryan D, Daley BJ, Wong K, Zhao X. 2013. Prediction of ICU in-hospital mortality using a deep Boltzmann machine and dropout neural net. Proceedings of the Biomedical Sciences and Engineering Conference (BSEC). [Online]

Ryan D, Papamichail D. 2013. Rational design of orthogonal libraries of protein coding genes. ACS Synthetic Biology, 2(5): 237-244. [Online]

Presentations while at NIMBioS

Ryan D. 22 May 2014. Deriving Discrete Adjoint Equations for the Numerical Solution of Optimal Control Problems with Higher Order Integrators. NIMBioS Seminar, University of Tennessee, Knoxville

Ryan D. 23 May 2013. Prediction of ICU In-hospital Mortality Using a Deep Boltzmann Machine and Dropout Neural Net, ORNL Biomedical Sciences and Engineering Conference

Ryan D. 1 March 2013. An Introduction to Deep Learning Biomedical Engineering Student Seminar on Machine Learning, University of Tennessee, Knoxville

Ryan D. 26 July 2012. A Cross-diffusion Model for Avoidance Behavior in an Intraguild Predation Community, Annual Meeting of the Society for Mathematical Biology, Knoxville, Tennessee

Ryan D. 23 July 2012. Numerical Solution of Optimal Control Problems, NIMBioS Seminar, University of Tennessee, Knoxville

Ryan D. 3 July 2012. A Cross-diffusion Model for Avoidance Behavior in an Intraguild Predation Community, 9th AIMS Conference on Dynamical Systems, Differential Equations and Applications, Orlando, FL

Ryan D. 11 October 2011. Nonrandom Dispersal in Intraguild Predation Communities, NIMBioS Seminar University of Tennessee, Knoxville

Ryan D. 12 September 2011. Modeling Avoidance Strategies for Intraguild Prey – Cross-diffusion PDE Systems, Differential Equations and Computational Math Seminar, University of Tennessee, Knoxville

Collaborations, Working Groups, and Workshops

Participant. NIMBioS Working Group: Pretty Darn Good Control

Participant. NIMBioS Investigative Workshop: Disturbance Regimes and Climate-Carbon Feedback

Participant. Challenges in Representation Learning Workshop, Atlanta, GA, 2013

Participant. Machine Learning for System Identification Workshop, Atlanta, GA, 2013

Participant. Deep Learning for Audio, Speech, and Language Processing Workshop, Atlanta, GA, 2013

Participant. Everything Disperses to Miami Workshop, Miami, FL, 2012

Participant. Workshop 5: Spatial Models of Micro and Macro Systems, Mathematical Biosciences Institute Workshop, Columbus, OH, 2012

Established collaborations with Xiaopeng Zhao (UTK Biomedical Engineering) and Calistus Ngonghala (former NIMBioS postdoc), both of which are ongoing

Education, Outreach and Training

Mentored students during the 2012 NIMBioS REU program

Assisted with labs during the 2013 NIMBioS-MBI-CAMBAM graduate summer program

Presented a talk for undergraduates at Fisk University: A Survey of Mathematical Models in Spatial Ecology, Mathematics Dept. Seminar, March 29, 2012

Attended NIMBioS Postdoc Career Development Seminars, NIMBioS Interdisciplinary Seminars, UTK Math Department Seminars and CISML Seminars at UTK.

Participated in informal NIMBioS course on agent-based models

Main NIMBioS Postdoc page

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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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