Biology subjects

Eastman, P.

Publications and source records attributed to Eastman, P..

4 recordsLinked to original sources

bioRxiv2024

Community-Based Entomological Surveillance and Control of Vector-Borne Diseases: A Scoping Review

Community-based surveillance and control methods (CBMs) present opportunities to decentralize surveillance and control efforts while simultaneously enhancing community education, leadership, and participation in the fight against vector-borne diseases (VBDs). A scoping review was conducted to describe how CBMs are being utilized currently to combat malaria, dengue fever, Chagas disease, tick-borne diseases (TBDs) and other mosquito-borne diseases (MBD) exclusive of dengue and malaria, and to overall highlight key approaches, lessons learned, potential challenges, and recommendations. A total of 304 potential publications were identified among which 82 met the inclusion criteria. This scoping review highlighted the following benefits to CBMs: cost savings, increased sustainability, increased community knowledge, human behavior changes, increased surveillance coverage, ease in deployment, and the creation of larger, more diverse entomological datasets. Potential challenges highlighted include: participant retention and motivation, participant recruitment and incentives, continued governmental support, data quality, and collaboration with local municipal authorities. CBMs are commonly and successfully used in vector surveillance and control systems, but the chosen vector management method varies by vector-borne disease and region of the world. Additional research is needed to support the implementation of CBMs including cost-effectiveness studies and those studies with negative outcomes. Taken together, this scoping review highlights key aspects, potential challenges, and benefits of CBMs, and outlines potential future directions for incorporating CBMs into VBD control and elimination programming, and potential for community based integrated vector management (IVM) approaches.

scientific communication and education↗

bioRxiv2016

OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics

OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community.

biophysics↗

bioRxiv2016

MSMBuilder: Statistical Models for Biomolecular Dynamics

MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis of atomistic simulations of biomolecular dynamics such as protein folding and conformational change. MSMBuilder is named for its ability to construct Markov State Models (MSMs), a class of models that has gained favor among computational biophysicists. In addition to both well-established and newer MSM methods, the package includes complementary algorithms for understanding time-series data such as hidden Markov models (HMMs) and time-structure based independent component analysis (tICA). MSMBuilder boasts an easy to use command-line interface, as well as clear and consistent abstractions through its Python API (application programming interface). MSMBuilder is developed with careful consideration for compatibility with the broader machine-learning community by following the design of scikit-learn. The package is used primarily by practitioners of molecular dynamics but is just as applicable to other computational or experimental time-series measurements. http://msmbuilder.org

biophysics↗

bioRxiv2016

Energy Conservation as a Measure of Simulation Accuracy

Energy conservation is widely used as a measure of accuracy for molecular simulations. When reporting rates of energy drift, researchers usually assume it is linear in the simulation length, temperature, and system size. We study these assumptions and find that all three are incorrect. Energy drift is too complicated to characterize with a single number, and a more sophisticated analysis is needed to identify the effects of systematic versus random drift, and of integration error versus numerical error. We further argue that energy conservation is not a reliable measure of accuracy. Having small overall drift on long time scales is not a sufficient condition, and in some cases not a necessary condition, for a simulation to produce meaningful results.

biophysics↗