BioSimulator.jl: Stochastic simulation in Julia

Biological systems with intertwined feedback loops pose a challenge to mathematical modeling efforts. Moreover, rare events, such as mutation and extinction, complicate system dynamics. Stochastic simulation algorithms are useful in generating time-evolution trajectories for these systems because they can adequately capture the influence of random fluctuations and quantify rare events. We present a simple and flexible package, BioSimulator.jl, for implementing the Gillespie algorithm, $\tau$-leaping, and related stochastic simulation algorithms. The objective of this work is to provide scientists across domains with fast, user-friendly simulation tools. We used the high-performance programming language Julia because of its emphasis on scientific computing. Our software package implements a suite of stochastic simulation algorithms based on Markov chain theory. We provide the ability to (a) diagram Petri Nets describing interactions, (b) plot average trajectories and attached standard deviations of each participating species over time, and (c) generate frequency distributions of each species at a specified time. BioSimulator.jl's interface allows users to build models programmatically within Julia. A model is then passed to the simulate routine to generate simulation data. The built-in tools allow one to visualize results and compute summary statistics. Our examples highlight the broad applicability of our software to systems of varying complexity from ecology, systems biology, chemistry, and genetics. The user-friendly nature of BioSimulator.jl encourages the use of stochastic simulation, minimizes tedious programming efforts, and reduces errors during model specification.Comment: 27 pages, 5 figures, 3 table

Mindfulness Training Supports Quality of Life and Advance Care Planning in Adults With Metastatic Cancer and Their Caregivers: Results of a Pilot Study

Background: Emotional distress often causes patients with cancer and their family caregivers (FCGs) to avoid end-of-life discussions and advance care planning (ACP), which may undermine quality of life (QoL). Most ACP interventions fail to address emotional barriers that impede timely ACP. Aim: We assessed feasibility, acceptability, and preliminary effects of a mindfulness-based intervention to facilitate ACP for adults with advanced-stage cancer and their FCGs. Design: A single-arm pilot was conducted to assess the impact of a 6-week group mindfulness intervention on ACP behaviors (patients only), QoL, family communication, avoidant coping, distress, and other outcomes from baseline (T1) to post-intervention (T2) and 1 month later (T3). Participants: Eligible patients had advanced-stage solid malignancies, limited ACP engagement, and an FCG willing to participate. Thirteen dyads (N = 26 participants) enrolled at an academic cancer center in the United States. Results: Of eligible patients, 59.1% enrolled. Attendance (70.8% across 6 sessions) and retention (84.6% for patients; 92.3% for FCGs) through T3 were acceptable. Over 90% of completers reported high intervention satisfaction. From T1 to T3, patient engagement more than doubled in each of 3 ACP behaviors assessed. Patients reported large significant decreases in distress at T2 and T3. Family caregivers reported large significant improvements in QoL and family communication at T2 and T3. Both patients and FCGs reported notable reductions in sleep disturbance and avoidant coping at T3. Conclusions: The mindfulness intervention was feasible and acceptable and supported improvements in ACP and associated outcomes for patients and FCGs. A randomized trial of mindfulness training for ACP is warranted

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

The idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17)

The 16th Data Release of the Sloan Digital Sky Surveys : First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).Peer reviewe

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

Simulation and Numerical Methods for Stochastic Processes

Stochastic processes and randomness are vital features of mathematical modeling in biology.Unfortunately analytical results are rarely available for even moderately complexstochastic processes leaving simulation and numerical techniques the main avenues of attack.We begin this work by exploring coupling bounds for birth-death processes, a fundamentaltype of stochastic process that describes how populations of individuals change overtime. By forming a coupling between a truncated version of the process and the originalunbounded version, we are able to compute both moments and transition probabilities forthe true process within an acceptable error bound. Second, we present an algorithm designframework for Interacting Particle Systems (IPSs). These are complex stochastic processeswith wide application to spatial phenomenon across many scientific disciplines. Here we describea method for efficiently sorting particles into classes based off of their type and spatialconfiguration in such a fashion that reduces the spatial simulation to that of a non-spatialwell-mixed process, albeit with a more complicated update step. This also allows us to applya large suite of well-developed stochastic simulation algorithms to IPSs with little additionalcoding cost. Third, we return to numerical methods, this time for multi-type branchingprocesses applied to gene therapy. We derive a series of ordinary differential equations thatgovern the evolution of the probability generating function and provide a straightforwardnumerical inversion approach to obtain marginalized probability distributions for probabilisticquantities of interest. We provide examples of our techniques applied to lentiviral genetherapy and the associated risk of oncogenesis in transplanted hematopoietic stem cell lines.Finally, we conclude with a chapter on future directions, both related to the previous threechapters as well as projects not previously addressed in this work

Simulation and Numerical Methods for Stochastic Processes

Stochastic processes and randomness are vital features of mathematical modeling in biology.Unfortunately analytical results are rarely available for even moderately complexstochastic processes leaving simulation and numerical techniques the main avenues of attack.We begin this work by exploring coupling bounds for birth-death processes, a fundamentaltype of stochastic process that describes how populations of individuals change overtime. By forming a coupling between a truncated version of the process and the originalunbounded version, we are able to compute both moments and transition probabilities forthe true process within an acceptable error bound. Second, we present an algorithm designframework for Interacting Particle Systems (IPSs). These are complex stochastic processeswith wide application to spatial phenomenon across many scientific disciplines. Here we describea method for efficiently sorting particles into classes based off of their type and spatialconfiguration in such a fashion that reduces the spatial simulation to that of a non-spatialwell-mixed process, albeit with a more complicated update step. This also allows us to applya large suite of well-developed stochastic simulation algorithms to IPSs with little additionalcoding cost. Third, we return to numerical methods, this time for multi-type branchingprocesses applied to gene therapy. We derive a series of ordinary differential equations thatgovern the evolution of the probability generating function and provide a straightforwardnumerical inversion approach to obtain marginalized probability distributions for probabilisticquantities of interest. We provide examples of our techniques applied to lentiviral genetherapy and the associated risk of oncogenesis in transplanted hematopoietic stem cell lines.Finally, we conclude with a chapter on future directions, both related to the previous threechapters as well as projects not previously addressed in this work