Bayesian Phylogenetic Analysis on Multi-Core Compute Architectures: Implementation and Evaluation of BEAGLE in RevBayes With MPI.

Phylogenies are central to many research areas in biology and commonly estimated using likelihood-based methods. Unfortunately, any likelihood-based method, including Bayesian inference, can be restrictively slow for large datasets-with many taxa and/or many sites in the sequence alignment-or complex substitutions models. The primary limiting factor when using large datasets and/or complex models in probabilistic phylogenetic analyses is the likelihood calculation, which dominates the total computation time.

Assessing a model of Pacific Northwest harmful algal bloom transport as a decision-support tool.

In the Pacific Northwest, blooms of the diatom Pseudo-nitzschia (PN) sometimes produce domoic acid, a neurotoxin that causes amnesic shellfish poisoning, leading to a Harmful Algal Bloom (HAB) event. The Pacific Northwest (PNW) HAB Bulletin project, a partnership between academic, government, and tribal stakeholders, uses a combination of beach and offshore monitoring data and ocean forecast modeling to better understand the formation, evolution, and transport of HABs in this region. This project produces periodic Bulletins to inform local stakeholders of current and forecasted conditions.

High-Performance Computing in Bayesian Phylogenetics and Phylodynamics Using BEAGLE.

In this chapter, we focus on the computational challenges associated with statistical phylogenomics and how use of the broad-platform evolutionary analysis general likelihood evaluator (BEAGLE), a high-performance library for likelihood computation, can help to substantially reduce computation time in phylogenomic and phylodynamic analyses. We discuss computational improvements brought about by the BEAGLE library on a variety of state-of-the-art multicore hardware, and for a range of commonly used evolutionary models. For data sets of varying dimensions, we specifically focus on comparing performance in the Bayesian evolutionary analysis by sampling trees (BEAST) software between multicore central processing units (CPUs) and a wide range of graphics processing cards (GPUs).

BEAGLE 3: Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics.

BEAGLE is a high-performance likelihood-calculation library for phylogenetic inference. The BEAGLE library defines a simple, but flexible, application programming interface (API), and includes a collection of efficient implementations for calculation under a variety of evolutionary models on different hardware devices. The library has been integrated into recent versions of popular phylogenetics software packages including BEAST and MrBayes and has been widely used across a diverse range of evolutionary studies.

Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10.

The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package has become a primary tool for Bayesian phylogenetic and phylodynamic inference from genetic sequence data. BEAST unifies molecular phylogenetic reconstruction with complex discrete and continuous trait evolution, divergence-time dating, and coalescent demographic models in an efficient statistical inference engine using Markov chain Monte Carlo integration. A convenient, cross-platform, graphical user interface allows the flexible construction of complex evolutionary analyses.

Acute and chronic dietary exposure to domoic acid in recreational harvesters: A survey of shellfish consumption behavior.

Domoic acid (DA) is a neurotoxin that is naturally produced by phytoplankton and accumulates in seafood during harmful algal blooms. As the prevalence of DA increases in the marine environment, there is a critical need to identify seafood consumers at risk of DA poisoning. DA exposure was estimated in recreational razor clam (Siliqua patula) harvesters to determine if exposures above current regulatory guidelines occur and/or if harvesters are chronically exposed to low levels of DA.

Prostatic paracoccidioidomycosis with a fatal outcome: a case report.

Introduction: Paracoccidioidomycosis is a systemic mycosis in Latin America that can affect various organs. Few case reports of paracoccidioidomycosis affecting the prostate are found in the literature.

Case Presentation: We present the case of a 79-year-old Caucasian man with a six-month history of irritative symptoms of the prostate (urgency, frequency and nocturia) and difficulty initiating urination that progressed to urinary retention and the use of a urinary catheter.

MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space.

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003.

Premature ejaculation: is there an efficient therapy?

Premature ejaculation is the most frequent male sexual dysfunction, estimated to affect 20 to 30% of men at some time in their life. A Pubmed search from the year 2000 to the present was performed to retrieve publications related to management or treatment of premature ejaculation. Behavioral techniques have been the mainstay of premature ejaculation management for many years, although evidence of their short-term efficacy is limited.

BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics.

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches.