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Institute for Computational and Experimental Research in Mathematics (ICERM)

This semester program brings together mathematicians, statisticians, computer scientists, and experimental biologists to address the challenges involved in genome-scale phylogenetic inference. An overarching goal is to unite biologically-sound modeling with algorithms that can be implemented in a computationally tractable manner and that scale as both the number of species and the amount of genetic data increase. Specific topics to be investigated include: theory and practice of model-based inference for trees and networks, combinatorial and algebraic approaches for inferring phylogenies, software and algorithm development for inference and visualization, Bayesian approaches to phylogenetic inference, models for phylogenetic diversity and node dating, and methods for assessing model fit.

ICERM;     Email.: info@icerm.brown.edu

biology, computation, genomic data, phylogenomics, software development, algorithm development

Institute for Computational and Experimental Research in Mathematics (ICERM)

Computational phylogenetic methods have become essential tools for understanding the evolutionary relationships that underlie much life science research. Motivated by biological questions and insights, built on a broad spectrum of mathematical and statistical ideas and approaches, and implemented through novel and sophisticated algorithmic design, their development draws from multiple fields. Bringing together researchers spanning disciplinary perspectives and techniques, this workshop will present a diverse sample of work addressing current challenges in phylogenetics, with an eye toward future progress.

ICERM;     Email.: info@icerm.brown.edu

phylogenetics, statistics, mathematics, computation

Institute for Computational and Experimental Research in Mathematics (ICERM)

The unprecedented amount of genomic data that has become readily available presents specific challenges for the field of phylogenetic inference, which is concerned with estimating the evolutionary relationships among collections of species, populations, or sequences. These challenges include the development of evolutionary models that are sufficiently complex to be biologically realistic while remaining computationally tractable; deriving and implementing algorithms to efficiently estimate phylogenetic relationships that use models whose theoretical properties are well-understood and therefore interpretable; and devising ways to scale novel methodology developed to handle datasets that are increasingly large and complex. This workshop focuses on statistical modeling and the scaling of phylogenetic methods. Topics will include modeling (e.g. multispecies coalescent model with extension to networks; diversification models) and inference with speed to scale to genomic datasets, consistency, and robustness using statistical, combinatorial, and algebraic approaches. This workshop will present the latest advances in these areas and serve as a forum to spark new ideas and collaborations.

ICERM;     Email.: info@icerm.brown.edu

statistical modeling, phylogenetics, combinatorics, algebra

Institute for Computational and Experimental Research in Mathematics (ICERM)

In this workshop, we will consider challenges and best practices in translating theory to software for phylogenetic inference. We will discuss strategies adopted by the tool development community, their relative advantages, and lessons learned through software development. We will discuss a variety of objective functions (parametric and non-parametric) and algorithmic techniques used by inference methods. We will cover parallelization and how it interacts with the choice of objective function and algorithmic technique. Finally, we will discuss best practices for evaluating new and existing software tools, not just to validate the implementation but also to study accuracy and scalability in relation to theory and usage in realistic bioinformatics pipelines. In addition to discussing how theory influences tools, we will examine how tool development can inform the theoretical questions asked.

ICERM;     Email.: info@icerm.brown.edu

bioinformatics, phylogenetic inference, software development