Rice’s dean of engineering and computing building new software infrastructure for evolutionary biology

(Press-News.org) Rice University computer scientist Luay Nakhleh, who also serves as the dean of the George R. Brown School of Engineering and Computing, has received a $1.9 million grant from the National Science Foundation to build a powerful new software infrastructure that could significantly expand how scientists study evolution. The project, titled PhyNetPy, aims to bring the next generation of evolutionary modeling tools into the hands of researchers around the world by enabling the widespread use of phylogenetic networks — complex, nontreelike models of evolutionary history.

“For decades, biology has relied on phylogenetic trees to study evolutionary relationships, but those models fall short in many real-world scenarios,” Nakhleh said. “Processes like hybridization, gene flow and horizontal gene transfer don’t fit neatly on a tree. Phylogenetic networks are essential for capturing the full picture.”

While thousands of tools and libraries exist for phylogenetic tree analysis, comparable resources for phylogenetic networks are scarce and fragmented. PhyNetPy aims to be the first open-source, general-purpose Python library designed specifically for network-based evolutionary modeling.

“Our goal is to create the kind of software ecosystem for networks that already exists for trees,” Nakhleh said. “That means not just inference tools but also robust data structures, simulation engines, visualization capabilities and a user-friendly interface. We want to lower the barrier to entry, so more biologists — and computer scientists — can use and build on these models.”

The project is designed with broad compatibility in mind, enabling interoperability with tools like DendroPy, ETE Toolkit and Biopython. It also promises seamless cloud deployment, so users can access powerful analytical tools without needing to install or configure complicated software.

Traditional tree models assume evolution is strictly branching with species splitting and never merging again. But in reality, evolutionary history is often tangled. Hybridization in plants, gene flow in animals and horizontal gene transfer in bacteria all create reticulate patterns that look more like webs than trees.

“More than 25% of plant species are of hybrid origin,” Nakhleh said. “In agriculture, this has huge implications. For example, hybrid crops can outperform their parents, a phenomenon known as hybrid vigor. Understanding how that happens at the genomic level requires network models.”

Even in animals, hybridization occurs.

“Studies suggest that at least 10% of animal species have experienced hybridization,” Nakhleh said. “Without networks, we’re missing critical insights into how evolution works.”

One of PhyNetPy’s most ambitious goals is to unite the phylogenetics and population genetics communities, which have traditionally used different languages and models to study similar phenomena. Phylogeneticists typically speak of “networks,” while population geneticists often talk of “graphs,” including ancestral recombination graphs or admixture graphs. Despite their different names, these structures can be mathematically equivalent.

“By providing a unified framework, we hope to bridge the gap between these two communities,” Nakhleh said. “If we can get more researchers using shared tools and terminology, it will accelerate discovery across the board.”

The five-year NSF-funded project is structured around five technical thrusts, including data structures, inference algorithms, simulation tools, network characterization methods and visualization capabilities. Nakhleh and his team will also reimplement and expand many of the successful methods from his earlier project, PhyloNet, to make them more scalable, user-friendly and ready for the cloud. The project will also include education and outreach efforts with undergraduate and graduate students contributing to PhyNetPy’s development and its use integrated into courses at Rice. As with Nakhleh’s previous tools, the entire PhyNetPy platform will be open-source and freely available to the scientific community.

“This isn’t just about building software; it’s also about building a community,” he said. “We want PhyNetPy to be a platform where researchers can contribute new methods, share ideas and collaborate to push the boundaries of evolutionary science.”

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