Allen G. Rodrigo

MutSimABC infers mutation and developmental parameters in long-lived trees using ABC, achieving accurate parameter recovery in simulations and application to Eucalyptus melliodora data.

This study characterizes the gut microbiome of velvet worms in Australian deadwood microhabitats, finding minimal spatial structuring and environmental influence over host-specific microbial associations.

This paper creates an artificial system with bidirectional DNA-music information flow to study evolutionary properties, finding that unidirectional inheritance is more error-resistant than Lamarckian inheritance.

The paper introduces an agent-based model to study holobiont dynamics, showing that multiple microbial generations per host generation can buffer environmental changes and reduce fitness trade-offs between hosts and microbes.

This study extends an agent-based model of host-microbiome evolution by incorporating resource provisioning, showing that host resource allocation depends on microbiome composition and environmental interactions.

NJGPT uses a large language model to construct phylogenetic trees from sequence data, offering a user-friendly interface but with limitations in handling large datasets and speed.

TaxonGPT uses generative AI to create taxonomic descriptions and keys, with error-checking to improve accuracy.

This study simulates how environmental microbial selection reduces microbial diversity in hosts and promotes beneficial host-microbe symbioses.

The paper introduces the MAST model for phylogenetic inference using concatenated alignments with multiple evolutionary histories, showing it can accurately recover tree parameters and detect incomplete lineage sorting and introgression.

AFPhyloMix reconstructs haplotype phylogenies from pooled short-read sequences without barcoding, achieving 80% accuracy for up to 15 haplotypes in simulations and real data.

This paper presents the first hybrid assembled genome of Eucalyptus polybractea using short- and long-read sequencing, achieving high contiguity and completeness.

This paper introduces a dynamic programming algorithm for improving DNA sequence assembly with very low coverage by updating the reference sequence dynamically, achieving better alignment and assembly quality.

HaploJuice improves haplotype assembly accuracy by estimating sub-sample proportions and using dynamic programming, outperforming existing methods on simulated and real data.