Aramayo Lab: People & Projects

The Aramayo Lab is an interdisciplinary research group in the Department of Biology at Texas A&M University. We integrate computational genomics, bioinformatics, and large language models to investigate molecular and evolutionary biology, with reproducibility as a core requirement throughout the research process.

Led by Rodolfo Aramayo, PhD, Associate Professor of Biology, the laboratory brings different biological questions together through a shared commitment to careful experimental reasoning, computational methods, and interpretable evidence.

Current graduate students

Graduate student

Brian White

Protein systems

Brian connects proteome-scale comparison with protein structure and dynamics. His work asks how sequence differences relate to the behavior of proteins as molecular systems.

Contribution to the lab. Extends the interpretation of protein variation from sequence scores toward structure, motion, and residue communication.

Explore Brian's projects

Composition-based comparative proteomicsTests amino-acid composition profiles as a screening layer for candidate reciprocal substitutions and phenotype-associated differences across proteome collections. Preliminary pipeline results guide broader analyses in progress.

Proteins as dynamic networksA manuscript in preparation connects structure prediction, molecular dynamics, allostery, and graph analysis to interpret proteins as communicating ensembles.

Mutation responses in human RNase 1An ongoing study compares AlphaFold3-derived and experimentally determined starting structures to ask whether similar static models yield different dynamic or residue-network responses to mutation. The manuscript, Dynamic Allostery as a Principal Arbiter of Amino Acid Residue Substitution in Human Pancreatic RNase 1 (White B, Aramayo R, 2026), is in preparation.

Public record: Proteins as Dynamic Networks →

Graduate student

Julen Gamboa

Circadian genomics

Julen investigates how natural genomic variation among inbred mouse strains relates to circadian behavior. His work connects organism-level measurements to gene structure and regulatory architecture.

Contribution to the lab. Connects comparative genomics to phenotype while examining annotation quality, controls, and alternative explanations.

Explore Julen's projects

Completed behavioral synthesisReconciled 260 circadian-relevant measurements from seven public studies into day-night behavioral profiles for 16 strains. Initial clustering produced no stable groupings, prompting a shift to within-strain effect estimates.

Comparative locus analysisOngoing work examines sequence conservation, locus architecture, and annotation quality across 28 circadian genes. Preliminary alignments nominate candidate differences for formal review.

Proposed regulatory integrationPhylogenetics, pangenome graphs, motif mapping, and DNA language models are proposed for testing whether coding, structural, and cis-regulatory variation helps explain behavioral differences.

Former undergraduate researchers

These projects contributed distinct analyses to the laboratory's research program. Findings below apply to the datasets studied.

Former undergraduate researcher · 2025 thesis

Daniel Nguyen

Isoform evolution

Predicting iso-orthology for human CARS1 isoforms

Daniel developed an isoform-level comparative framework for human cysteinyl-tRNA synthetase 1 and four nonhuman hominid species. His thesis identified conserved isoform-specific features and showed how incomplete annotations complicate orthology calls.

Methods and significance

He combined enhanced reciprocal-best-hit analysis with tissue-expression data, sequence alignment, coding-sequence comparison, and protein-domain annotation. The project moves comparative analysis beyond gene-level labels toward transcript and protein diversity. Proposed functional interpretations require experimental validation.

Texas A&M researcher spotlight →

Former undergraduate researcher · Public poster

Joseph Gallucci

Data quality

Auditing public next-generation sequencing submissions

Joseph audited 25 selected cancer-related human whole-genome datasets from the NCBI Sequence Read Archive. His work demonstrates why coverage and metadata need scrutiny before public data can support reproducible reanalysis.

Methods and findings

He extracted metadata and estimated coverage across sample runs in the randomly selected set. Eleven datasets exceeded 1× average coverage and six exceeded 4×. These findings describe the selected datasets and do not estimate the quality of the entire archive.

Read the public research poster →

Former undergraduate researcher · Research poster

Mariana Fauteux

Primate proteomics

Highly conserved proteins across primate species

Mariana compared proteomes from 26 primate species and reported 50 highly conserved protein clusters in the selected data. Her project connects comparative sequence analysis to questions about evolutionary constraint.

Methods and findings

The analysis combined 100% sequence-identity and full-length-coverage clustering with proteome-completeness assessment and protein-domain annotation. Histones, ribosomal proteins, and other strongly constrained functions were prominent. The findings depend on the selected proteomes, their annotations, and the stated thresholds.

Texas A&M researcher spotlight →

Mentoring and research culture

We practice biological reasoning, intellectual independence, reproducible workflows, and clear scientific communication. Students learn to turn public data and computational tools into an argument that distinguishes observations, interpretations, and hypotheses.

Ongoing studies and proposed analyses are labeled throughout these summaries. Public research records are linked where available.

Selected research Teaching & mentorship Public lab outputs