Alistair Turcan
Alistair Turcan

Alistair Turcan

Computational Biology · Carnegie Mellon University

aturcan@cs.cmu.edu [Google Scholar] [Website] [CV]

I develop statistical and machine-learning methods for large-scale genomic data, with a focus on connecting genetic variation to disease mechanisms at cellular resolution.

I then build agentic AI systems that automate key parts of this process, such as method development, code optimization, and benchmark design.

Research interests

Statistical genetics.
Genetic architecture of diseases and complex traits; functional interpretation of GWAS variants; linking variants to target genes and cell types.
Agentic AI for biology.
AutoResearch; biomedical agents; AI code optimization.

Papers

Google Scholar ↗

* Equal contribution. † Co-senior authors.

Key-author publications

  1. Conditional polygenic enrichment distinguishes causal from tagging disease-critical cell populations in single-cell RNA-seq. [paper]

    Alistair Turcan, Kangcheng Hou, Kevin Z. Lin, Andreas Pfenning, Saori Sakaue, Martin Jinye Zhang.

    medRxiv, 2026. Under review at Nature Genetics.

    Related abstract awarded ASHG 2024 Reviewers’ Choice (Top 10%); related research awarded a $150,000 Center for Machine Learning and Health fellowship.

  2. Towards automated development of computational biology methods.

    Alistair Turcan, Elizabeth Dorans, Kangcheng Hou, Jane Siwek, Jishnu Das, Maria Chikina, Luca Pinello, Alkes Price, Lei Li, Kexin Huang, Martin Jinye Zhang.

    In preparation.

    Related abstract awarded ASHG 2026 Reviewers’ Choice (Top 10%). Currently deployed on Biomni Lab, used by 100+ researchers and several top pharma companies.

  3. Recovering cell-type specific variation in RNA-seq data.

    Martin Jinye Zhang*, Kangcheng Hou*, Alistair Turcan*, Alkes Price.

    In preparation.

  4. TusoAI: Agentic Optimization for Scientific Methods. [paper]

    Alistair Turcan, Kexin Huang, Lei Li, Martin Jinye Zhang.

    ICLR, 2026.

  5. SpatialEpiBench: Benchmarking Spatial Information and Epidemic Priors in Forecasting. [paper]

    Ruiqi Lyu*, Alistair Turcan*, Bryan Wilder.

    NeurIPS, 2026.

  6. Improving constraint-based discovery with robust propagation and reliable LLM priors. [paper]

    Ruiqi Lyu*, Alistair Turcan*, Martin Jinye Zhang†, Bryan Wilder†.

    NeurIPS, 2026.

  7. Explaining Concept Shift with Interpretable Feature Attribution. [paper]

    Ruiqi Lyu, Alistair Turcan, Bryan Wilder.

    ICML, 2026.

  8. Population-Robust Feature Selection via Generalized Welfare Optimization. [paper]

    Ruiqi Lyu, Alistair Turcan, Bryan Wilder.

    arXiv, 2026.

  9. Combining digital data streams and epidemic networks for real time outbreak detection. [paper]

    Ruiqi Lyu, Alistair Turcan, Bryan Wilder.

    arXiv, 2025. Under revision at PNAS.

  10. Integrative Detection of Genome-wide Translation using iRibo. [paper]

    Alistair Turcan, Jiwon Lee, Aaron Wacholder, Anne-Ruxandra Carvunis.

    STAR Protocols, 2024.

  11. Exhaustive In-silico Simulation of Single Amino Acid Insertion and Deletion Mutations. [paper]

    Alistair Turcan, Grant Chou, Lilu Martin, Theo Miller, Dylan Thompson, Filip Jagodzinski.

    IEEE BIBM, 2022.

  12. Elucidating the Structural Impacts of Protein InDels. [paper]

    Muneeba Jilani, Alistair Turcan, Nurit Haspel, Filip Jagodzinski.

    Biomolecules, 2022.

  13. Assessing the Effects of Amino Acid Insertion and Deletion Mutations. [paper]

    Muneeba Jilani, Alistair Turcan, Nurit Haspel, Filip Jagodzinski.

    IEEE BIBM, 2021.

  14. CGRAP: A Web Server for Coarse-Grained Rigidity Analysis of Proteins. [paper]

    Alistair Turcan, Anna Zivkovic, Dylan Thompson, Lorraine Wong, Lauren Johnson, Filip Jagodzinski.

    Symmetry, 2021.

Other publications

  1. SkillFoundry: Building Self-Evolving Agent Skill Libraries from Heterogeneous Scientific Resources. [paper]

    Shuaike Shen, Wenduo Cheng, Mingqian Ma, Alistair Turcan, Martin Jinye Zhang, Jian Ma.

    COLM, 2026.

  2. Genetic and Cellular Architecture of Breast Cancer Risk in Multi-Ancestry Studies of 159,297 Cases and 212,102 Controls. [paper]

    James L. Li, Maria Zanti, Jacob Williams, Om Jahagirdar, Guochong Jia, Alistair Turcan, …, Haoyu Zhang.

    JNCI, 2025.

  3. Predicting Language Models' Success at Zero-Shot Probabilistic Prediction. [paper]

    Kevin Ren, Santiago Cortes-Gomez, Carlos Miguel Patiño, Ananya Joshi, Ruiqi Lyu, Jingjing Tang, Alistair Turcan, Khurram Yamin, Steven Wu, Bryan Wilder.

    Findings of EMNLP, 2025.

  4. Deep-learning-based interpolation of longitudinal microbiome data powers biologically informative discovery. [paper]

    Yixiang Qu*, Ruiqi Lyu*, Duan Wang, Yifan Dai, Alistair Turcan, Shilin Yu, Jialiu Xie, Jeffrey Roach, Catherine Butler, Pew-Thian Yap, Hongtu Zhu, Stuart Dashper, Apoena Aguiar Ribeiro, Didong Li, Kimon Divaris, Di Wu.

    bioRxiv, 2025.

  5. Towards Understanding the Effective Design of Automated Formative Feedback for Programming Assignments. [paper]

    Qiang Hao, David Smith, Lu Ding, Amy Ko, Camille Ottaway, Jack Wilson, Kai Arakawa, Alistair Turcan, Timothy Poehlman, Tyler Greer.

    Computer Science Education, 2022.

Curriculum vitae

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