Alan Moses
Professor
Applies machine learning to microscopy images and protein and genome sequences to study regulatory evolution.
Alan Moses's lab at Toronto works on genomics & computational biology, proteins, drugs & materials and medical image analysis. 17 papers since 2023. 5 PhD students and 2 master's students. 26 alumni. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 0%
- PhD students
- 5
- MS students
- 2
- alumni listed
- 26
Papers by yearfrom the lab homepage, 2023–2026
- 6 papers2026 · T1 0 · collecting
- 6 papers2025 · T1 0
- 3 papers2024 · T1 0
- 2 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- Proteins, drugs & materials3 papers
- Genomics & computational biology2 papers
- sequences1 paper
- Medical image analysis0 papers
- systems biology0 papers
Paper list
From the lab homepage.
20266 papers
- Proc Natl Acad Sci U S A. May 26 PNAS link PDF Mirror PubMed AbstractA functional map of the human intrinsically disordered proteome
- Genetics Jan 7;232(1):iyaf209 Genetics Link PDF Mirror PubMed AbstractInferring fungal cis-regulatory networks from genome sequences via unsupervised and interpretable representation learning
- Nat Cell Biol Feb;28(2):214-216 Nature Cell Bio Link PDF Mirror PubMed AbstractMotifs and chemistry dictate the role of intrinsically disordered regions
- Forty-Third International Conference on Machine Learning (ICMLPredicting evolutionary rate as a pretraining task improves genome language model representations
- eLife 15:RP112029 eLife linkProtein generation with evolutionary diffusion: sequence is all you need
- GEN Biotechnology GEN Biotech link PDF MirrorTranscription Factors: Disorderly Conduct
20256 papers
- J Mol Biol Apr 3:169124 Journal of Molecular Biology Link PDF Mirror PubMed AbstractAn RNA condensate model for the origin of life
- Science Jul 17;389(6757):235-236 Science Link PDF Mirror PubMed AbstractDisorder meets its match
- Nature Link PDF MirrorNature Machine Intelligence Mar 13
- Proceedings of the Machine Learning in Computational Biology meetingRepresentation Learning Methods for Single-Cell Microscopy are Confounded by Background Cells
- Learning Meaningful Representations of Life (LMRLUnsupervised Whole-Genome Representation Learning Captures Bacterial Phenotypes
- PLoS Comput Biol Nov 11;21(11):e1012929 PLoS Comp Bio Link PDF Mirror PubMed AbstractZero-shot segmentation using embeddings from a protein language model identifies functional regions in the human proteome
20243 papers
- Bioinformatics Mar 29;40(4):btae190 Bioinformatics Link PDF Mirror PubMed AbstractImproving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation
- Cell Rep Jul 23;43(7):114417 Cell Reports Link PDF Mirror PubMed AbstractThe TSC22D, WNK, and NRBP gene families exhibit functional buffering and evolved with Metazoa for cell volume regulation
- Methods Mol Biol 2800:217-229 Methods in Molecular Biology Link PDF Mirror PubMed AbstractUsing Dimensionality Reduction to Visualize Phenotypic Changes in High-Throughput Microscopy
20232 papers
- Chem Rev Jul 26;123(14):9036-9064 Chemical Reviews Link PDF Mirror PubMed AbstractA New Phase of Networking: The Molecular Composition and Regulatory Dynamics of Mammalian Stress Granules
- PNAS Oct 31;120(44):e2304302120 PNAS Link PDF Mirror PubMed AbstractSystematic identification of conditionally folded intrinsically disordered regions by AlphaFold2
Where alumni went26 listed
Apply to TorontoFall 2027
Computer Science MSc/PhD
- Round
- Single round (Dec 1)
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS if applicable
- Fee
- CAD 135
Confirmed on the program page.
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- Papers
- The lab homepage
- Members
- Lab homepage
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