2 citations · 2 across the 11 of their papers we have counts for
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HyperHELM: Hyperbolic Hierarchy Encoding for mRNA Language Modeling
Max van Spengler, Artem Moskalev, Tommaso Mansi +2
Language models are increasingly applied to biological sequences like proteins and mRNA, yet their default Euclidean geometry may mismatch the hierarchical structures inherent to b…
BioLangFusion: Multimodal Fusion of DNA, mRNA, and Protein Language Models
Amina Mollaysa, Artem Moskale, Pushpak Pati +3
We present BioLangFusion, a simple approach for integrating pre-trained DNA, mRNA, and protein language models into unified molecular representations. Motivated by the central dogm…
Geometric Hyena Networks for Large-scale Equivariant Learning
Artem Moskalev, Mangal Prakash, Junjie Xu +3
Processing global geometric context while preserving equivariance is crucial when modeling biological, chemical, and physical systems. Yet, this is challenging due to the computati…
HELM: Hierarchical Encoding for mRNA Language Modeling
Mehdi Yazdani-Jahromi, Mangal Prakash, Tommaso Mansi +2
Messenger RNA (mRNA) plays a crucial role in protein synthesis, with its codon structure directly impacting biological properties. While Language Models (LMs) have shown promise in…
SE(3)-Hyena Operator for Scalable Equivariant Learning
Artem Moskalev, Mangal Prakash, Rui Liao +1
Modeling global geometric context while maintaining equivariance is crucial for accurate predictions in many fields such as biology, chemistry, or vision. Yet, this is challenging…