6 citations · 10 across the 7 of their papers we have counts for
7 papers
T-cell receptor specificity landscape revealed through de novo peptide design
Gian Marco Visani, Michael N. Pun, Anastasia A. Minervina +3
T-cells play a key role in adaptive immunity by mounting specific responses against diverse pathogens. An effective binding between T-cell receptors (TCRs) and pathogen-derived pep…
Loop-Diffusion: an equivariant diffusion model for designing and scoring protein loops
Kevin Borisiak, Gian Marco Visani, Armita Nourmohammad
Predicting protein functional characteristics from structure remains a central problem in protein science, with broad implications from understanding the mechanisms of disease to d…
HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction
Gian Marco Visani, William Galvin, Zac Jones +5
Predicting the stability and fitness effects of amino acid mutations in proteins is a cornerstone of biological discovery and engineering. Various experimental techniques have been…
H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing
Gian Marco Visani, William Galvin, Michael Neal Pun +1
Accurately modeling protein 3D structure is essential for the design of functional proteins. An important sub-task of structure modeling is protein side-chain packing: predicting t…
Holographic-(V)AE: an end-to-end SO(3)-Equivariant (Variational) Autoencoder in Fourier Space
Gian Marco Visani, Michael N. Pun, Arman Angaji +1
Group-equivariant neural networks have emerged as a data-efficient approach to solve classification and regression tasks, while respecting the relevant symmetries of the data. Howe…
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories
Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen +4
We address the problem of modeling constrained hospital resources in the midst of the COVID-19 pandemic in order to inform decision-makers of future demand and assess the societal…
Enzyme promiscuity prediction using hierarchy-informed multi-label classification
Gian Marco Visani, Michael C. Hughes, Soha Hassoun
As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-l…