Search Results for author: Scott Gigante

Found 6 papers, 1 papers with code

SystemMatch: optimizing preclinical drug models to human clinical outcomes via generative latent-space matching

no code implementations14 May 2022 Scott Gigante, Varsha G. Raghavan, Amanda M. Robinson, Robert A. Barton, Adeeb H. Rahman, Drausin F. Wulsin, Jacques Banchereau, Noam Solomon, Luis F. Voloch, Fabian J. Theis

Translating the relevance of preclinical models ($\textit{in vitro}$, animal models, or organoids) to their relevance in humans presents an important challenge during drug development.

Compressed Diffusion

no code implementations31 Jan 2019 Scott Gigante, Jay S. Stanley III, Ngan Vu, David van Dijk, Kevin Moon, Guy Wolf, Smita Krishnaswamy

Diffusion maps are a commonly used kernel-based method for manifold learning, which can reveal intrinsic structures in data and embed them in low dimensions.

Harmonic Alignment

no code implementations30 Sep 2018 Jay S. Stanley III, Scott Gigante, Guy Wolf, Smita Krishnaswamy

We use this to relate the diffusion coordinates of each dataset through our assumption of partial feature correspondence.

Modeling Dynamics of Biological Systems with Deep Generative Neural Networks

no code implementations27 Sep 2018 Scott Gigante, David van Dijk, Kevin R. Moon, Alexander Strzalkowski, Katie Ferguson, Guy Wolf, Smita Krishnaswamy

DyMoN is well-suited to the idiosyncrasies of biological data, including noise, sparsity, and the lack of longitudinal measurements in many types of systems.

Dimensionality Reduction

Modeling Global Dynamics from Local Snapshots with Deep Generative Neural Networks

no code implementations10 Feb 2018 Scott Gigante, David van Dijk, Kevin Moon, Alexander Strzalkowski, Guy Wolf, Smita Krishnaswamy

In order to model the dynamics of such systems given snapshot data, or local transitions, we present a deep neural network framework we call Dynamics Modeling Network or DyMoN.

Dimensionality Reduction

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