Joseph A. Morrone

According to our database, Joseph A. Morrone authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MAMMAL - Molecular Aligned Multi-Modal Architecture and Language.

Yoel Shoshan, Moshiko Raboh, Michal Ozery-Flato, Vadim Ratner, Alex Golts, Jeffrey K. Weber, Ella Barkan, Simona Rabinovici-Cohen, Sagi Polaczek, Ido Amos, Ben Shapira, Liam Hazan, Matan Ninio, Sivan Ravid, Michael M. Danziger, Joseph A. Morrone, Parthasarathy Suryanarayanan, Michal Rosen-Zvi, Efrat Hexter

CoRR, 2024

Multi-view biomedical foundation models for molecule-target and property prediction.

Parthasarathy Suryanarayanan, Yunguang Qiu, Shreyans Sethi, Diwakar Mahajan, Hongyang Li, Yuxin Yang, Elif K. Eyigöz, Aldo Guzmán-Sáenz, Daniel E. Platt, Timothy H. Rumbell, Kenney Ng, Sanjoy Dey, Myson Burch, Bum Chul Kwon, Pablo Meyer, Feixiong Cheng, Jianying Hu, Joseph A. Morrone

CoRR, 2024

SPARK: Harnessing Human-Centered Workflows with Biomedical Foundation Models for Drug Discovery.

Bum Chul Kwon, Simona Rabinovici-Cohen, Beldine Moturi, Ruth Mwaura, Kezia Wahome, Oliver Njeru, Miguel Shinyenyi, Catherine Wanjiru, Sekou L. Remy, William Ogallo, Itai Guez, Parthasarathy Suryanarayanan, Joseph A. Morrone, Shreyans Sethi, Seung-gu Kang, Tien Huynh, Kenney Ng, Diwakar Mahajan, Hongyang Li, Matan Ninio, Shervin Ayati, Efrat Hexter, Wendy D. Cornell

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2022

Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation.

Seung-gu Kang, Joseph A. Morrone, Jeffrey K. Weber, Wendy D. Cornell

J. Chem. Inf. Model., 2022

Self-Focusing Virtual Screening with Active Design Space Pruning.

David E. Graff, Matteo Aldeghi, Joseph A. Morrone, Kirk E. Jordan, Edward O. Pyzer-Knapp, Connor W. Coley

J. Chem. Inf. Model., 2022

Roughness of Molecular Property Landscapes and Its Impact on Modellability.

Matteo Aldeghi, David E. Graff, Nathan C. Frey, Joseph A. Morrone, Edward O. Pyzer-Knapp, Kirk E. Jordan, Connor W. Coley

J. Chem. Inf. Model., 2022

Simplified, interpretable graph convolutional neural networks for small molecule activity prediction.

Jeffrey K. Weber, Joseph A. Morrone, Sugato Bagchi, Jan D. Estrada Pabon, Seung-gu Kang, Leili Zhang, Wendy D. Cornell

J. Comput. Aided Mol. Des., 2022

In-Pocket 3D Graphs Enhance Ligand-Target Compatibility in Generative Small-Molecule Creation.

Seung-gu Kang, Jeffrey K. Weber, Joseph A. Morrone, Leili Zhang, Tien Huynh, Wendy D. Cornell

CoRR, 2022

2020

Combining Docking Pose Rank and Structure with Deep Learning Improves Protein-Ligand Binding Mode Prediction over a Baseline Docking Approach.

Joseph A. Morrone, Jeffrey K. Weber, Tien Huynh, Heng Luo, Wendy D. Cornell

J. Chem. Inf. Model., 2020