Debora S. Marks

According to our database, Debora S. Marks authored at least 25 papers between 2007 and 2024.

Collaborative distances:

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

2024

Kernel-Based Evaluation of Conditional Biological Sequence Models.

Pierre Glaser, Steffanie Paul, Alissa M. Hummer, Charlotte M. Deane, Debora Susan Marks, Alan Nawzad Amin

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Scientific discovery in the age of artificial intelligence.

Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik

Nat., 2023

Biological Sequence Kernels with Guaranteed Flexibility.

Alan Nawzad Amin, Eli Nathan Weinstein, Debora Susan Marks

CoRR, 2023

ProteinNPT: Improving protein property prediction and design with non-parametric transformers.

Pascal Notin, Ruben Weitzman, Debora S. Marks, Yarin Gal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design.

Pascal Notin, Aaron Kollasch, Daniel Ritter, Lood van Niekerk, Steffanie Paul, Han Spinner, Nathan J. Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora S. Marks

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Kernelized Stein Discrepancy for Biological Sequences.

Alan Nawzad Amin, Eli N. Weinstein, Debora Susan Marks

Proceedings of the International Conference on Machine Learning, 2023

2022

PDBe-KB: collaboratively defining the biological context of structural data.

Mihaly Varadi, Stephen Anyango, David R. Armstrong, John M. Berrisford, Preeti Choudhary, Mandar S. Deshpande, Nurul Nadzirin, Sreenath Nair, Lukás Pravda, Ahsan Tanweer, Bissan Al-Lazikani, Claudia Andreini, Geoffrey J. Barton, David Bednar, Karel Berka, Tom L. Blundell, Kelly Brock, José María Carazo, Jirí Damborský, Alessia David, Sucharita Dey, Roland L. Dunbrack Jr., Juan Fernández-Recio, Franca Fraternali, Toby J. Gibson, Manuela Helmer-Citterich, David Hoksza, Thomas A. Hopf, David Jakubec, Natarajan Kannan, Radoslav Krivák, Manjeet Kumar, Emmanuel D. Levy, Nir London, José Ramón Macías, Mallur Srivatsan Madhusudhan, Debora S. Marks, Lennart Martens, Stuart A McGowan, Jake E. McGreig, Vivek Modi, R. Gonzalo Parra, Gerardo Pepe, Damiano Piovesan, Jaime Prilusky, Valeria Putignano, Leandro G. Radusky, Pathmanaban Ramasamy, Atilio O. Rausch, Nathalie Reuter, Luis A. Rodriguez, Nathan J. Rollins, Antonio Rosato, Pawel Rubach, Luis Serrano, Gulzar Singh, Petr Skoda, Carlos Oscar Sánchez Sorzano, Jan Stourac, Joanna I. Sulkowska, Radka Svobodová Vareková, Natalia Tichshenko, Silvio C. E. Tosatto, Wim F. Vranken, Mark N. Wass, Dandan Xue, Daniel Zaidman, Janet M. Thornton, Michael J. E. Sternberg, Christine A. Orengo, Sameer Velankar

Nucleic Acids Res., 2022

RITA: a Study on Scaling Up Generative Protein Sequence Models.

Daniel Hesslow, Niccoló Zanichelli, Pascal Notin, Iacopo Poli, Debora S. Marks

CoRR, 2022

Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness.

Eli N. Weinstein, Alan Nawzad Amin, Jonathan Frazer, Debora S. Marks

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval.

Pascal Notin, Mafalda Dias, Jonathan Frazer, Javier Marchena-Hurtado, Aidan N. Gomez, Debora S. Marks, Yarin Gal

Proceedings of the International Conference on Machine Learning, 2022

Optimal Design of Stochastic DNA Synthesis Protocols based on Generative Sequence Models.

Eli N. Weinstein, Alan Nawzad Amin, Will S. Grathwohl, Daniel Kassler, Jean Disset, Debora S. Marks

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A generative nonparametric Bayesian model for whole genomes.

Alan Nawzad Amin, Eli N. Weinstein, Debora S. Marks

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting.

Eli N. Weinstein, Debora S. Marks

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

The EVcouplings Python framework for coevolutionary sequence analysis.

Thomas A. Hopf, Anna G. Green, Benjamin Schubert, Sophia Mersmann, Charlotta Schärfe, John Ingraham, Ágnes Tóth-Petróczy, Kelly Brock, Adam J. Riesselman, Perry Palmedo, Chan Kang, Robert P. Sheridan, Eli J. Draizen, Christian Dallago, Chris Sander, Debora S. Marks

Bioinform., 2019

Learning Protein Structure with a Differentiable Simulator.

John Ingraham, Adam J. Riesselman, Chris Sander, Debora S. Marks

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Population-specific design of de-immunized protein biotherapeutics.

Benjamin Schubert, Charlotta Schärfe, Pierre Dönnes, Thomas A. Hopf, Debora S. Marks, Oliver Kohlbacher

PLoS Comput. Biol., 2018

2017

Variational Inference for Sparse and Undirected Models.

John Ingraham, Debora S. Marks

Proceedings of the 34th International Conference on Machine Learning, 2017

2015

Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models.

Richard R. Stein, Debora S. Marks, Chris Sander

PLoS Comput. Biol., 2015

2014

Structure, Dynamics and Implied Gating Mechanism of a Human Cyclic Nucleotide-Gated Channel.

Yana Gofman, Charlotta Schärfe, Debora S. Marks, Turkan Haliloglu, Nir Ben-Tal

PLoS Comput. Biol., 2014

FreeContact: fast and free software for protein contact prediction from residue co-evolution.

László Kaján, Thomas A. Hopf, Matú Kala, Debora S. Marks, Burkhard Rost

BMC Bioinform., 2014

PconsFold: improved contact predictions improve protein models.

Mirco Michel, Sikander Hayat, Marcin J. Skwark, Chris Sander, Debora S. Marks, Arne Elofsson

Bioinform., 2014

2012

miRcode: a map of putative microRNA target sites in the long non-coding transcriptome.

Ashwini Jeggari, Debora S. Marks, Erik Larsson

Bioinform., 2012

2011

3D Protein Structure Predicted from Sequence

Debora S. Marks, Lucy J. Colwell, Robert P. Sheridan, Thomas A. Hopf, Andrea Pagnani, Riccardo Zecchina, Chris Sander

CoRR, 2011

2008

The microRNA.org resource: targets and expression.

Doron Betel, Manda Wilson, Aaron Gabow, Debora S. Marks, Chris Sander

Nucleic Acids Res., 2008

2007

Computational Analysis of Mouse piRNA Sequence and Biogenesis.

Doron Betel, Robert P. Sheridan, Debora S. Marks, Chris Sander

PLoS Comput. Biol., 2007