Marginalized Continuous Time Bayesian Networks for Network Reconstruction from Incomplete Observations. - Lukas Studer; Loïc Paulevé; Christoph Zechner; Matthias Reumann; María Rodríguez Martínez; Heinz Koeppl (AAAI, 2016)

Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer. - Ali Oskooei; Matteo Manica; Roland Mathis; María Rodríguez Martínez (CoRR, 2018)

PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks. - Ali Oskooei; Jannis Born; Matteo Manica; Vigneshwari Subramanian; Julio Sáez-Rodríguez; María Rodríguez Martínez (CoRR, 2018)

Inference of the three-dimensional chromatin structure and its temporal behavior. - Bianca-Cristina Cristescu; Zalán Borsos; John Lygeros; María Rodríguez Martínez; Maria Anna Rapsomaniki (CoRR, 2018)

edGNN: a Simple and Powerful GNN for Directed Labeled Graphs. - Guillaume Jaume; An-phi Nguyen; María Rodríguez Martínez; Jean-Philippe Thiran; Maria Gabrani (CoRR, 2019)

Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders. - Matteo Manica; Ali Oskooei; Jannis Born; Vigneshwari Subramanian; Julio Sáez-Rodríguez; María Rodríguez Martínez (CoRR, 2019)

Reinforcement learning-driven de-novo design of anticancer compounds conditioned on biomolecular profiles. - Jannis Born; Matteo Manica; Ali Oskooei; María Rodríguez Martínez (CoRR, 2019)

MonoNet: Towards Interpretable Models by Learning Monotonic Features. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2019)

DeStress: Deep Learning for Unsupervised Identification of Mental Stress in Firefighters from Heart-rate Variability (HRV) Data. - Ali Oskooei; Sophie Mai Chau; Jonas R. M. Weiss; Arvind Sridhar; María Rodríguez Martínez; Bruno Michel (CoRR, 2019)

Context-specific interaction networks from vector representation of words. - Matteo Manica; Roland Mathis; Joris Cadow; María Rodríguez Martínez (Nat. Mach. Intell., 2019)

PaccMannRL: Designing Anticancer Drugs From Transcriptomic Data via Reinforcement Learning. - Jannis Born; Matteo Manica; Ali Oskooei; Joris Cadow; María Rodríguez Martínez (RECOMB, 2020)

PaccMannRL on SARS-CoV-2: Designing antiviral candidates with conditional generative models. - Jannis Born; Matteo Manica; Joris Cadow; Greta Markert; Nil Adell Mill; Modestas Filipavicius; María Rodríguez Martínez (CoRR, 2020)

On quantitative aspects of model interpretability. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2020)

Learning Invariances for Interpretability using Supervised VAE. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2020)

Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream Tasks. - Modestas Filipavicius; Matteo Manica; Joris Cadow; María Rodríguez Martínez (CoRR, 2020)

PaccMann: a web service for interpretable anticancer compound sensitivity prediction. - Joris Cadow; Jannis Born; Matteo Manica; Ali Oskooei; María Rodríguez Martínez (Nucleic Acids Res., 2020)

FPGA Accelerated Analysis of Boolean Gene Regulatory Networks. - Matteo Manica; Raphael Polig; Mitra Purandare; Roland Mathis; Christoph Hagleitner; María Rodríguez Martínez (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

On the feasibility of deep learning applications using raw mass spectrometry data. - Joris Cadow; Matteo Manica; Roland Mathis; Tiannan Guo; Ruedi Aebersold; María Rodríguez Martínez (Bioinform., 2021)

SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems. - Andreas Dräger; Tomás Helikar; Matteo Barberis; Marc R. Birtwistle; Laurence Calzone; Claudine Chaouiya; Jan Hasenauer; Jonathan R. Karr; Anna Niarakis; María Rodríguez Martínez; Julio Saez-Rodriguez; Juilee Thakar (Bioinform., 2021)

TITAN: T-cell receptor specificity prediction with bimodal attention networks. - Anna Weber; Jannis Born; María Rodríguez Martínez (Bioinform., 2021)

It's FLAN time! Summing feature-wise latent representations for interpretability. - An-phi Nguyen; María Rodríguez Martínez (CoRR, 2021)

Data-driven molecular design for discovery and synthesis of novel ligands: a case study on SARS-CoV-2. - Jannis Born; Matteo Manica; Joris Cadow; Greta Markert; Nil Adell Mill; Modestas Filipavicius; Nikita Janakarajan; Antonio Cardinale; Teodoro Laino; María Rodríguez Martínez (Mach. Learn. Sci. Technol., 2021)

The Multiple Dimensions of Networks in Cancer: A Perspective. - Cristian Axenie; Roman Bauer 001; María Rodríguez Martínez (Symmetry, 2021)

Attention-Based Interpretable Regression of Gene Expression in Histology. - Mara Graziani; Niccolò Marini; Nicolas Deutschmann; Nikita Janakarajan; Henning Müller; María Rodríguez Martínez (iMIMIC@MICCAI, 2022)

Is Attention Interpretation? A Quantitative Assessment on Sets. - Jonathan Haab; Nicolas Deutschmann; María Rodríguez Martínez (PKDD/ECML Workshops (1), 2022)

PCfun: a hybrid computational framework for systematic characterization of protein complex function. - Varun S. Sharma; Andrea Fossati; Rodolfo Ciuffa; Marija Buljan; Evan G. Williams; Zhen Chen 009; Wenguang Shao; Patrick G. A. Pedrioli; Anthony W. Purcell; María Rodríguez Martínez; Jiangning Song; Matteo Manica; et al. (Briefings Bioinform., 2022)

DECODE: a computational pipeline to discover T cell receptor binding rules. - Iliana Papadopoulou; An-Phi Nguyen; Anna Weber; María Rodríguez Martínez (Bioinform., 2022)

Computational modelling in health and disease: highlights of the 6th annual SysMod meeting. - Anna Niarakis; Juilee Thakar; Matteo Barberis; María Rodríguez Martínez; Tomás Helikar; Marc R. Birtwistle; Claudine Chaouiya; Laurence Calzone; Andreas Dräger (Bioinform., 2022)

Aligned Diffusion Schrödinger Bridges. - Vignesh Ram Somnath; Matteo Pariset; Ya-Ping Hsieh; María Rodríguez Martínez; Andreas Krause 001; Charlotte Bunne (UAI, 2023)

Adaptive Conformal Regression with Jackknife+ Rescaled Scores. - Nicolas Deutschmann; Mattia Rigotti; María Rodríguez Martínez (CoRR, 2023)

DockGame: Cooperative Games for Multimeric Rigid Protein Docking. - Vignesh Ram Somnath; Pier Giuseppe Sessa; María Rodríguez Martínez; Andreas Krause 001 (CoRR, 2023)

FLAN: feature-wise latent additive neural models for biological applications. - An-phi Nguyen; Stefania Vasilaki; María Rodríguez Martínez (Briefings Bioinform., 2023)

Conformal Autoregressive Generation: Beam Search with Coverage Guarantees. - Nicolas Deutschmann; Marvin Alberts; María Rodríguez Martínez (AAAI, 2024)

HoVer-NeXt: A Fast Nuclei Segmentation and Classification Pipeline for Next Generation Histopathology. - Elias Baumann; Bastian Dislich; Josef Lorenz Rumberger; Iris D. Nagtegaal; María Rodríguez Martínez; Inti Zlobec (MIDL, 2024)

Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases. - Ling Han; Hao Huang 001; Dustin Scheinost; Mary-Anne Hartley; María Rodríguez Martínez (CoRR, 2024)

Adaptive Conformal Regression with Split-Jackknife+ Scores. - Nicolas Deutschmann; Mattia Rigotti; María Rodríguez Martínez (Trans. Mach. Learn. Res., 2024)