Tamara Broderick

Tamara Broderick

1. Generative power of a protein language model trained on multiple sequence alignments
2. BayesTME: A reference-free Bayesian method for end-to-end analysis of spatial transcriptomic data
3. RITA: a Study on Scaling Up Generative Protein Sequence Models
4. Learning Batch-Invariant Representations with Domain Adaptation in Large Scale Proteomics Data
5. COEM: Cross-Modal Embedding for MetaCell Identification
6. EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
7. A Deep Learning Framework for Estimating Cell-specific Kinetic Rates of RNA Velocity
8. Learning to rank metabolites across datasets
9. RTfold: RNA secondary structure prediction using deep learning with domain inductive bias
10. 7-UP: generating in silico CODEX from a small set of immunofluorescence markers
11. Mass Enhanced Node Embeddings for Drug Repurposing
12. Confounded Domain Adaptation: A Framework for Biological Data Batch Correction
13. Trust-region Bayesian optimisation with developability constraints enables sample efficient, high-affinity antibody design
14. Reinforcement learning to optimize fungal Biosynthetic Gene Clusters
15. How Graph Neural Networks Enhance Convolutional Neural Networks Towards Mining the Topological Structures from Histology
16. N-ACT: An Interpretable Deep Learning Model for Automatic Cell Type and Salient Gene Identification
17. Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints
18. Capturing Similarity among Simulated Patches of Human Cell Membrane
19. Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning
20. Protein language models trained on multiple sequence alignments learn phylogenetic relationships
21. Inferring cell-specific causal regulatory networks from drift and diffusion
22. High Performance of Gradient Boosting in Binding Affinity Prediction
23. Zero-Shot Prediction of Drug Combination Activity for High-Throughput Screens
24. Antibody design by optimization of affinity and naturalness using language models
25. Scalable Causal Structure Learning via Amortized Conditional Randomization Testing
26. Identifying Spatial Biomarkers from Cellular Imaging Data

Panelists: - Mohammad AlQuraishi - Elana Fertig - Patrick Schwab - Neeha Zaidi

Moderator: Pascal Notin

1. DIISCO: Dynamic Intercellular Interactions in Single Cell transcriptOmics
2. SPACE-GM: geometric deep learning of disease-associated microenvironments from multiplex spatial protein profiles.
3. Probabilistic basis decomposition for characterizing temporal dynamics of gene expression
4. A mechanistic probabilistic model of genomic compartments
5. SNVformer: An Attention-based Deep Neural Network for GWAS Data
6. Extracting Part of Signal Representation from Direct RNA Squiggle for Modification Detection
7. TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-binding analyses
8. Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions
9. Assessing the utility of genomic deep learning models for disease-relevant variant effect prediction
10. Molecular Fingerprints Are a Simple Yet Effective Solution to the Drug–Drug Interaction Problem
11. Disentangling ancestry representations for improving genetic risk prediction across diverse population
12. Hierarchically weighted mixture modeling of drug combination responses
13. Uncertainty Quantification for Atlas-Level Cell Type Transfer
14. Learning representations from mass spectra for peptide property prediction
15. Joint Embedding of Biological Networks for Cross-Species Functional Alignment
16. MultiCPA: Multimodal Compositional Perturbation Autoencoder
17. LANTERN: An Interpretable Genotype-Phenotype Landscape Model
18. Toward Inferring Ancestral States and Evolutionary Parameters using a Variational Generative Model for Multiple Sequence Alignments
19. An Optimal Likelihood Free Method for Biological Model Selection
20. PEPSI: Post-docking Evaluation with Protein-Small Molecules Interaction
21. Deep Active Learning for De Novo Peptide Sequencing from Data-independent-acquisition Mass Spectrometry
22. Combating Extreme Adversarial Vulnerabilities in WSI Classification
23. Purification of single-cell transcriptomics data with coreset selection
24. Continual single-cell architecture surgery for reference mapping
25. Bayesian matrix factorization with integrated human genetics evidence for predicting the success of clinical trial outcomes