Poster Session
in
Workshop: ICML 2022 Workshop on Computational Biology

Poster session #1 / Lunch break

2022 Poster Session
in
Workshop: ICML 2022 Workshop on Computational Biology

Abstract

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

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