Disentangling shared and groupspecific variations in singlecell transcriptomics data with multiGroupVI

A generative recommender system with GMM prior for cancer drug generation and sensitivity prediction

Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy images

Selecting deep neural networks that yield consistent attributionbased interpretations for genomics

Applying pathbased reasoning on biological knowledge graphs improves annotation of gene functions

Phyloformer: towards fast and accurate phylogeny reconstruction with selfattention networks

The ENCODE Imputation Challenge: A critical assessment of methods for crosscell type imputation of epigenomic profiles

Missing Value Imputation for Genomics Data using a Sequence Based Generative Adversarial Network

Gene colocalizationaware segmentation of imagebased spatial transcriptomics using Graph Markov Neural Networks

Predicting Adverse Drug Reactions Using Bias Resilient and Interpretable Artificial Neural Networks

Accurate estimation of celltype resolution abundance and transcriptome in bulk tissue through matrix completion

RPCAtree: An adaptive robust PCA algorithm for embedded tree structure recovery from noisy and heterogeneous data

Identifying commonalities between cell lines and tumors at the single cell level using Sobolev Alignment of deep generative models

Mapping the affinity of proteinprotein interactions with multiple amino acid mutations using deep neural networks

Inferring multigenic signatures across the phenome with novel Bayesian variable selection method for binary classification

A Methodology for Predicting Tissuespecific Metabolic and Inflammatory Receptor Functions Applied to Subcutaneous and Visceral Adipose

SiteofMetabolism Prediction using Graph Neural Networks and its Applications to Ranking Promiscuous Enzymatic Products

Deep learningbased phenotyping identifies subcellular organelle dysregulation and differentiates healthy and ALS neurons

Assessing machine learning models performances for bacterial taxonomic classification and host removal in metagenomic sequencing data

Comparison of deep and shallow graph representation learning algorithms for detecting modules in molecular networks

Overview of Novel Computational Tools for CRISPR Genome Editing Advances and Challenges

Nonnegative matrix trifactorization for simultaneous identification of informative feature and cell clusters from single cell omic datasets

A unified framework of realistic in silico data generation and statistical model inference for singlecell and spatial omics

Generative diffusion modelling on the singlecell differentiation data with compositional perturbation

External biological knowledge can aid the development and deployment of wellspecified models in breast cancer subtyping

Multitask hierarchical convolutional networks to predict thermodynamic property changes due to mutations in proteinprotein complexes

Disentangling ancestry representations for improving genetic risk prediction across diverse population

A Novel Twin Convolutional Neural Network to Decipher the Functional Effect of Noncoding Genetic Variants in Neurodegenerative Diseases

ScRAT: Early Phenotype Prediction From Singlecell RNAseq Data using AttentionBased Neural Networks

Yuzhen Mao (School of Computing Sciences, Simon Fraser University); YenYi Lin (Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, University of British Columbia); Funda Sar (Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, University of British Columbia); Nelson Wong (Department of Experimental Therapeutics, BC Cancer); Stanislav Volik (Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, University of British Columbia); Mark Carey (Gynecologic Oncology, University of British Columbia); Colin Collins (Vancouver Prostate Centre, Department of Urologic Sciences, Faculty of Medicine, University of British Columbia); Martin Ester (Simon Fraser University)*

ResPAN: a powerful batch correction model for scRNAseq data through residual adversarial networks