- IndepthPathway: an integrated tool for in-depth pathway enrichment analysis based on single cell sequencing data
- Deep single-cell RNA-seq data clustering with graph prototypical contrastive learning
- Online bias-aware disease module mining with ROBUST-Web
- Pygenomics: manipulating genomic intervals and data files in Python
- Mutate and Observe: Utilizing Deep Neural Networks to Investigate the Impact of Mutations on Translation Initiation
- GraphscoreDTA: optimized graph neural network for protein-ligand binding affinity prediction
- KNeMAP: A Network Mapping Approach for Knowledge-driven Comparison of Transcriptomic Profiles
- itol.toolkit accelerates working with iTOL (Interactive Tree Of Life) by an automated generation of annotation files
- scME: A Dual-Modality Factor Model for Single-Cell Multi-Omics Embedding
- A Co-adaptive Duality-aware Framework for Biomedical Relation Extraction
- Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics
- gExcite — A start-to-end framework for single-cell gene expression, hashing, and antibody analysis
- HONMF: integration analysis of multi-omics microbiome data via matrix factorization and hypergraph
- MultiNEP: a Multi-omics Network Enhancement framework for Prioritizing disease genes and metabolites simultaneously
- Deep learning-based multi-functional therapeutic peptides prediction with a multi-label focal dice loss function
- RaggedExperiment: the missing link between genomic ranges and matrices in Bioconductor
- GIL: A python package for designing custom indexing primers
- BRGenomics for analyzing high resolution genomics data in R
- Letter to the editor: Testing on External Independent Datasets is Necessary to Corroborate Machine Learning Model Improvement
- ODNA: Identification of Organellar DNA by Machine Learning