A collection of UNet and hybrid architectures in PyTorch for 2D and 3D Biomedical Image segmentation
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Updated
Aug 2, 2018 - Python
A collection of UNet and hybrid architectures in PyTorch for 2D and 3D Biomedical Image segmentation
A Curated List of Computational Biology Datasets Suitable for Machine Learning
Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.
A software package for statistically significant shapelet mining
UNet based model that segment retina to 8 layers in OCT images
Ultimate ATAC-seq Data Processing, Quantification and Annotation Snakemake Workflow and MrBiomics Module.
VerifAI initiative to build open-source easy-to-deploy generative question-answering engine that can reference and verify answers for correctness (using posteriori model)
Machine-learning based pipeline relying on LambdaMART currently used in PubMed for relevance (Best Match) searches
Knee Osteoarthritis Analysis with X-ray Images using CNN
Turning Ontologies Plus Annotation Properties into Vectors
A Snakemake workflow and MrBiomics module for performing genomic region set and gene set enrichment analyses using LOLA, GREAT, GSEApy, pycisTarget and RcisTarget.
A Python library for biomedical statistical shape and appearance modelling.
A Snakemake workflow and MrBiomics module for performing and visualizing differential (expression) analyses (DEA) on NGS data powered by the R package limma.
Providing interactions between drugs and genes sourced from a variety of publications and knowledgebases
Unsupervised domain adaptation method for relation extraction
A Snakemake workflow and MrBiomics module for easy visualization of genome browser tracks of aligned BAM files (e.g., RNA-seq, ATAC-seq, scRNA-seq, ...) powered by the wrapper gtracks for the package pyGenomeTracks, and IGV-reports.
A Snakemake workflow and MrBiomics module for processing and visualizing (multimodal) sc/snRNA-seq data generated with 10X Genomics Kits or in the MTX matrix file format powered by the R package Seurat.
R package for delineating temporal dataset shifts in Eletronic Health Records
A Snakemake workflow and MrBiomics module for performing differential expression analyses (DEA) on (multimodal) sc/snRNA-seq data powered by the R package Seurat.
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