FADHLyemen

FADHLyemen's Stars

• bowang-lab/scGPT

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• saeyslab/nichenetr

  NicheNet: predict active ligand-target links between interacting cells

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• aertslab/SCENIC

  SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

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• junjunlab/scRNAtoolVis

  Useful functions to make your scRNA-seq plot more cool!

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• noriakis/ggkegg

  Analyzing and visualizing KEGG information using the grammar of graphics

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• saezlab/liana-py

  LIANA+: an all-in-one framework for cell-cell communication

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• neurorestore/Libra

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• 10XGenomics/loupeR

  Convert Seurat objects to 10x Genomics Loupe files.

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• YMa-lab/CARD

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• CSOgroup/cellcharter

  A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.

  Language:Python782232

• sjcockell/lockdown-learning

  Scripts written for my Bioinformatics-along on YouTube: https://www.youtube.com/playlist?list=PLzfP3sCXUnxEu5S9oXni1zmc1sjYmT1L9

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• simslab/scHPF

  Single-cell Hierarchical Poisson Factorization

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• saezlab/CollecTRI

  Gene regulatory network containing signed transcription factor-target gene interactions

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• swsoyee/TCC-GUI

  📊 Graphical User Interface for TCC package

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• PMBio/MuDataSeurat

  .h5mu files interface for Seurat

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• interactivereport/scRNAsequest

  scRNASequest: an ecosystem of scRNA-seq analysis, visualization and publishing

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• SpatialHackathon/SpaceHack2023

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• srp33/CodeBuddy

  CodeBuddy: A programming assignment management system for short-form exercises

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• saezlab/DOT

  DOT

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• ZhangLabGT/scDisInFact

  scDisInFact is a single-cell data integration and condition effect prediction framework

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• saezlab/kasumi_bench

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• jditz/comics

  Interpretable End-to-End Learning for Graph-Based Data in Healthcare

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• federicomarini/bettr

  A better way to explore what is best

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• karstensuhre/comics

  The Molecular Human – A Roadmap of Molecular Interactions Linking Multiomics Networks with Disease Endpoints.

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• gaminh/PURE

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• ncl-icbam/ismb-tutorial-2023

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• sulab-wmu/PASBench

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• dhirohama/Human_Kidney_Proteomics

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• drzeeshanahmed/GVViZ-Public

  1101

• ncl-icbam/Mapping-the-Transcriptome

  Code and data for the paper: "Mapping the Transcriptome - realising the full potential of spatial transcriptomics data analysis"

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