Alternatives and similar repositories for Sweetwater:

Users that are interested in Sweetwater are comparing it to the libraries listed below

• Perturbation-Response-Prediction / PRnet
  PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturb…
  ☆40Updated 3 months ago
• theislab / nicheformer
  Repository for Nicheformer: a foundation model for single-cell and spatial omics
  ☆86Updated last week
• xianglin226 / Benchmarking-Single-Cell-Perturbation
  Single-Cell (Perturbation) Model Library
  ☆45Updated 2 weeks ago
• sidhomj / DeepTCR
  Deep Learning Methods for Parsing T-Cell Receptor Sequencing (TCRSeq) Data
  ☆118Updated 2 years ago
• idekerlab / DrugCell
  A visible neural network model for drug response prediction
  ☆140Updated last year
• theislab / chemCPA
  Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
  ☆111Updated last month
• theislab / sc-pert
  Models and datasets for perturbational single-cell omics
  ☆152Updated 2 years ago
• sanderlab / scPerturb
  scPerturb: A resource and a python/R tool for single-cell perturbation data
  ☆116Updated last month
• Genentech / scimilarity
  A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to repr…
  ☆181Updated last month
• snap-stanford / GEARS
  GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
  ☆245Updated 2 months ago
• OmicsML / awesome-foundation-model-single-cell-papers
  ☆246Updated 2 months ago
• phbradley / TCRdock
  python tools for TCR:peptide-MHC modeling and analysis
  ☆72Updated 11 months ago
• tianshilu / pMTnet
  Deep Learning the T Cell Receptor Binding Specificity of Neoantigen
  ☆79Updated 2 years ago
• wukevin / tcr-bert
  Large language modeling applied to T-cell receptor (TCR) sequences.
  ☆52Updated 2 years ago
• CompBioT / SCAD
  ☆9Updated last year
• mims-harvard / PINNACLE
  Contextual AI models for single-cell protein biology
  ☆83Updated last month
• theislab / single-cell-transformer-papers
  ☆304Updated 3 weeks ago
• HelloWorldLTY / scEval
  Codes for paper: Evaluating the Utilities of Large Language Models in Single-cell Data Analysis.
  ☆64Updated 2 months ago
• JackieHanLab / TOSICA
  Transformer for One-Stop Interpretable Cell-type Annotation
  ☆138Updated last year
• LewisLabUCSD / Ligand-Receptor-Pairs
  Compendium of available lists of ligand-receptor pairs and surface-secreted protein interactions.
  ☆129Updated 2 years ago
• jkobject / geneformer
  ☆57Updated last year
• carpenter-singh-lab / 2022_Haghighi_NatureMethods
  High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
  ☆48Updated 2 months ago
• YangLabHKUST / SpatialScope
  A unified approach for integrating spatial and single-cell transcriptomics data by leveraging deep generative models
  ☆63Updated 10 months ago
• ArcInstitute / arc-virtual-cell-atlas
  Arc Virtual Cell Atlas
  ☆240Updated last week
• dpeerlab / spectra
  Supervised Pathway DEConvolution of InTerpretable Gene ProgRAms
  ☆165Updated 8 months ago
• bm2-lab / PanPep
  ☆49Updated last year
• OmicsML / CellPLM
  Official repo for CellPLM: Pre-training of Cell Language Model Beyond Single Cells.
  ☆78Updated last year
• Lifoof / MoGCN
  Multi-omics integration method using AE and GCN
  ☆34Updated last year
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆97Updated 7 months ago
• welch-lab / PerturbNet
  PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
  ☆30Updated last month