ceesu's Stars
oven-sh/bun
Incredibly fast JavaScript runtime, bundler, test runner, and package manager – all in one
stitionai/devika
Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI.
organicmaps/organicmaps
🍃 Organic Maps is a free Android & iOS offline maps app for travelers, tourists, hikers, and cyclists. It uses crowd-sourced OpenStreetMap data and is developed with love by MapsWithMe (MapsMe) founders and our community. No ads, no tracking, no data collection, no crapware. Please donate to support the development!
rawgraphs/rawgraphs-app
A web interface to create custom vector-based visualizations on top of RAWGraphs core
peak/s5cmd
Parallel S3 and local filesystem execution tool.
AllenDowney/ThinkBayes2
Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.
rmcelreath/stat_rethinking_2024
lrberge/fixest
Fixed-effects estimations
paws-r/paws
Paws, a package for Amazon Web Services in R
bioSyntax/bioSyntax
Syntax highlighting for computational biology
biomap-research/scFoundation
nigelpoulton/gsd
Files for Getting Started with Docker video training course
snap-stanford/GEARS
GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
aertslab/scenicplus
SCENIC+ is a python package to build gene regulatory networks (GRNs) using combined or separate single-cell gene expression (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq) data.
HelenaLC/muscat
Multi-sample multi-group scRNA-seq analysis tools
lynnlangit/aws-for-bioinformatics
AWS for Bioinformatics Researchers
cmudig/emblaze
Interactive Jupyter notebook widget for visually comparing embedding spaces.
theislab/chemCPA
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
theislab/cpa
The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.
const-ae/lemur
Latent Embedding Multivariate Regression
coolbutuseless/svgparser
Render SVG images in R. Load SVG data as data.frames
thomasmaxwellnorman/Perturbseq_GI
Code for reproducing "Exploring genetic interaction manifolds constructed from rich single-cell phenotypes"
drisso/zinbwave
Clone of the Bioconductor repository for the zinbwave package, see https://bioconductor.org/packages/zinbwave
microsoft/zero-shot-scfoundation
Genentech/iterative-perturb-seq
Sequential Optimal Experimental Design of Perturbation Screens Guided by Multimodal Priors
douglasyao/FR-Perturb
Factorize-Recover for Perturb-seq analysis (FR-Perturb)
yulun-rayn/graphVCI
This repository implements Graph Variational Causal Inference (graphVCI), a framework that integrates prior knowledge of relational information into variational causal inference for the prediction of perturbation effect on gene expressions at single-cell and marginal level.
powellgenomicslab/BGI_vs_Illumina_Benchmark
This repository contains code related to the publication "Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing" by Senabouth et al.
EvaYiwenWang/Managing_batch_effects
wvictor14/rbiotechsalary
reddit r/biotech salary