rzzli

rzzli's Stars

• Systems-Methods/icWGCNA

  R package for Iteratively Corrected Weighted Gene Co-expression Network Analysis

  Language:R51

• ssine/pptx2md

  a pptx to markdown converter

  Language:Python45172

• google-research/prompt-tuning

  Original Implementation of Prompt Tuning from Lester, et al, 2021

  Language:Python63456

• npdeloss/meirlop

  Motif Enrichment In Ranked Lists Of Peaks

  Language:HTML31

• mermaid-js/mermaid

  Generation of diagrams like flowcharts or sequence diagrams from text in a similar manner as markdown

  Language:JavaScript68.8k6.1k

• edoughty/deepdive_genegene_app

  Language:Python85

• qiuyu96/CoDeF

  [CVPR 2024 Highlight] Official PyTorch implementation of CoDeF: Content Deformation Fields for Temporally Consistent Video Processing

  Language:Python4.8k389

• codecrafters-io/build-your-own-x

  Master programming by recreating your favorite technologies from scratch.

  283k26.5k

• melobio/EvoPlay

  Language:Python5910

• Novartis/ChemBioMultimodalAutoencoders

  a package for streamlined multidomain data integration and translation based on cross-modal autoencoders architectures

  Language:Python283

• dinesh-varyani/ds-algos

  Language:Java267203

• xzhao11/leetcode_to_notion

  Language:Jupyter Notebook443

• poseidonchan/TAPE

  Deep learning-based tissue compositions and cell-type-specific gene expression analysis with tissue-adaptive autoencoder (TAPE)

  Language:Jupyter Notebook4710

• patrickloeber/pytorchTutorial

  PyTorch Tutorials from my YouTube channel

  Language:Python1.7k1.2k

• tommyfan34/cs61a

  UCB CS61A fall 2020 codes

  Language:JavaScript233

• 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.

  Language:Python7717

• facebookresearch/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.

  Language:Jupyter Notebook17448

• PacktPublishing/40-Algorithms-Every-Programmer-Should-Know

  40 Algorithms Every Programmer Should Know, published by Packt

  Language:Python936367

• Sinaptik-AI/pandas-ai

  Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

  Language:Python11.8k1.1k

• trevismd/statannotations

  add statistical significance annotations on seaborn plots. Further development of statannot, with bugfixes, new features, and a different API.

  Language:Python61967

• aidenlab/straw

  Extract data quickly from Juicebox via straw

  Language:C++6136

• labuladong/fucking-algorithm

  刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

  Language:Markdown124k23.1k

• kundajelab/dfim

  Deep Feature Interaction Maps (DFIM)

  Language:Python527

• DongzeHE/alevin-fry

  🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.

  Language:Rust2

• liulab-dfci/MAESTRO

  Single-cell Transcriptome and Regulome Analysis Pipeline

  Language:C26873

• patrickloeber/python-fun

  Some fun and useful projects with Python

  Language:Jupyter Notebook710555

• HouariZegai/Calculator

  Calculator app created with Java Swing, It is simple with an easy code to help novices learn how to operate a calculator.

  Language:Java4292.1k

• ICBI/neoantigeR

  a R package to identify neoantigens from NGS data

  Language:R194

• cherryljr/LeetCode

  LeetCode各题解法分析~（Java and Python）

  Language:Java350176

• mrgloom/awesome-semantic-segmentation

  :metal: awesome-semantic-segmentation

  10.4k2.5k