TD-lab-Wu

TD-lab-Wu's Stars

• louisfb01/start-machine-learning

  A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2024 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

  4.5k1566582

• yangkky/Machine-learning-for-proteins

  Listing of papers about machine learning for proteins.

  1.6k150182207

• theislab/single-cell-tutorial

  Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

  Language:Jupyter Notebook1.4k45101466

• hemberg-lab/scRNA.seq.course

  Analysis of single cell RNA-seq data course

  Language:TeX6736261360

• mdozmorov/scRNA-seq_notes

  A list of scRNA-seq analysis tools

  Language:R646291149

• aertslab/SCENIC

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

  Language:HTML4262230295

• FunctionLab/selene

  a framework for training sequence-level deep learning networks

  Language:Jupyter Notebook3751710491

• quadbio/scRNAseq_analysis_vignette

  Tutorial for scRNA-seq data analysis beginners using R

  1666457

• google-research/proteinfer

  Deep networks for protein functional inference

  Language:Jupyter Notebook16391527

• tallulandrews/scRNASeqPipeline

  Language:Perl11815160

• grimmlab/MicrobiomeBestPracticeReview

  Current Challenges and Best Practice Protocols for Microbiome Analysis using Amplicon and Metagenomic Sequencing

  Language:Shell1114138

• ArnovanHilten/GenNet

  Framework for Interpretable Neural Networks

  Language:Jupyter Notebook9661513

• samsledje/D-SCRIPT

  A structure-aware interpretable deep learning model for sequence-based prediction of protein-protein interactions

  Language:Jupyter Notebook8965718

• mheinzinger/SeqVec

  Modelling the Language of Life - Deep Learning Protein Sequences

  Language:Python7331325

• canceromics/MeRIPseqPipe

  MeRIPseqPipe：An integrated analysis pipeline for MeRIP-seq data based on Nextflow.

  Language:Nextflow3121819

• PubuduSaneth/cnvScan

  CNV screening and annotation tool

  Language:Python24725

• cellmapslab/DeepWAS

  DeepWAS: Directly integrating regulatory information into GWAS using machine learning

  Language:Jupyter Notebook16415

• Charrick/SDN2GO

  A Deep Learning Model for Protein Function Prediction

  Language:Python16343

• FunctionLab/DeepArk

  Modeling the genomic regulatory codes of fly, mouse, worm, and fish with deep learning

  Language:Python16723

• vam-sin/CATHe

  Deep Learning tool trained on protein sequence embeddings from protein language models to accurately detect remote homologues for CATH superfamilies

  Language:Python11123

• azodichr/GenomicPrediction_2018

  Influence of algorithms, parameter choice, and feature selection on genomic prediction accuracy

  Language:R10407

• FGonzalezLopez/DeepSequencePPI

  Protein-Protein Interaction prediction using a deep RNN-based neural network architecture.

  Language:Jupyter Notebook4231

• vam-sin/deepcys

  A complete Deep Learning solution to predicting the behavior of a given cysteine. The predictions are made using the features from the high resolution protein crystal structures.

  Language:Roff4100

• FelixHeinrich/MIDESP

  Mutual information based detection of epistatic SNP pairs

  Language:Java3132

• insilico/PriorKnowledgeEpistasisRank

  Epistasis network centralities that incorporate prior knowledge

  Language:R3602

• wyp1125/SeqEnhDL

  Multiple machine learning and deep learning models for sequence-based enhancer prediction

  Language:Python3401

• lehner-lab/FOS_JUN_trans_epistasis

  Scripts for "The genetic landscape of a physical interaction", Diss & Lehner 2018

  Language:R2201

• azodichr/Combined_Stress_Response

  Scripts to analyze transcriptional response to combinations of stresses

  Language:Python1200

• azodichr/Tetraselmis_project

  Assembly and annotation of Tetraselmis striata

  1201

• dominikgrimm/deeplearning-models

  A collection of various deep learning architectures, models, and tips

  Language:Jupyter Notebook1000