Popular GitHub Repositories for Rna Sequencing

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

一种基于迭代多大型语言模型的共识框架，用于提高单细胞RNA测序数据中细胞类型注释的准确性

Colab Notebooks covering deep learning tools for biomolecular structure prediction and design

DANCE: a deep learning library and benchmark platform for single-cell analysis

DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

gRNAde: Geometric Deep Learning for 3D RNA inverse design (ICLR 2025 Spotlight)

LucaProt: A novel deep learning framework that incorporates protein amino acid sequence and structural information to predict protein function.

Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with extensive customized reports

Code for the tutorial/review paper for RL-based-fine-tuniing. In this code, we especially focus on the design of biological sequences like DNA (enhancers) and RNA (UTRs) design.

RiboNucleic Acid (RNA) Language Model

Code for our Nature Scientific Reports paper "A universal framework for accurate and efficient geometric deep learning of molecular systems"

Nucleic Acids Research 2024：RNA-MSM model is an unsupervised RNA language model based on multiple sequences that outputs both embedding and attention map to match different types of downstream tasks.

scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics

Deep learning datasets for RNA 3D and 2.5D structures.

Primary RNA sequence model

Wasserstein Generative Adversarial Network for analysing scRNAseq data

基于ZooKeeper一致性协议的分布式序列生成器

UniTVelo, Temporally Unified RNA Velocity for single cell trajectory inference

TransfoRNA: Navigating the Uncertainties of Small RNA Annotation with an Adaptive Machine Learning Strategy