ni-lab / personalized-expression-benchmarkLinks
Evaluating genomic sequence models for explaining personalized expression variation
☆19Updated last year
Alternatives and similar repositories for personalized-expression-benchmark
Users that are interested in personalized-expression-benchmark are comparing it to the libraries listed below
Sorting:
- code to run EPInformer for gene expression prediction and gene-enhancer link prediction☆43Updated 2 weeks ago
- Pytorch implementation of the Borzoi model from Calico, and Flashzoi, a 3x faster Borzoi enhancement.☆75Updated 3 weeks ago
- PyTorch implementation of Basenji2.☆16Updated 5 months ago
- Computational Optimization of DNA Activity (CODA)☆61Updated 6 months ago
- For fine-tuning Enformer using paired WGS & gene expression data☆22Updated last month
- ☆24Updated last year
- ☆24Updated last year
- deep learning-inspired explainable sequence model for transcription initiation☆96Updated 7 months ago
- ☆41Updated 2 months ago
- ☆32Updated 8 months ago
- RNA-seq prediction with deep convolutional neural networks.☆198Updated last month
- Code repository for study ''Evaluating the representational power of pre-trained DNA language models for regulatory genomics"☆22Updated last year
- code to run sei and obtain sei and sequence class predictions☆109Updated 2 years ago
- Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.☆98Updated 3 weeks ago
- Polygraph evaluates and compares groups of nucleic acid sequences based on their sequence and functional content for effective design of …☆35Updated 6 months ago
- Machine learning methods for DNA sequence analysis.☆55Updated last month
- Models and datasets for perturbational single-cell omics☆164Updated 3 years ago
- This repository hosts a minimal version of a Python API for BPNet.☆49Updated last month
- ☆21Updated 5 months ago
- A lite implementation of tfmodisco, a motif discovery algorithm for genomics experiments.☆84Updated 2 weeks ago
- Toolset for training quantitative sequence to function models.☆23Updated last year
- C.Origami, a prediction and screening framework for cell type-specific 3D chromatin structure.☆79Updated last year
- Evaluation framework for computationally inferred gene networks from single-cell data.☆15Updated 3 weeks ago
- Bias factorized, base-resolution deep learning models of chromatin accessibility (chromBPNet)☆179Updated 3 weeks ago
- sequence-based prediction of multiscale genome structure from kilobase to whole-chromosome scale☆92Updated 7 months ago
- Decima is a Python library to train sequence models on single-cell RNA-seq data.☆47Updated last week
- Modeling complex perturbations with CellFlow☆87Updated last week
- Analyses related to the Borzoi paper.☆19Updated 2 weeks ago
- scPerturb: A resource and a python/R tool for single-cell perturbation data☆148Updated 7 months ago
- ☆17Updated 11 months ago