Developing advanced tools to improve accuracy and accessibility for long-read RNA sequencing
In the ever-evolving world of computational biology, one of the greatest challenges has always been…
Browsing: Computational Biology
New AI tool pinpoints gene splicing with unmatched precision
A recent innovation from Johns Hopkins researchers enables deeper insights into gene function and disease-linked…
scGraphformer – unveiling cellular heterogeneity and interactions in scRNA-seq data using a scalable graph transformer network
Single-cell RNA sequencing (scRNA-seq) has become a cornerstone tool in modern biology, allowing researchers to…
MST-m6A – a novel multi-scale transformer-based framework for prediction of m6A modification sites
In recent years, scientists have found that cells use small chemical “tags” on RNA molecules…
REDalign – accurate RNA structural alignment using residual encoder-decoder network
RNA molecules are essential for various biological processes, and studying them helps scientists understand how…
scHetG – Structure-preserved integration of scRNA-seq data using heterogeneous graph neural network
Single-cell RNA sequencing (scRNA-seq) is a powerful technique that allows scientists to study individual cells…