A5074273360- RNA modifications and cancer
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Molecular Biology Techniques and Applications
- Genomics and Rare Diseases
- RNA Research and Splicing
- Single-cell and spatial transcriptomics
- Cancer Genomics and Diagnostics
- Machine Learning in Bioinformatics
- Cancer-related molecular mechanisms research
Peking University
2022-2024
Abstract Tumor research is a fundamental focus of medical science, yet the intrinsic heterogeneity and complexity tumors present challenges in understanding their biological mechanisms initiation, progression, metastasis. Recent advancements single-cell transcriptomic sequencing have revolutionized way researchers explore tumor biology by providing unprecedented resolution. However, key limitation loss spatial information during preparation. Spatial transcriptomics (ST) emerges as...
Single-molecule Real-time Isoform Sequencing (Iso-seq) of transcriptomes by PacBio can generate very long and accurate reads, thus providing an ideal platform for full-length transcriptome analysis. We present integrated computational toolkit named TAGET Iso-seq transcript data analyses, including alignment, annotation, gene fusion detection, quantification analyses such as differential expression analysis isoform usage evaluate the performance using a public dataset newly sequenced datasets...
Abstract Accurately predicting the effects of mutations in cancer has potential to improve existing treatments and identify novel therapeutic targets. In this paper, we evidence for first time that large-scale pre-trained protein language models (PPLMs) are zero-shot predictors two clinically relevant tasks: identifying diseasecausing patient survival rate. Then benchmark a series state-of-the-art (SOTA) PPLMs on 2279 variants across 20 cancer-related genes. Our empirical results show...