bioinfo-statistics

Perplexity의 추천 1~10 : 유전체 & 전사체 AI 모델Evo2: 100,000종 DNA 기반, 돌연변이 예측 및 유전체 설계.​DNABERT-2: DNA 서열 해석에 특화된 BERT 기반 AI.​Nucleotide Transformer: 대규모 유전체 데이터 학습용 Transformer 기반 모델.​GeneFormer: 유전자 기능 및 표현 해석을 위한 전사체 모델.​scFoundation: 단일 세포 데이터 분석용 파운데이션 모델.​scGPT: 단일 세포 transcriptome 분석용 GPT 모델.​RNA-FM: RNA 시퀀스 기능 및 구조 예측 AI(비공개).​RNABERT: RNA 구조/기능 예측에 특화된 BERT 모델.​GENA-LM: 인간 DNA를 BPE 토큰화로 처리하는 랭귀지 ..

AbstractRNA-protein interactions critically regulate gene expression and cellular processes, yet their comprehensive mapping remains challenging due to their structural diversity. We introduce PRIM-seq (protein-RNA interaction mapping by sequencing), a method for concurrent de novo identification of RNA-binding proteins and their associated RNAs. PRIM-seq generates unique chimeric DNA sequences ..

THE PAPER IN BRIEF• Cancer is a dynamic condition but tracking its evolution using genomic analyses of single tumour samples is challenging.• Certain sites in the genome are epigenetically modified with a methyl group, and some of these sites stochastically fluctuate between a methylated and an unmethylated state over time.• The methylation pattern of these sites in a population of cancer cells ..

Gimeno-Valiente, F., Castignani, C., Larose Cadieux, E. et al. DNA methylation cooperates with genomic alterations during non-small cell lung cancer evolution. Nat Genet (2025). https://doi.org/10.1038/s41588-025-02307-xAbstractAberrant DNA methylation has been described in nearly all human cancers, yet its interplay with genomic alterations during tumor evolution is poorly understood. To explor..

Gabbutt, C., Duran-Ferrer, M., Grant, H.E. et al. Fluctuating DNA methylation tracks cancer evolution at clinical scale. Nature (2025). https://doi.org/10.1038/s41586-025-09374-4AbstractCancer development and response to treatment are evolutionary processes1,2, but characterizing evolutionary dynamics at a clinically meaningful scale has remained challenging3. Here we develop a new methodology c..

Bhatt, B.J., Ghosh, S., Mazurak, V. et al. Molecular subtypes of human skeletal muscle in cancer cachexia. Nature (2025). https://doi.org/10.1038/s41586-025-09502-0 AbstractCancer-associated muscle wasting is associated with poor clinical outcomes1, but its underlying biology is largely uncharted in humans2. Unbiased analysis of the RNAome (coding and non-coding RNAs) with unsupervised clus..

AbstractAtherosclerosis, a major cause of cardiovascular diseases, is characterized by the buildup of lipids and chronic inflammation in the arteries, leading to plaque formation and potential rupture. Despite recent advances in single-cell transcriptomics (scRNA-seq), the underlying immune mechanisms and transformations in structural cells driving plaque progression remain incompletely defined...

https://www.nature.com/articles/s41591-025-03945-8#citeas AbstractAlthough genomic sequencing presents groundbreaking newborn screening (NBS) opportunities, critical feasibility and utility questions remain. Here we present initial results from the Early Check program—an observational study assessing the feasibility and clinical utility of genomic NBS in North Carolina. Recruitment was st..

Costanzo, M.C., Harris, L.W., Ji, Y. et al. Realizing the promise of genome-wide association studies for effector gene prediction. Nat Genet (2025). https://doi.org/10.1038/s41588-025-02210-5 몇가지 생각들 - Variant의 effector gene prediction (variant의 영향을 밝히는 것)과 variant를 활용해 gene-disease 관계를 밝히는 것(mendelian randomization 등)은 약간 다른 문제임- GWAS 결과 상 어떤 유전자에 coding region에 variant가 있고 protein altering va..

Hazelwood, E., Canson, D.M., Deslandes, B. et al. Multi-tissue expression and splicing data prioritise anatomical subsite- and sex-specific colorectal cancer susceptibility genes. Nat Commun 16, 5043 (2025). https://doi.org/10.1038/s41467-025-60275-6 궁금한 점: - TWAS와 MR의 차이, 둘 다 할 이유? - TWAS에서 어떻게 여러 tissue 정보 통합해서 통계적 power를 높이는지, 그것을 MR 분석에 적용할 수 있는지 - Splicing의 영향도 고려하는 점 - splicing이 protein fu..