#Genomics

6 posts tagged with "Genomics"

AlphaGenome: One Model for the Other 98% of Your DNA

2026-01-29T16:00:00+00:00•12 min read

#deep-learning #genomics #alphagenome #deepmind #variant-prediction #non-coding-dna

Google DeepMind's AlphaGenome reads 1 million base pairs of DNA and predicts thousands of regulatory functions at single-nucleotide resolution, beating 25 of 26 specialized models.

How AlphaGenome Tackles Variant Effect Prediction

2026-01-29T12:00:00Z•8 min read

#genomics #deep learning #variant effect prediction #alphagenome #computational biology

AlphaGenome processes 1 million DNA base pairs to predict variant effects across 7,000+ genomic tracks in one second, outperforming specialized models on 25 of 26 VEP benchmarks.

How AlphaGenome Models Gene Regulation: 2D Embeddings, Splicing, and the Race to Read Non-Coding DNA

2026-01-29T11:00:00Z•18 min read

#alphagenome #genomics #deep learning #splicing #computational biology #google deepmind #variant interpretation

A technical look at AlphaGenome's architecture, its 2D pairwise embeddings for splicing prediction, and what the model means for clinical variant interpretation.

A Bioinformatician's Guide to Choosing Genomic Foundation Models

2026-01-19T10:30:00Z•22 min read

#foundation models #genomics #bioinformatics #deep learning #protein language models #dna models #esm-2 #dnabert-2 #hyenadna #scgpt

A practical guide to selecting genomic foundation models for bioinformatics tasks. Covers ESM-2, DNABERT-2, HyenaDNA, Nucleotide Transformer, scGPT, and Evo with specific recommendations for DNA sequence analysis, protein structure prediction, and single-cell analysis based on hardware requirements, inference speed, and task type.

When the Algorithm Can't Explain Itself: ML Interpretability in Precision Oncology

2026-01-03T10:00:00Z•19 min read

#machine learning #precision oncology #explainability #genomics #graph neural networks #clinical ai

Machine learning models now outperform FDA-approved biomarkers in predicting treatment response, but the best-performing models often resist explanation. Here's how precision oncology is navigating the trade-off between performance and interpretability.

Why Two Gene Discovery Methods Found Completely Different Genes (And Why That Matters for Your Health)

2025-11-06T10:00:00+00:00•14 min read

#genomics #gwas #bioinformatics #drug-discovery #statistical-genetics

How gene length, trait specificity, and luck systematically distort which genes we think are important for disease, and what researchers should do about it