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Use when working with Sei — the FunctionLab sequence-to-activity deep learning framework for predicting chromatin profiles and regulatory activity from DNA sequences. Sei takes 4096 bp DNA windows and
Use with AI
Install the MCP server or CLI to instantly fetch Sei documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/sei
BPNet — deep learning framework for learning base-resolution regulatory sequence features from genomics assays (ChIP-seq, ATAC-seq, CUT&RUN). Uses dilated convolutional neural networks to predict TF b
2 shared topics • 2 shared operations
DeepConsensus — Google's gap-aware sequence transformer for improving PacBio CCS (HiFi) read accuracy post-basecalling. Use for: polishing PacBio long reads, reducing insertion/deletion errors in CCS
2 shared topics • 2 shared operations
Use when working with DeepRVAT — a deep learning framework for rare variant association testing (RVAT) that learns gene-level embeddings from rare variant annotations using an auto-encoder, then tests
2 shared topics • 2 shared operations
Geneformer — transformer-based foundation model pretrained on ~30 million single-cell transcriptomes for context-specific gene network analysis. Supports fine-tuning for cell type classification, gene
2 shared topics • 2 shared operations
JAX — Google's high-performance numerical computing library combining NumPy API with automatic differentiation (grad, value_and_grad), just-in-time XLA compilation (jit), automatic vectorization (vmap
2 shared topics • 2 shared operations