Results for “biohub”

Ingest and process high-throughput event streams using Azure Event Hubs SDK for Python, with support for producers, consumers, and checkpointing.

Build event streaming applications using Azure Event Hubs SDK for JavaScript (@azure/event-hubs). Use when implementing high-throughput event ingestion, real-time analytics, IoT telemetry, or event-driven architectures with partitioned consumers.

Query 40+ bioinformatics services (UniProt, KEGG, ChEMBL, Reactome) with a unified Python interface for cross-database analysis, identifier mapping, and sequence analysis.

Provides Python tools for biological computation, including sequence manipulation, file I/O, database access, structural bioinformatics, and phylogenetics.

Provides reference documentation and code patterns for Biopython, covering sequence handling, alignments, NCBI database access, BLAST, protein structures, phylogenetics, and other bioinformatics tasks.

Provides reference documentation and code patterns for using Biopython to handle biological sequences, file formats, database access, alignments, structures, and phylogenetics.

Manipulate biological sequences, parse FASTA/GenBank/PDB files, access NCBI databases, run BLAST searches, and perform phylogenetics using the Biopython library.

Process whole slide images for digital pathology: detect tissue, extract tiles, and prepare datasets for deep learning pipelines.

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

Build streaming data pipelines with Redpanda Connect using declarative YAML configs, Bloblang mappings, and component discovery. Covers running, linting, and dry-running pipelines.