3. Data, Science & AI

Coordinates multi-agent workflows, enabling task delegation, worker spawning, and parallel execution management for AI systems.

Manages multi-agent coordination, task delegation, status checks, and messaging within agent-swarm architectures.

Searches and archives significant global news events (7-day window) with entity tracking and semantic deduplication.

Provides real-time cryptocurrency balance checks for ETH and ERC-20 tokens using the Etherscan API.

Manages AI's internal memory by reviewing, consolidating, organizing, and cleaning to prevent context overload and maintain optimal performance.

Infers chromatin states from histone modification ChIP-seq data using chromHMM for genomic segmentation and annotation.

Performs GO and KEGG functional enrichment analysis on genomic regions or gene lists using HOMER, generating R-based visualizations for biological interpretation.

Analyzes and visualizes average DNA methylation profiles around target genomic regions such as TSS or CTCF peaks.

Annotates chromatin loops with enhancer-promoter assignments and CTCF-peak overlap, automatically constructing missing sets and standardizing loop categories.

Annotates genomic regions (promoters, exons, TSS) and visualizes feature distributions using Homer and ChIPseeker for genomic data analysis.

Identifies transcription factor binding motifs in genomic regions using HOMER and PSSMs, providing precise coordinates for ChIP-seq and ATAC-seq peaks.

Performs genomic peak calling for ChIP-seq and ATAC-seq data using MACS3 with adaptive parameter tuning based on user feedback.

Performs ChIP-seq specific quality control by calculating protein-binding assay metrics including Cross-correlation (NSC/RSC) and FRiP.

Cleans genomic BAM files by removing mitochondrial reads, blacklisted regions, PCR duplicates, and unmapped reads to prepare for peak calling.

Generates technical quality metrics for aligned BAM files including read depth, mapping quality, and error rates using samtools and Picard.

Analyzes genome-wide DNA methylation profiles from WGBS data, computing density distributions, genomic feature mappings, and sample clustering via PCA.

Provides a streamlined workflow for methylation variability and epigenetic heterogeneity analysis from WGBS data, quantifying CpG-level variability and identifying highly variable CpGs (HVCs).

Performs differential TAD analysis on Hi-C contact matrices to identify condition-specific chromatin domain alterations using HiCExplorer.

Performs PCA-based A/B compartments calling on Hi-C .mcool datasets using cooler-tools and cooltools for genomic data analysis.

Integrates CpG methylation data with chromatin features like ATAC-seq and histone marks through a scientific data pipeline.

Performs A/B compartment shift analysis on Hi-C genomic data to compare spatial chromosomal organization between two biological samples.

Performs correlation analysis between differential methylation and gene expression to identify genes with coordinated epigenetic regulation, including preprocessing and integration workflows.

Automates normalization of Hi-C genomic data files, checking for existing normalization and applying balancing when necessary.

Detects hierarchical TAD structures from Hi-C contact maps using OnTAD, processing .cool/mcool files to extract chromosome-specific data for 3D genome analysis.