Results for “analysis”

Define, track, and interpret product metrics across discovery, growth, and mature product stages using frameworks like AARRR, North Star, and HEART.

Analyze sprint data with Python scripts for velocity forecasting, health scoring, and retrospective insights to coach agile teams.

Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations.

Perform cheminformatics tasks including molecular I/O, descriptor calculation, fingerprinting, substructure search, and similarity analysis using the RDKit library.

Run standard single-cell RNA-seq analysis pipelines: QC, normalization, dimensionality reduction, clustering, differential expression, and visualization using Scanpy.

Perform astronomical data analysis with Astropy: coordinate transformations, unit conversions, FITS I/O, cosmological calculations, time handling, table operations, and WCS transformations.

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

Performs differential expression analysis on bulk RNA-seq or pseudo-bulk count matrices with QC, PCA, and contrast testing.

Scores genetic compatibility between all male-female pairings in a Genomebook generation, ranking optimal mating pairs based on heterozygosity, trait complementarity, and disease risk.

Provides best practices for optimizing MariaDB queries, including indexing strategies, EXPLAIN analysis, pagination, histogram statistics, and MariaDB-specific optimizer settings.

Create data-driven charts with Vega-Lite and Vega, covering bar, line, scatter, heatmap, area, radar, and word cloud visualizations from structured data arrays.

Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

Maps support capabilities, plans cross-training, and sizes multi-skilling against real proficiency and routing cost.

Analyze images using Azure AI Vision SDK for Java, enabling captioning, OCR, object detection, tagging, and smart cropping.

Simplify molecular cheminformatics with a Pythonic wrapper around RDKit for SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel processing.

Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface, covering loading, preprocessing, drift correction, spike sorting, quality metrics, and unit curation.

Track key macro indicators (VIX, US10Y, DXY, gold, oil, BTC) and get AI-generated impact analysis linked to your portfolio holdings.

Optimizes SQL queries, designs database schemas, and troubleshoots performance issues using execution plan analysis, indexing strategies, and set-based operations.

Optimize PostgreSQL queries, configure replication, and implement advanced database features with EXPLAIN analysis, JSONB operations, extension usage, and VACUUM tuning.

Analyzes uploaded data files with full Python access, producing cleaned datasets, statistical reports, charts, and dashboards via the CellCog coding agent.

Create, analyze, and visualize complex networks and graphs in Python using NetworkX, including graph construction, algorithms, generators, I/O, and plotting.

Provides a pre-built Salesforce Service Cloud data model template with Mermaid diagrams, ASCII fallback, and relationship summaries for documentation and analysis.

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

Use when content analytics, website performance data analysis, audience insights, or comprehensive data-driven reporting is needed. This agent specializes in content and website analytics within the ContentForge AI ecosystem.

Optimize SQL queries, indexes, and database performance across MySQL, PostgreSQL, SQL Server, and Oracle with execution plan analysis and universal tuning techniques.

Analyze network packet captures (PCAP/PCAPNG) using Wireshark, tshark, tcpdump, and Python to reconstruct communications, extract files, and identify malicious traffic.

Detects and ranks trending market themes by analyzing cross-sector momentum, volume, and breadth signals with lifecycle maturity assessment.

Provides expert guidance for systematic backtesting of trading strategies, covering methodology, stress testing, bias prevention, and result interpretation.

Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

Analiza series temporales: tendencia, estacionalidad y pronóstico con Prophet, statsmodels y ML, incluyendo descomposición, tests de estacionariedad y evaluación contra baselines.

Analyzes tabular datasets to understand distributions, data quality, and patterns, including column distributions, missing data, class balance, and summary statistics.

Designs and backtests systematic trading strategies using technical indicators, fundamental analysis, and statistical models, with clear entry/exit rules, risk controls, and documentation.

Guides analysis of Neuropixels recordings from raw data to curated units, covering preprocessing, motion correction, spike sorting, quality metrics, and export.

Search, analyze, and engage with X/Twitter from the terminal, including bookmarks, likes, following, trends, and Grok AI analysis, with export to JSON, CSV, or Markdown.

Identifies which dimension items (pages, campaigns, products, channels, regions) had the biggest increases or decreases for a key metric between two time periods.

Provides deep generative models for single-cell omics analysis, including probabilistic batch correction, transfer learning, differential expression, and multi-modal integration.