3. Data, Science & AI

Breaks down complex queries into step-by-step plans to improve multi-hop reasoning performance in AI tasks.

Designs efficient and specific gRNA sequences for CRISPR-Cas9 gene editing experiments, optimizing target specificity and experimental success.

Deploys parallel AI agents (Researcher, Reviewer, Safety Officer) to collaboratively solve complex biomedical research problems.

Optimizes experimental and black-box functions using Bayesian methods with Gaussian Processes, enhancing efficiency in automated laboratory settings.

Extracts medical entities (diseases, medications, procedures) from clinical text using rule-based or LLM-powered NLP techniques.

Predicts 3D protein structures from amino acid sequences using ESMFold and AlphaFold3 AI models.

Provides a unified interface for annotating single-cell RNA-seq data using marker genes, CellTypist, and LLMs.

AI-driven matching of patient profiles to clinical trials using vector similarity and eligibility criteria for precise trial recommendations.

Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to detect anomalies and generate diagnostic reports.

Classifies genetic variants using ACMG guidelines for clinical interpretation in genomic data analysis.

Provides computational analysis of molecular properties, toxicity, and synthetic accessibility for cheminformatics applications.

Provides tools for integrating and processing Electronic Health Records (EHR) data using the HL7 FHIR standard, enabling healthcare data interoperability.

Designs CRISPR-Cas9 guide RNA sequences with off-target analysis for precise gene editing.

Tracks institutional investor ownership changes via 13F filings to identify stocks with significant smart money accumulation or distribution for investment insights.

Expert guidance for systematic backtesting of quantitative trading strategies, covering robustness testing, slippage modeling, and bias prevention.

Transcribes audio/video from URLs using local WhisperKit AI, with optional AI analysis of transcripts upon request.

Enables defining metrics, tracking KPIs, creating dashboards, and conducting A/B tests to drive data-informed product decisions.

Analyzes YouTube and TikTok video performance metrics to identify trends, explain key indicators, and deliver growth-focused recommendations.

Analyzes user portfolio holdings via Alpaca integration, computing risk metrics, allocation, and diversification to provide rebalancing recommendations.

Fetches economic events and market-moving data from FMP API, generating chronological markdown reports with impact assessments for specified date ranges.

Quantitatively assesses U.S. market bubble risk using objective metrics and a revised Minsky/Kindleberger framework for data-driven investment decisions.

Retrieves and organizes upcoming US stock earnings announcements for mid-cap and above companies via FMP API, presented in a clean markdown table.

Screens US stocks for high-quality dividend opportunities using value metrics, yield thresholds, and growth trends via API-driven analysis.

Statistical arbitrage tool identifying cointegrated stock pairs, analyzing spread behavior, and providing entry/exit recommendations using z-scores and backtesting for market-neutral strategies.