Data Science & ML Habilidades de Claude

Astropy Scientific Computing

Provides comprehensive tools for astronomical data analysis, including coordinate transformations, unit conversions, and FITS file manipulation.

Genomic Interval Machine Learning

Builds and trains machine learning models on genomic interval data to generate embeddings for regions, single cells, and metadata.

AnnData Scientific Data Management

Manages annotated data matrices for single-cell genomics and large-scale biological datasets using the Python AnnData framework.

Pydicom Medical Imaging

Processes DICOM medical imaging files for metadata extraction, pixel data manipulation, and secure patient data anonymization.

Blinding Procedures

Minimizes experimental bias by implementing structured blinding protocols and objectivity standards for scientific research studies.

Tool Experimenter

Systematically refines and validates research tools through multi-phase iterative testing and rigorous data-driven evaluation.

Results Interpretation

Interprets and reports statistical findings with accuracy, prioritizing effect sizes and confidence intervals over simple p-value significance.

MQL5 Python Workspace

Automates the translation of MetaTrader 5 (MQL5) indicators into validated Python implementations for algorithmic trading.

Hypothesis Testing

Guides the selection, assumption checking, and interpretation of statistical hypothesis tests for rigorous research data analysis.

MLflow Python Integration

Automates experiment tracking and backtest logging using the MLflow Python API and QuantStats metrics.

Statistical Power Analysis

Calculates statistical power and determines optimal sample sizes to ensure experimental designs meet rigorous scientific and funding standards.

Randomization

Implements rigorous random assignment procedures for scientific experiments to minimize selection bias and meet CONSORT standards.

Risk of Bias Assessment

Evaluates methodological quality and potential biases in research studies using industry-standard frameworks for systematic reviews.

Knowledge Base Builder

Creates and optimizes elizaOS knowledge bases using RAG, smart chunking strategies, and semantic search integration.

Meta-Analysis

Conducts quantitative synthesis by pooling effect sizes across multiple research studies to calculate summary effects and assess statistical heterogeneity.

Subgroup Analysis

Conducts detailed subgroup analyses to examine effect moderation, explore dataset heterogeneity, and identify differential outcomes across specific populations.

Human Metabolome Database Explorer

Accesses the Human Metabolome Database (HMDB) to retrieve detailed chemical properties, biomarker data, and spectral information for over 220,000 metabolites.

Times Square Integration

Integrates the Times Square notebook execution system into web applications using established patterns for data fetching, real-time updates, and URL management.

Integrative Methylation-Expression Analysis

Integrates differential methylation and gene expression datasets to identify coordinated epigenetic regulation patterns and classify regulatory relationships.

Global Methylation Profiling

Performs genome-wide DNA methylation analysis to characterize patterns, genomic feature distributions, and sample similarities from sequencing data.

RAG Chunking Strategies

Implements optimized document splitting and processing workflows for Retrieval-Augmented Generation (RAG) systems.

FlowerPower Pipeline Manager

Automates the creation and management of robust data pipelines using Hamilton DAGs and the FlowerPower framework.

Effect Size Calculation

Calculates and interprets standardized effect sizes to quantify the practical significance of research findings beyond statistical significance.

Sensitivity Analysis

Evaluates the robustness of research findings by testing how conclusions change under varying analytical assumptions and data conditions.

Inclusion Criteria

Systematically applies eligibility criteria during literature screenings to ensure rigorous and reproducible study selection in research workflows.

PRISMA Flow Diagram

Generates standardized PRISMA 2020-compliant flow diagrams to document the study selection process in systematic literature reviews.

Experiment Design

Designs methodologically rigorous scientific experiments and research studies following NIH rigor standards and best practices.

Data Visualization

Generates publication-quality data visualizations and scientific figures following academic design and statistical best practices.

Synthesis Matrix

Generates structured evidence synthesis matrices to organize, compare, and analyze research data across multiple studies.

BAM Filtration

Filters raw BAM files by removing mitochondrial reads, PCR duplicates, and blacklisted regions to prepare genomic data for peak calling.