🔬🦞 A self-evolving AI research colleague for scientists. 285 skills, zero hallucination, persistent memory.
[Read-Only] All R code and source files for the online guide "Doing Meta-Analysis with R: A Hands-On Guide"
CHAPI (Common Hierarchical Abstract Parser and Information Converter) streamlines code analysis by converting diverse language source code into a unified abstract model, simplifying cross-language development. Chapi 是一个通用层次抽象解析器与信息转换器，它可以将不同编程语言的源代码转换为统一的层次抽象模型。
Tidy data frames and expressions with statistical summaries 📜
A meta-analysis package for R
Produce PRISMA-2020 compliant flow diagrams
TIGMINT: OSINT (Open Source Intelligence) GUI software framework
The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.
Genomic Data Retrieval with R
Agent Skills for medical research — literature search, reporting-guideline & citation checks, statistics, publication figures, submission. Works with Claude Code, Codex, Cursor & GitHub Copilot. Built by a physician-researcher, tested on real publications. MIT.
Coordinate- and image-based meta-analysis in Python
Core tools required for running Canlab Matlab toolboxes. The heart of this toolbox is object-oriented tools that enable interactive analysis of neuroimaging data and simple scripts using high-level commands tailored to neuroimaging analysis.
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Perform forward and backward citation chasing as part of an evidence synthesis project
Rare variant test software for next generation sequencing data
ENIGMA HALFpipe is a user-friendly software that facilitates reproducible analysis of fMRI data
Literature Scanner: Automated collection & analyses of the scientific literature.
Claude Code-powered end-to-end meta-analysis automation: AI-assisted literature review, screening, extraction, analysis, and manuscript generation for systematic reviews and clinical evidence synthesis
An ongoing, collaborative meta-analysis about Human-AI-Interactions. We aggregate data and knowledge to build a non-abrasive, user-friendly prompting framework tailored to LLM mechanics, ensuring reasoning stability and a friction-free prompting environment that is safe for the human psyche and wellbeing.
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