find-collaborators

Query PubMed to rank research collaborators by topic overlap and generate reports.

64|12|Updated Apr 7, 2026

Search Tags:#pubmed #data-visualization #collaborators #topic overlap #research-networking #author-profiles #publication-analysis

Ready to run

npx skills add https://github.com/MDhewei/bioinfor-claw --skill find-collaborators

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: find-collaborators
Source: https://github.com/MDhewei/bioinfor-claw/tree/main/lab-search-and-track/find-collaborators
Command: npx skills add https://github.com/MDhewei/bioinfor-claw --skill find-collaborators

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, matplotlib, numpy, pandas, and includes scripts (resource) components.

What problem does it solve?

Identify and rank potential research collaborators based on topic overlap by querying PubMed and compiling a ranked report.

Core Features & Use Cases

Discover collaborators across biomedical topics by cross-referencing topic lists with publication records.
Build author profiles, topic heatmaps, and ranking charts to inform collaboration decisions.
Generate outputs such as collaborators.tsv, collaborator_profiles.md, a topic-author heatmap, and a ranking visualization for reporting.

Quick Start

Run the CLI with topics and optional filters to retrieve the top collaborators.

Frequently Asked Questions about find-collaborators

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I find potential research collaborators by topic overlap on PubMed?▼

You can find potential research collaborators by querying PubMed publication records to cross-reference multiple topics, generating a ranked report with author profiles and a topic overlap heatmap to inform your collaboration decisions.

How do I rank biomedical authors by publication topics and generate a visualization?▼

Rank biomedical authors by querying publication records across topic lists and year ranges, then output a collaborators TSV file, markdown profiles, a topic-author heatmap, and ranking charts for analysis.

Can I filter PubMed author profiles by country, institution, and year range?▼

Yes, you can filter PubMed author profiles by applying country and institution filters alongside specific year ranges to narrow down potential collaborators and generate targeted ranking reports.

Do I need Python, pandas, and matplotlib to build a research networking report?▼

Yes, you need a Python environment with pandas, numpy, matplotlib, and requests installed, along with PubMed eUtils API access, to execute the script and generate the networking analysis outputs.

What is the best way to analyze publication overlap for multiple biomedical research topics?▼

The best way to analyze publication overlap is cross-referencing multiple biomedical topic lists against PubMed records, which produces a ranked report, markdown author profiles, and a topic heatmap for comparison.

Why does my collaborator search require a companion script in lab-search-and-track?▼

Your collaborator search requires the companion script located in the lab-search-and-track/find-collaborators directory because it contains the core processing logic needed to query PubMed and compile the ranked outputs.