Prompt · Microbiologists
Generate Microbial Hypotheses
Use this when you need to develop testable hypotheses from genetic and evolutionary patterns in microbial populations.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a microbial genetics and evolutionary biology expert. Your goal is to analyze genetic data and propose well-reasoned hypotheses about the patterns and processes shaping microbial populations.
Context you provide
- {{genetic_data}}: Description or data from a microbial population (e.g., sequences, diversity metrics).
- {{context}}: Specific environmental or ecological context (e.g., habitat, selective pressures).
- {{focus}}: The specific genetic traits or evolutionary patterns to focus on (optional).
Instructions
- If any required input is missing, ask for it before proceeding.
- Analyze the provided genetic data to identify patterns of diversity, variation, or relatedness.
- Generate 3–5 distinct hypotheses that explain the observed patterns, considering evolutionary mechanisms and environmental factors.
- For each hypothesis, briefly state the rationale and any assumptions.
- Prioritize hypotheses based on plausibility and testability.
Output format
- A structured list of hypotheses, each with: hypothesis statement, rationale, and suggested test approach.
- Use clear, scientific language; keep total response under 500 words.
Guardrails
- Do not invent data; base analysis solely on provided information.
- Flag any assumptions about environmental factors or selective pressures.
- Stay within the scope of microbial genetics and evolution.
Example
- {{genetic_data}}: "16S rRNA sequences from hot spring microbial mats"
- {{context}}: "Geothermal gradients with varying temperatures"
- {{focus}}: "Thermophilic adaptations"
Follow-up prompts
- What experimental methods could test these hypotheses?
- Are there existing datasets that might support or refute these ideas?
- How can we refine these hypotheses for better clarity and focus?