调研与学习技能

Create population-level clinical decision support documents for research and pharmaceutical work. The skill structures biomarker-stratified cohort analyses and evidence-graded treatment recommendations, with statistical outcome comparisons and decision algorithms in LaTeX or PDF format.

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• Comparing outcomes across biomarker groups
• Drafting evidence-graded treatment guidelines
• Preparing trial subgroup analyses

Create a baseline characteristics section for a meta-analysis from supplied study data. The skill produces a descriptive paragraph and a formatted Markdown table in Chinese or English, then combines them into a consistent results section with a table reference.

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• Draft a baseline characteristics section from meta-analysis data
• Create the accompanying Markdown table in Chinese or English
• Format the paragraph and table into a consistent results section

Turn a research paper into a journal club slide outline with background context, key figure explanations, critical appraisal points, and discussion questions. Set the audience level and presentation time to shape the plan.

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• Preparing a lab meeting presentation
• Introducing a paper to graduate students
• Practicing critical appraisal

Turn a biomedical research question into a structured retrospective or prospective clinical cohort protocol. Define the population, eligibility, time zero, follow-up, endpoints, variables, and one primary analysis plan, while flagging uncertain data availability and design limitations.

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• Planning a retrospective EHR cohort study
• Choosing retrospective or prospective cohort structure
• Defining cohort eligibility, time zero, and follow-up

Design a structured drug-safety signal study using FAERS or a similar spontaneous-report database. The plan can define drug and comparator groups, adverse-event terms, seriousness filters, subgroup analyses, and Reporting Odds Ratio (ROR) comparisons, while setting limits on interpretation.

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• Planning a FAERS drug-safety study
• Comparing safety signals across a drug class
• Stratifying reports by indication or patient group

Turn a fixed drug and adverse effect into a structured network pharmacology research plan. Compare four workload levels and map target collection, pathway interpretation, docking, optional validation, references, figures, dependencies, and evidence limits.

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• Planning a one-drug, one-adverse-effect study
• Comparing Lite through Publication+ research scopes
• Adding pathway, docking, or validation modules to a study plan

Turn a biomedical research direction into a structured plan combining Mendelian randomization, a method for testing causal links, with single-cell RNA sequencing. Compare four workload levels, choose a primary plan, and outline analyses, figures, validation, and verified references.

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• Plan an MR and single-cell study from a disease or mechanism theme
• Compare feasible study plans for different time and resource limits
• Map analysis steps to figures and validation strategies

Create an executable Mendelian randomization study plan from a proposed exposure and outcome. It selects a suitable design, outlines genetic instrument choices and analyses, compares four workload levels, and sets validation steps and boundaries for interpreting causal claims.

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• Planning an MR study for an exposure and outcome
• Choosing between one-way and bidirectional MR
• Designing sensitivity checks for genetic instruments

Creates a structured research plan for mapping one drug’s safety profile in FAERS, a database of adverse event reports. It compares four workload levels and outlines signal detection, subgroup or onset analysis, validation limits, and supporting literature needs.

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• Plan a broad FAERS safety scan for one drug
• Compare study plans at different workload levels
• Add age, sex, onset, or seriousness analyses

Turn adverse event case details into structured safety narratives for regulatory reporting. The skill checks required fields, organizes the event timeline, supports MedDRA coding and causality assessment, and formats drafts for CIOMS I, ICH E2B R3, or FDA MedWatch.

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• Drafting an ICSR narrative from an adverse event case
• Checking a case for missing CIOMS I fields
• Organizing drug and event dates into a timeline

Creates structured bulk transcriptome research plans for cancer studies focused on programmed or regulated cell death. It compares four workload levels and recommends a primary design, with analysis steps, figures, validation, a minimal plan, an upgrade path, and verified literature or a transparent search strategy.

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• Planning a ferroptosis study in a cancer type
• Designing a prognostic signature and immune analysis
• Comparing Lite through Publication+ study workloads

Build a structured study plan for prognostic biomarkers, from cohort and follow-up design to endpoint selection, marker screening, risk modeling, and validation. It helps researchers distinguish prognosis from diagnosis or treatment-response prediction and surface key feasibility and bias risks.

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• Planning a cohort study for a survival biomarker
• Defining follow-up and endpoints for recurrence risk
• Choosing between a single marker and a prognostic score

Plan locus-level studies that compare GWAS findings with eQTL, pQTL, sQTL, or related molecular signals. Get a structured workflow, candidate prioritization, workload options, and clear limits on what colocalization evidence can establish.

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• Planning an eQTL–GWAS study for a disease or trait
• Prioritizing candidate genes at a GWAS locus
• Connecting pQTL or sQTL signals with GWAS findings

Turn a biomedical association or mechanism finding into an ordered validation plan. The skill identifies what current evidence supports, highlights the weakest link, and separates the next essential steps from stronger upgrades and optional extensions.

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• Plan the next validation steps for a pathway finding
• Decide which experiments are essential and which can wait
• Identify the weakest link in a biomarker evidence chain

Turn a cancer context, fixed target gene, and validation goal into a structured single-gene oncology study plan. It compares four workload levels, recommends a primary approach, maps analysis dependencies, and retrieves verified literature to support design choices.

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• Plan a single-gene cancer biomarker study
• Compare lightweight and publication-focused study designs
• Build a gene study plan with a defined validation goal

Turn medical notes, textbook excerpts, lecture summaries, or Q&A material into focused Anki cards. The workflow produces an importable TSV or card blueprint, states assumptions, and flags source material that is incomplete or too ambiguous to convert safely.

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• Convert lecture notes into focused recall cards
• Create drug mechanism and side-effect cards
• Build anatomy cards covering location and function

Builds a structured case-control study blueprint from a clinical research question. It clarifies whether the design fits, how to define and sample cases and controls, whether matching is justified, how to measure exposure, and which biases and interpretation limits need attention.

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• Planning a case-control study for a rare clinical outcome
• Choosing a defensible control sampling strategy
• Deciding whether and how to match cases and controls

Turn a disease and process-related gene or pathway theme into a structured diagnostic biomarker bioinformatics study plan. Compare four workload levels, then get a recommended workflow, figure plan, validation hierarchy, minimal version, upgrade path, and verified literature or a search strategy when browsing is unavailable.

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• Designing a process-related biomarker study
• Planning DEG and WGCNA integration
• Building a diagnostic model and nomogram workflow

Turn one or more already identified biomedical research gaps into a traceable study plan. The output recommends one primary protocol, maps each gap to design choices, and lays out workflow, figures, validation, a minimal version, and an upgrade path without inventing references.

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• Turning an audited research gap into a study protocol
• Choosing a design for several candidate biomedical gaps
• Planning a minimal study and a publication upgrade path

Find recent algorithms that fit a biomedical research question, its data type, goals, and resource limits. The skill prioritizes recent literature, verifies primary method papers, checks published uses when available, and separates practical recommendations from baselines and unverified names.

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• Finding recent methods for a disease-specific research project
• Matching algorithms to omics data and a study aim
• Checking whether a named biomedical algorithm is real and relevant

Develop an assumption-aware sample size and power planning memo for clinical or translational studies. Identify the design and endpoint that drive planning, assess uncertain inputs, compare feasible scenarios, and outline fallback options without inventing precision when key assumptions are missing.

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• Planning enrollment for a clinical study
• Assessing a fixed cohort’s ability to address an endpoint
• Framing sample size for a biomarker study

Condense an academic paper into a structured abstract of up to 250 words, organized by background, objective, methods, results, and conclusion. It aims to retain key quantitative findings and supports papers from several research fields; figures and charts are not interpreted.

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• Creating a concise abstract from a research paper
• Summarizing empirical studies while retaining key statistics
• Preparing structured summaries across multiple papers

Design phenotype-scoring bioinformatics studies around a disease and a user-defined pathway, process, or molecular signature. Get four workload options, a recommended workflow, validation plan, figures, and literature references that are verified when search is available.

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• Planning a disease signature discovery study
• Designing phenotype scoring and feature selection
• Adding immune or single-cell interpretation

Plan a drug repurposing study from a disease, mechanism, or omics finding. The skill connects drug-target logic, expression patterns, and clinical evidence where relevant, then lays out candidate prioritization and validation steps while keeping research hypotheses separate from treatment advice.

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• Planning a repurposing study from disease or omics evidence
• Connecting a biological target to existing drug candidates
• Combining expression reversal and mechanism evidence