리서치·학습 스킬

Create a structured, practice-ready pitch for an academic conference poster. Choose a 30-second, 60-second, or three-minute duration, and use the poster title and available information to shape a concise spoken introduction with clear assumptions and scope.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare a 30-second introduction for a poster session
• Draft a one-minute explanation of a research poster
• Practice a three-minute poster presentation

Finds claims in a biomedical paper that need citations, searches PubMed for relevant articles, and adds PMID markers to a new Markdown copy. It also creates a separate file of candidate references for later formatting with a reference manager.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add PubMed references to a biomedical manuscript
• Find sources for claims in a review article
• Create a candidate reference list from a paper draft

Stress-test a biomedical grant proposal with a structured simulation of NIH peer review. It scores five review criteria, identifies strengths and weaknesses, drafts a summary statement, and suggests prioritized revisions; scores are simulated and may differ from real reviewers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a biomedical grant before submission
• Finding weaknesses in specific aims or research approach
• Comparing an original and revised proposal

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• 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

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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

Design a comparative bioinformatics study linking two related diseases through shared genes or biomarkers. It lays out four workload levels, recommends a primary plan, and organizes analyses such as enrichment, hub-gene selection, machine learning, immune interpretation, and validation with clear evidence limits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a shared biomarker study for two diseases
• Comparing Lite, Standard, Advanced, and Publication+ study plans
• Structuring public-data validation and immune analyses

Shape a biomedical study idea into a realistic plan based on available samples, data, time, budget, lab capacity, and team skills. The skill identifies the main constraints, narrows the study route, defines a minimum executable version, and flags dependencies and assumptions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Scale a biomedical project to fit a limited timeline or budget
• Choose a feasible route when lab or validation resources are uncertain
• Narrow a study idea to the minimum version that can answer its core question

Build a structured bioinformatics study plan for non-oncology diseases using bulk transcriptome data and a process-related gene theme. Compare four workload levels and define analysis steps, validation logic, figures, a minimal plan, and a publication upgrade path.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a non-oncology biomarker study from public expression data
• Combining differential expression with a biological gene set
• Designing hub-gene, ROC, or immune analysis workflows

Plan a bulk-transcriptome tumor biomarker study guided by immune infiltration. The skill structures analysis from differential expression and immune estimates through feature selection and diagnostic modeling, with four workload levels, validation options, and a figure plan.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a bulk-expression diagnostic biomarker study for a cancer type
• Linking immune infiltration estimates to candidate biomarkers
• Scoping machine-learning feature selection and diagnostic modeling

Creates a structured comparative network toxicology study plan for two related exposures and one shared toxic outcome. It maps shared and exposure-specific targets, proposes enrichment and network analyses, and lays out four workload levels, validation options, figures, and a cautious evidence-based interpretation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing a parent compound and its metabolite
• Planning shared and specific target analysis for two chemicals
• Designing a comparative toxicology study with validation options

Organize research team contributions to support author-order decisions, assign CRediT contributor roles, and prepare journal-ready statements. The skill can also flag possible inequities and provide recommendations for discussing authorship in collaborative projects.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Discussing author order for a research manuscript
• Mapping team contributions to CRediT roles
• Preparing a journal contributor statement

Pressure-test a biomedical study design before data collection by classifying variable roles, identifying plausible confounders, and choosing how to control them. Get a reasoned adjustment strategy, likely bias risks, and mitigation steps, with uncertainty and residual bias made explicit.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning confounder control for an observational study
• Deciding which variables to adjust for
• Comparing matching, stratification, and weighting

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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

Refine a broad biomedical research aim into a bounded, measurable objective that can guide study design. Identify the objective type, missing details, and exploratory versus confirmatory intent, then provide versions suited to plain-language, protocol, and downstream planning needs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Narrow a broad biomedical research aim before choosing a study design
• Identify missing populations, outcomes, comparisons, or time frames
• Separate exploratory questions from confirmatory objectives

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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

Plan a computational study that compares gene expression across two diseases to identify shared biomarkers or hub genes. It lays out four workload options, recommends a primary workflow, and organizes analysis, validation, figures, and literature support.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a shared biomarker study for two diseases
• Comparing differential expression and shared gene signals
• Designing hub-gene prioritization and diagnostic evaluation

Create a research plan linking one compound or exposure to a disease or toxic phenotype. Compare target overlap, enrichment, protein interaction networks, docking, and optional expression checks across four workload levels, while clearly limiting mechanistic claims to the evidence available.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a network toxicology study for one pollutant and disease
• Comparing target overlap and pathway analysis options
• Adding docking or expression data as validation branches

Plan validation before a medical study begins by matching the study’s main claim and available resources to appropriate validation layers. The skill distinguishes internal, external, temporal, and functional evidence, and clarifies what conclusions each can support.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning validation for a biomarker study
• Deciding whether an independent cohort is needed
• Choosing between temporal and external validation

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• 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

Plan a two-sample Mendelian randomization study using a disease outcome and one or more exposures. The skill lays out instrument selection, harmonization, primary and sensitivity analyses, validation, and publication upgrades across four workload levels, with conservative interpretation and verified references.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning an MR screen for an exposure panel and disease
• Designing IVW and sensitivity analyses from summary statistics
• Comparing Lite, Standard, Advanced, and Publication+ plans

Turn a clinical research question into a structured observational study plan using EHR, claims, or registry data. Define the cohort, index date, exposures, outcomes, follow-up, confounding approach, and assumptions the data cannot yet verify.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a comparative effectiveness study with claims data
• Defining time zero and exposure windows for an EHR analysis
• Framing an observational safety study with registry data

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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

Plan a biomedical study to predict response or resistance to a defined treatment. Clarify the population, response endpoint, baseline predictors, model development, and validation approach while surfacing bias, data leakage, feasibility limits, and assumptions that still need confirmation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a treatment response prediction study
• Defining responder and non-responder groups
• Designing a resistance prediction study