Research & Learning skills

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.

• 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

Maps a biomedical topic into research streams, populations, endpoints, methods, and evidence density. It highlights well-covered and thin areas and suggests possible entry points, while keeping those observations separate from formal research gaps or study plans.

• Getting oriented in an unfamiliar biomedical topic
• Mapping evidence before a formal gap analysis
• Structuring a topic before a scoping review

Assess whether a biomedical research area is truly saturated or only busy on the surface. It organizes evidence about repeated study designs, validation depth, and major groups, then maps meaningful entry angles and the timing and feasibility of pursuing them.

• Checking whether a popular disease research topic is still open
• Comparing crowded study designs with less explored research angles
• Assessing whether a research project can be differentiated

Turn a basic biomedical finding into a structured map of possible clinical or therapeutic uses. Compare the evidence, feasibility, and gaps for each path, then identify a defensible next research direction without treating an early finding as clinically ready.

• Mapping clinical uses for a disease mechanism finding
• Comparing biomarker and therapeutic research paths
• Finding evidence gaps between basic research and clinical use

Map biomarkers in a disease area by type, specimen, use case, validation, and maturity. The structured evidence map distinguishes exploratory signals from externally validated or clinically embedded markers, and highlights limitations and gaps without treating popularity as proof of clinical readiness.

• Mapping biomarker evidence by disease and intended use
• Comparing validation and maturity across biomarker classes
• Finding under-validated areas in a research field

Scan biomedical and biological preprints from bioRxiv, medRxiv, and arXiv to map active topics, emerging methods, and early research signals. Get a structured landscape report with source and freshness caveats, plus search terms for independent verification.

• Checking recent preprints in a biomedical research area
• Tracking shifts in competitor research or methods
• Scanning topic momentum before writing an introduction or grant

Use this skill to explore medical and clinical research questions through structured reasoning. It helps examine symptoms and findings, compare possible explanations, understand disease mechanisms and drugs, and assess what medical studies support, while making evidence limits clear.

• Learning how clinicians reason through a diagnostic question
• Understanding disease mechanisms or pharmacology
• Interpreting lab findings in a research context

Reconstructs the operational workflow of a biomedical study from its methods text or other supplied material. It lays out data and sample selection, analysis steps, tools, parameters, and validation, while marking what is reported, inferred, or still missing for replication.

• Turning a methods section into ordered study steps
• Building a replication checklist from a paper
• Finding missing details in an analysis workflow

Screen biomedical papers for fit with a research question, study design, sample adequacy, novelty, and reproducibility value. Get a reasoned recommendation to read the full paper, skim it, skip it, or wait for more information.

• Prioritizing papers for a research project
• Deciding whether to read a paper in full
• Pruning a reading list

Analyzes medical and scientific papers by study type, such as clinical, computational, or experimental research. It weighs evidence, identifies methodological limits and interpretation boundaries, and can prepare related-study comparisons, journal club materials, or follow-up questions.

• Assessing a clinical or biomedical paper
• Preparing a journal club discussion
• Comparing studies of the same type

Build a traceable pool of candidate biomedical papers across databases. The skill adapts search logic to each source, preserves record metadata, labels evidence types such as preprints and trials, and organizes results for later deduplication and screening without treating candidates as final inclusions.

• Collect candidate papers across biomedical databases
• Build database-specific search strategies for a research question
• Prepare a traceable literature pool for deduplication and screening

Turns computational, omics, biomarker, genetic, or clinical findings into a staged cell and animal validation plan. It defines the claim, suitable model families, perturbations, controls, readouts, and workload options while marking feasibility assumptions and limits on interpretation.

• Plan wet-lab follow-up for a computational finding
• Choose cell or animal model families for a specific claim
• Set perturbations, controls, readouts, and experiment order

Audit whether a study’s findings are dependable by examining its design, sample, statistical methods, bias controls, and validation. The result separates reported findings from the reliability judgment and identifies where claims are robust, fragile, or still exploratory.

• Checking whether a study is reliable enough to cite
• Reviewing small-sample or overfitting risks
• Assessing whether a paper’s conclusions exceed its evidence

Design comparative drug safety studies using FAERS, the FDA’s adverse event reporting database, within one defined safety area. The plan compares drugs or classes, lays out workload options and analysis steps, and distinguishes detected signals from conclusions the data cannot support.

• Comparing drug classes within one adverse event area
• Planning a FAERS study with active comparators
• Adding declared subgroup or onset characterization

Build copy-ready biomedical literature queries by combining MeSH subject headings, synonyms, Boolean operators, and justified filters. Adapt a search strategy for PubMed, Embase, Web of Science, or Cochrane, with notes on uncertain mappings and scope.

• Building a PubMed query from a clinical question
• Creating a systematic review search strategy
• Expanding concepts with MeSH terms and synonyms

Analyze why biomedical studies on the same topic reach different conclusions. Compare populations, endpoints, samples, platforms, study designs, models, validation, and bias control to distinguish real conflicts from differences in scope or interpretation.

• Comparing two papers with opposing results
• Checking whether different endpoints explain a disagreement
• Assessing how assay or model choices affect findings

Map specific gaps in care from guidelines, reviews, and real-world or clinical-practice evidence. It organizes where current care falls short across the patient journey, rates how strongly each need is supported, and helps frame research value without treating general disease burden as proof of an unmet need.

• Finding care gaps in a disease area or treatment pathway
• Mapping diagnostic, monitoring, or implementation problems
• Grounding a research proposal in evidence-backed clinical needs

Map how biomedical studies cover relevant populations and subgroups, distinguishing simple mentions from analyzed or validated evidence. Identify meaningful gaps, assess how well they are supported, and prioritize a focused population for follow-up research.

• Finding underrepresented patient populations in a research area
• Checking whether studies analyze age or disease-stage subgroups
• Identifying groups pooled together without sufficient resolution

Explore heredity, Mendelian laws, and inheritance patterns through patient, example-led explanations in Gregor Mendel’s voice. The skill adapts to a learner’s level, connects classical genetics with later discoveries, and marks where evidence or knowledge has limits.

• Understanding dominant and recessive traits
• Working through a Punnett square
• Learning how inheritance patterns work

Turn a biomedical research idea into a structured bulk omics study plan. It clarifies the research question, suggests suitable study patterns and analysis methods, lays out validation and deliverables, and compares four workload levels while marking unverified data assumptions.

• Planning a bulk RNA-seq, proteomics, or metabolomics study
• Comparing Lite, Standard, Advanced, and Publication+ plans
• Designing a biomarker or subtype study with validation steps

Turn a broad biomedical research idea into one primary aim, supporting secondary aims, and hypotheses that can be tested. The skill separates confirmatory questions from exploratory work and aligns each aim with the evidence and study scope needed to support it.

• Narrowing a broad research topic into a coherent study question
• Drafting primary and secondary aims for a biomarker study
• Writing testable hypotheses for a proposed intervention study

Audit verified medical literature to map what a topic already covers, reject generic or unsupported claims of a research gap, and develop credible remaining questions into feasible study opportunities. It distinguishes direct evidence from adjacent studies and flags uncertainty.

• Find evidence-backed gaps in a medical research topic
• Check whether a proposed gap is already addressed
• Turn a credible open question into a study direction

Map how evidence for a disease connects molecular drivers, pathways, cell types, tissue changes, biological effects, and clinical features. The skill labels direct evidence, indirect support, and inference, highlights weak links, and requires cited literature to be verifiable.

• Tracing disease mechanisms from molecules to symptoms
• Preparing a mechanism framework before study design
• Checking where evidence chains are incomplete

Assess whether a medical research idea is genuinely novel and feasible under stated constraints such as data, samples, collaborators, and timeline. Get an explicit start, narrow, redesign, or stop recommendation, with assumptions and evidence gaps clearly identified.

• Checking whether a medical research idea is truly differentiated
• Assessing feasibility with available data, samples, and time
• Choosing whether to start, narrow, redesign, or stop a project