Results for “cell-biology”

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

Use when triaging a study before any writing — stress-tests whether it clears Cell's bar (a complete, mechanistic, hypothesis-driven story with multiple converging lines of evidence) or belongs at a sibling. Use this first to decide Cell vs Molecular Cell vs Cell Reports vs Cell Reports Medicine before investing in framing or figures.

Applies physical principles to model biological systems, including protein folding, membrane transport, molecular forces, and neural signaling.

Analyzes biochemical processes, including enzyme kinetics, metabolic pathways, and biomolecule characterization, with practical techniques and examples.

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

Use when deciding which cell-* sub-skill to invoke next, or when sequencing a manuscript from significance test through reviewer rebuttal for Cell (Cell Press). Routes — it does not replace — the specialized skills.

Notebook Cell References

Use after Cell reviews arrive to triage the decision, prioritize the (often substantial) new experiments by impact × feasibility, and draft a point-by-point response that is respectful, evidence-led, and closes the "completeness" gaps reviewers demand. Do not run before the experiments and revision are actually done.

Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data, enabling efficient access to cell metadata, gene expression slices, summary counts, and embeddings without downloading whole datasets.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over marker lists with an LLM.

Predicts tissue or cell-type gene expression (log TPM and TPM) from a TSS-centered DNA sequence using the hosted Genomic Intelligence G0 Expression model, conditioned on a free-text cell-type description.

Spatial region-aware cell matching for CODEX/scRNAseq integration

Teleological physiology analysis framework for understanding biological systems through multi-constraint optimization. Use when analyzing physiological mechanisms, explaining apparent biological "inefficiencies", preparing for medical examinations (CICM/ANZCA Primary), understanding why biological systems are designed the way they are, or when seeking deeper mechanistic understanding beyond descriptive knowledge. Triggers on questions like "why is X designed this way", "what purpose does Y serve", "how is Z optimized", analysis of physiological trade-offs, or exploration of evolutionary/design constraints.

Annotates single-cell RNA-seq data by scoring marker genes, transferring labels with CellTypist, or reasoning over cluster markers with an LLM.

Predict biomolecular complexes with Chai-1, an open AlphaFold3-style model that folds multi-entity assemblies (proteins, ligands, nucleic acids) from a single typed FASTA — strong on antibody–antigen and protein–ligand complexes, with optional MSA and restraint inputs. Use when predicting an antibody–antigen complex, folding a mixed protein/ligand/nucleic-acid assembly described in one FASTA, or generating a complex with experimental restraints. For binding-affinity prediction or a ligand-focused co-fold prefer alterlab-boltz; for protein-only or protein–protein folding prefer alterlab-alphafold; to dock into a fixed receptor prefer alterlab-diffdock. Part of the AlterLab Academic Skills suite.

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

Use to build Cell's data and code deposition plan and the Data and Code Availability statement that lives inside STAR Methods Resource Availability — approved repositories, accessions/DOIs at submission, and Cell's three-bullet availability format with Mendeley Data as Elsevier's default.

Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O. Use when simulating metabolic networks, predicting growth or knockout phenotypes, or running systems-biology and metabolic-engineering analyses on SBML genome-scale models. Part of the AlterLab Academic Skills suite.

MaxFuse parameter tuning for datasets with large protein:RNA cell ratios (>100:1)

Use to finalize Cell Press display items — column-width sizing, minimum fonts, RGB, show-the-data with defined error bars/n/replicate type, scale bars, colorblind-safe palettes, multi-panel discipline, stand-alone legends, and image integrity.

Botany Based Prediction Skill

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

Discovers and uses scientific datasets, models, blog posts, and interactive demos from a curated catalog for AI/ML work in domains like biology, chemistry, physics, and genomics.

Botany Testing Advanced Skill

Extract battery features for degradation analysis and health monitoring in MATLAB. Covers cycling test features, differential curves (IC/DV/DT), and measurement statistics. Use when working with battery cycling data, SOH estimation, RUL prediction, or any battery test data analysis in MATLAB. Triggers on battery* functions such as batteryTestDataParser, batteryTestFeatureExtractor, batteryMeasurementFeatures, batteryDifferentialCurves.

Botany Design Advanced Skill

Botany Based Simulation Skill

Botany Testing Expert Skill

Applied Botany Analysis Skill

Applied Botany Synthesis Skill

Battery Management System reference — cell balancing, SOC estimation, thermal management, and protection circuits. Use when designing BMS for lithium-ion packs, evaluating battery safety, or understanding cell monitoring.