Results for “bio”

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.

CPRA §1798.121 sensitive personal information restrictions and compliance. Covers all 9 sensitive PI categories including SSN, precise geolocation, racial/ethnic origin, biometric, genetic, health, and sex life data. Right to limit use/disclosure, permitted purposes, and implementation.

Design prospective clinical studies by selecting and classifying endpoints, estimating sample size and power for two-arm designs, and scoring study plans for feasibility with phase-gate decisions.

Provides battle-tested PyTorch training recipes for LLMs, vision, diffusion, and biomedical domains, covering training loops, optimizer selection, LR scheduling, mixed precision, and debugging.

Use to structure a PNAS main text and hold its length — Title, Significance Statement, Abstract, Introduction, Results, Discussion, in-text Materials and Methods, references — and to choose the required Classification (Biological/Physical/Social Sciences + minor subject) and keywords at submission.

Build and analyze phylogenetic trees using MAFFT, IQ-TREE 2, and FastTree, with visualization via ETE3 or FigTree for evolutionary analysis, microbial genomics, viral phylodynamics, and molecular clock studies.

Automatically discovers social media profiles for individuals or brands across platforms like Facebook, Twitter, Instagram, LinkedIn, and TikTok, returning profile URLs, follower counts, and bio snippets as a downloadable CSV.

Extract Xiaohongshu (RedNote) user profile information and published notes list by user ID, returning nickname, bio, follower/following counts, engagement totals, tags, and paginated notes with engagement stats.

Searches Google to discover social media profiles associated with a person, brand, or username, returning platform name, profile URL, username, bio snippet, and follower count across multiple platforms.

Submit and manage protocols on Ginkgo Bioworks Cloud Lab for autonomous lab execution, including protein expression, purification, quantification, RNA synthesis, and custom workflows via EstiMate.

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.

Generates and analyzes proteins using ESM3 and ESM C language models, covering sequence generation, structure prediction, inverse folding, embeddings, and function conditioning with local or cloud-based Forge API inference.

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets.

Detect splice donor and acceptor sites in DNA sequences using the Genomic Intelligence G0 BigBird transformer, via the hosted /v1/tasks/splice/predict API. Returns per-position site probabilities and called sites.

> Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.

This skill recommends performing an imaging study to assess tumor size, appearance, and parasellar extent once biochemical diagnosis of acromegaly is confirmed. Trigger when IGF-1 is elevated and GH fails to suppress to <0.4 µg/L during an oral glucose tolerance test.

Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.

Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

Detect promoter regions in DNA sequences by calling the Genomic Intelligence G0 transformer (GENA-LM BERT Large) hosted API. Returns per-window promoter probabilities and called regions as a report and JSON, from a single FASTA input.

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

Advises against testosterone therapy in men with biochemical recurrence after prostate cancer treatment due to very limited data and potential risk of progression. Consider when a patient has a rising PSA after definitive therapy and the clinician evaluates testosterone for hypogonadism, questioning whether TTh is safe in BCR.

Runs NCBI BLAST+ 2.17.0 sequence searches from the command line: makeblastdb (with -parse_seqids), blastn/blastp/blastx/tblastn with tabular -outfmt 6/7 for parsing, correct -task choice (megablast vs blastn vs blastn-short), -taxids/-negative_taxids taxonomic scoping, and -mt_mode multithreading; plus a DIAMOND blastp --ultra-sensitive path for large protein searches. Warns that -max_target_seqs is a heuristic keep-count, not a top-N best-hits filter. Use when the user wants command-line BLAST, makeblastdb, a local BLAST database, blastn/blastp/blastx/tblastn searches, or DIAMOND protein search. For the Bio.Blast web NCBIWWW API prefer alterlab-biopython; for quick one-liner database lookups prefer alterlab-gget. Part of the AlterLab Academic Skills suite.

Create production-quality landscape materials with the master-material + material-function + material-instance paradigm, RVT, and auto-layering. Use when the user asks for an auto/procedural landscape material, slope/altitude/distance-based layer blending, Runtime Virtual Textures, biome configuration via instances, or layer material functions. For basic layer-blend materials load landscape-materials.

Access the BRENDA enzyme database via its SOAP API to retrieve kinetic parameters (Km, kcat, Ki), reaction equations, organism data, and substrate-specific enzyme information indexed by EC number. Use when looking up enzyme kinetics, turnover numbers, or substrate specificity for biochemical research and metabolic pathway analysis. Part of the AlterLab Academic Skills suite.

Query PubChem via the PUG-REST API and PubChemPy across 110M+ compounds, searching by name, CID, or SMILES and retrieving molecular properties, bioactivity, and similarity/substructure matches. Use when looking up a chemical compound, converting names/SMILES to CIDs, fetching physicochemical properties, or running cheminformatics structure searches. Part of the AlterLab Academic Skills suite.

Esta habilidade deve ser usada ao trabalhar com matrizes de dados anotados em Python, particularmente para análise de genômica de célula única, gerenciamento de medições experimentais com metadados ou manipulação de datasets biológicos em larga escala. Use quando as tarefas envolvam objetos AnnData, arquivos h5ad, dados de RNA-seq de célula única ou integração com ferramentas scanpy/scverse.

Professional CV and resume builder transforming career narratives into ATS-optimized, multi-format resumes. Integrates with career-biographer for data and competitive-cartographer for positioning. Generates PDF, DOCX, LaTeX, JSON Resume, HTML, and Markdown. Activate on 'resume', 'CV', 'ATS optimization', 'job application'. NOT for cover letters, portfolio websites (use web-design-expert), LinkedIn optimization, or interview preparation.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

Search and retrieve preprints from arXiv via the Atom API by keywords, authors, arXiv IDs, date ranges, or subject categories. Use when finding or fetching papers in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, or economics, or resolving an arXiv ID to its metadata and PDF. Part of the AlterLab Academic Skills suite.

Universal code quality principles applicable to all languages. Covers Clean Code, SOLID, complexity metrics, and quality standards. USE WHEN: user mentions "clean code", "SOLID", "code smells", "refactoring", "complexity", asks about "cyclomatic complexity", "cognitive complexity", "code review", "maintainability" DO NOT USE FOR: language-specific linting - use ESLint/Biome skills, security - use OWASP skills, testing - use testing skills

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

Access the European Nucleotide Archive (ENA) via its API and FTP to retrieve DNA/RNA sequences, raw sequencing reads (FASTQ), and genome assemblies by accession, with support for multiple formats. Use when downloading reads or sequences for a study, run, or sample accession, or when sourcing nucleotide data for genomics and bioinformatics pipelines. Part of the AlterLab Academic Skills suite.

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.