Explorar skills

通用项目部署到远程服务器。自动识别项目类型（Node.js/Python/Rust/Go/静态站），SSH 配置、环境安装、项目上传、进程管理、Nginx 反向代理、Cloudflare SSL、安全加固。当用户需要部署项目、上线服务、配置域名时使用

Cloud quantum chemistry platform with Python SDK. Run geometry optimization, conformer generation, torsional scans, and energy minimization (DFT/semiempirical), and retrieve properties (dipole, partial charges, frontier orbitals) — no local QC software or HPC needed.

Chunked N-D arrays with compression and cloud storage. NumPy-style indexing. Backends: local, S3, GCS, ZIP, memory. Dask/Xarray integration for parallel and labeled computation. For lineage use lamindb; for labeled arrays use xarray.

Python toolkit for neurophysiological signal processing: ECG (HR, HRV, R-peaks), EEG (complexity, PSD), EMG (activation onset), EDA/GSR (SCR decomposition), PPG, and RSP. Includes synthetic signal simulation. Alternatives: BioSPPy (less maintained), MNE (EEG/MEG specialist), heartpy (ECG only), scipy.signal (raw DSP).

Bulk RNA-seq DE with R/Bioconductor DESeq2. Negative binomial GLM, empirical Bayes shrinkage, Wald/LRT tests, multi-factor designs, Salmon tximeta import, apeglm LFC shrinkage, MA/volcano/heatmap viz. R gold standard. Use pydeseq2-differential-expression for Python; use edgeR for TMM normalization.

Unified Python framework for extracellular electrophysiology. Load 20+ formats (SpikeGLX, OpenEphys, NWB, Intan, Maxwell, Blackrock), preprocess, run 10+ sorters (Kilosort4, SpykingCircus2, Tridesclous, MountainSort5) via one API, compute quality metrics (SNR, ISI, firing rate), compare sorters, export NWB/Phy. For format-agnostic multi-sorter workflows. For Neuropixels-specific PSTH/decoding use

Detect somatic CNVs from WES/WGS/targeted BAMs (CNVkit v0.9.x). Bin coverage in target/antitarget regions, normalize vs reference, segment with CBS/HMM, call amps/dels, scatter/diagram plots, purity/ploidy, VCF/SEG export. CLI plus Python API (cnvlib). Use GATK CNV for deep WGS with population controls; use CNVkit for targeted/exome where antitarget bins matter.

Benchling R&D Python SDK: CRUD on registry entities (DNA, RNA, proteins, custom), inventory, ELN, workflow automation. Needs Benchling account and API key. Use biopython for local sequence analysis; pubchem for chemical DBs.

Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element. PNG/PDF/SVG export. Use seaborn for quick stats, plotly for interactive.

ENA REST API for sequences, reads, assemblies, and annotations. Portal API search, Browser API retrieval (XML/FASTA/EMBL), file reports for FASTQ/BAM URLs, taxonomy, cross-refs. For multi-DB Python use bioservices; for NCBI-only use pubmed-database or Biopython Entrez.

Construa, leia, valide e modifique modelos de redes biológicas SBML usando a API Python libSBML, com suporte para SBML Níveis 1-3, reações, espécies, regras e extensão FBC. Interopera com COBRApy, Tellurium/RoadRunner e COPASI, sendo ideal para a construção programática de modelos metabólicos/de sinalização baseados em ODE ou restrições.

MATLAB/GNU Octave numerical computing: matrices, linear algebra, ODEs, signal processing, optimization, statistics, scientific visualization. MATLAB-syntax examples run on both. For Python use numpy/scipy; for statistical modeling use statsmodels.